Copyright TechTarget - All rights reserved https://cyber.law.harvard.edu/rss/rss.html Techtarget Feed Generator en Sat, 13 Jun 2026 16:31:27 GMT https://www.techtarget.com/iotagenda editor@techtarget.com <p>5G, the latest generation of cellular technology, delivers faster speeds, lower latency, higher reliability and greater capacity for multiple devices than its 4G predecessor.</p> <p>In the coming years, <a href="https://www.techtarget.com/searchnetworking/definition/5G">5G</a> will become a cornerstone of enterprise communications. To that end, it's essential that organizations thoroughly understand 5G's benefits and challenges now and begin evaluating how the technology will affect the way they do business.</p> <p>This enterprise 5G guide explains how the cellular technology works, its architecture options, emerging use cases, how it compares to 4G and Wi-Fi 6, and more. Click on the links for details about key topics.</p> <section class="section main-article-chapter" data-menu-title="What is 5G?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What is 5G?</h2> <p>5G is the fifth generation of cellular communications technology. Initially released in 2017 by the 3rd Generation Partnership Project (3GPP) after years of development, the standard greatly increases the capacity and versatility of wireless connectivity.</p> <p>5G's potential speed of 20 Gbps is a significant draw, but its low latency -- ultimately two milliseconds or less -- is even more attractive for enterprise applications, such as augmented reality, <a href="https://www.techtarget.com/iotagenda/Ultimate-IoT-implementation-guide-for-businesses">IoT</a>, location awareness and branch connectivity. 5G is engineered to be more secure than its cellular predecessors, thanks to more comprehensive transport security algorithms and other safeguards.</p> </section> <section class="section main-article-chapter" data-menu-title="How does 5G work?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How does 5G work?</h2> <p>5G uses a vast network of <a href="https://www.techtarget.com/searchnetworking/definition/small-cell">small cell</a> base stations located on light poles and building roofs, among other locations, to transmit signals via the millimeter wave (30 GHz to 300 GHz) spectrum. Due to its shorter wavelength, millimeter wave (<a href="https://www.techtarget.com/searchnetworking/definition/millimeter-wave-MM-wave">mmWave</a>) can only travel short distances and is susceptible to weather and obstacles, such as buildings, walls, coated windows and foliage. It works best in densely populated areas or open venues, such as in factories or stadiums, which can be blanketed with low-power small cell stations to avoid line-of-sight limitations.</p> <p>In addition to small cells, 5G networks can be connected and distributed via <a href="https://www.techtarget.com/searchnetworking/feature/Macrocell-vs-small-cell-vs-femtocell-A-5G-introduction">macrocells and femtocells</a>. Macrocells transmit low-frequency radio signals for miles by using large towers and antennas, while femtocells are book-size, private and designed to improve coverage in buildings with furnishings and walls that could obstruct transmission of high-frequency mmWave signals.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/QZCmsHdMwdg?autoplay=0&amp;modestbranding=1&amp;rel=0&amp;widget_referrer=null&amp;enablejsapi=1&amp;origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0"></iframe> </div> <p>Enterprises in areas that aren't served by mmWave can gain access to 5G services through the <a href="https://www.techtarget.com/searchnetworking/feature/The-3-different-types-of-5G-technology-for-enterprises">low-frequency bands</a> (low-band and midband). The tradeoff is support for fewer devices at potentially lower speeds and greater latency. For now, many organizations concentrate their enterprise 5G efforts in dense areas or open venues to take optimal advantage of 5G's capabilities.</p> <p>Two other 5G options are <a href="https://www.techtarget.com/searchnetworking/definition/5G-standalone-5G-SA">5G standalone</a> and non-standalone 5G. Both are <a href="https://www.techtarget.com/searchnetworking/feature/5G-NSA-vs-SA-How-does-each-deployment-mode-differ">valid ways to build 5G networks</a> and provide roadmaps that enterprises can follow when migrating to the 5G standard.</p> <p>The 3GPP continuously reviews 5G standards to improve the technology, so enterprises need to pay close attention to its work. This new generation of cellular technology has its own lingo, so make sure to brush up on the <a href="https://www.techtarget.com/searchnetworking/feature/The-essential-5G-glossary-of-key-terms-and-phrases">5G terms you need to know</a>.</p> </section> <section class="section main-article-chapter" data-menu-title="The differences between 5G and 4G"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The differences between 5G and 4G</h2> <p>5G ushers in dozens of new features and capabilities. 4G cellular service has been instrumental in powering the mobile workforce, but 5G will be better known for improving enterprise operations and making possible the delivery of a new constellation of applications and services.</p> <p><a href="https://www.techtarget.com/searchnetworking/feature/A-deep-dive-into-the-differences-between-4G-and-5G-networks">4G LTE is limited by its spectrum</a>, which only reaches as high as 6 GHz. 5G's millimeter wave operates between 30 GHz and 300 GHz, which means the wider channels can transmit more data. 4G's use of lower-frequency bands impedes latency, speed and capacity, even though its signals can travel farther between radios or tall cell towers. Compared to 4G networks, some 5G networks might be able to support from 10 to 100 times more users and devices per square kilometer.</p> <p>Another key advancement is 5G New Radio (<a href="https://www.techtarget.com/whatis/definition/5G-New-Radio-NR">5G NR</a>), which will eventually replace the long-term evolution (LTE) standard that anchored 4G and previous cellular generations. 5G NR adds <a href="https://www.techtarget.com/searchnetworking/definition/beamforming">beamforming</a> and other techniques that boost 5G's capacity, throughput and range.</p> <p>5G also supports <a href="https://www.techtarget.com/whatis/definition/network-slicing">network slicing</a>. The technique -- unavailable in 4G -- lets enterprises create multiple virtual networks on top of the existing physical network, allowing users to safely and cost-effectively share 5G connectivity.</p> <p>These new capabilities don't come without cost: 5G requires organizations to invest in new core infrastructure that includes base stations and antennas, as well as onboard radios for devices and sensors. 5G's shorter travel distances also demand more infrastructure -- typically, more small cell stations, about the size of a pizza box -- to get signals from one point to another without interference.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/networking-4g_vs_5g-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/networking-4g_vs_5g-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/networking-4g_vs_5g-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/networking-4g_vs_5g-f.png 1280w" alt="4G vs. 5G" height="288" width="559"> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="Business benefits of enterprise 5G"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Business benefits of enterprise 5G</h2> <p>5G offers organizations a flexible and secure connectivity option. To that end, the standard is expected to <a href="https://www.techtarget.com/searchnetworking/tip/What-are-the-features-and-benefits-of-5G-technology-for-businesses">benefit businesses in several key ways</a>, including the following:</p> <ol class="default-list"> <li><b>Automation.</b> Increased speed and lower latency make cellular technology a viable option to bring automation to factories, offices and other facilities.</li> <li><b>Flexible alternatives to dedicated links.</b> 5G services provide less costly and more flexible alternatives to MPLS and other dedicated lines now used for latency-sensitive applications.</li> <li><b>More users and devices.</b> Thanks to its increased capacity, 5G supports more users and devices connected in the same physical area without affecting availability.</li> <li><b>Power savings.</b> 5G can cut the power consumed by devices by up to 90%, giving some IoT devices battery lives that can reach 10 years and making IoT a compelling 5G use case.</li> <li><b>Augmented security.</b> Additional security features, including key management services, make 5G a more trusted option than 4G for IoT, branch and other enterprise traffic.</li> </ol> <p>Providers, manufacturers and the U.S. government are working to <a href="https://www.techtarget.com/searchnetworking/tip/5G-security-Everything-you-should-know-for-a-secure-network">make 5G a secure technology</a>. Newer security tactics, such as zero trust, take advantage of 5G's programmability to ensure only validated users get access. What's more, 5G uses 256-bit encryption, doubling the 128-bit standard used in 4G.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/networking-5G_features_and_benefits.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/networking-5G_features_and_benefits_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/networking-5G_features_and_benefits_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/networking-5G_features_and_benefits.png 1280w" alt="5G features and benefits" height="322" width="560"> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="5G architecture and features"> <h2 class="section-title"><i class="icon" data-icon="1"></i>5G architecture and features</h2> <p>5G architecture supports machine-to-machine communication and other advanced applications better than its predecessors because it can transmit large data streams with low latency and supports a much greater number of connected devices.</p> <p>Three 5G service categories -- <a href="https://www.techtarget.com/searchnetworking/definition/What-are-eMBB-URLLC-and-mMTC-in-5G-Use-cases-explained">eMBB, URLLC and mMTC</a> -- provide many of these advantages. Enhanced mobile broadband enables peak data rates of 10 Gbps to 20 Gbps and is designed to keep data rates steady for large numbers of users as they move through different environments. High-definition video streaming and virtual reality are common uses of eMBB. Ultra-reliable, low-latency communications support autonomous vehicles and other applications that demand immediate response and high network availability. Massive machine-type communications can connect up to 1 million low-power devices -- among them IoT sensors.</p> <p>5G's programmability makes it easier to connect with more data sources, including resources stored in the cloud. Finally, 5G is backward compatible with other wireless technologies, including 3G, 4G and Wi-Fi, enabling enterprises to aggregate the standard with other communications systems.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/networking-slicing_diagram.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/networking-slicing_diagram_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/networking-slicing_diagram_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/networking-slicing_diagram.png 1280w" alt="Diagram of 5G network slicing" height="514" width="559"> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <h3>Private 5G network architecture</h3> <p>5G networks can be either public or private. To better secure their operations, many large enterprises build <a href="https://www.techtarget.com/searchnetworking/definition/private-5G">private 5G</a> networks as an alternative to procuring network capacity from 5G providers. While private networks can be more costly, they enable enterprises to customize their 5G buildouts to meet application requirements, more finely manage infrastructure and better secure data on premises.</p> <p>When enterprises <a href="https://www.techtarget.com/searchnetworking/tip/How-to-build-a-private-5G-network-architecture">consider building private 5G networks</a>, they should ask themselves some key questions:</p> <ol class="default-list"> <li>Do we need ubiquitous coverage for devices or a new type of wireless backhaul?</li> <li>Despite 5G's ability to support higher speeds, are we willing to trade larger cells and lower frequencies for speeds that might not meet expectations?</li> <li>Will most of our traffic stay on our enterprise network or head out to the internet?</li> <li>What device types, capabilities and density will be involved?</li> </ol> <p>Typically, a private 5G network design includes small cell hardware and upstream connectivity to the LAN. Private 5G networks are not one-size-fits-all, however.</p> <h3>5G and Wi-Fi 6</h3> <p>The <a href="https://www.techtarget.com/searchnetworking/feature/A-deep-dive-into-the-differences-between-5G-and-Wi-Fi-6">intersection of 5G and Wi-Fi 6</a> (802.11ax) presents some intriguing options for enterprises. For instance, Wi-Fi 6 might be better suited for congested spaces that have obstacles and little line of sight, while 5G works well in open spaces that require high speeds and low latency. Seamless handoffs between Wi-Fi and 5G networks mean the two technologies can be used together to support a growing mobile workforce.</p> <p>5G and Wi-Fi 6 both have powerful signal modulation, authentication and security features. In addition, each can help companies reduce their power consumption, either by design or through power-saving functions that can reduce the load on access points.</p> <p>Typically, one main difference between cellular and Wi-Fi technology is their respective operation in <a href="https://www.techtarget.com/searchnetworking/answer/Whats-the-difference-between-licensed-and-unlicensed-wireless">licensed versus unlicensed</a> frequency bands. 4G primarily operated only in licensed bands, but 5G operates in both. As a result, using 5G in an unlicensed band could create interference with Wi-Fi. Businesses should carefully map out their coverage.</p> <p>Also, Wi-Fi alone can't transfer sessions between access points. This limitation comes into play if a company wants to use Wi-Fi to track the movement of products. By contrast, 5G can handle those transfers with ease.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineImages/networking-5g_vs_wifi6-f.png"> <img data-src="https://www.techtarget.com/rms/onlineImages/networking-5g_vs_wifi6-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineImages/networking-5g_vs_wifi6-f_mobile.png 960w,https://www.techtarget.com/rms/onlineImages/networking-5g_vs_wifi6-f.png 1280w" alt="5G vs. Wi-Fi 6" height="366" width="560"> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <h3>5G, IoT and edge computing</h3> <p><a href="https://www.techtarget.com/searchnetworking/feature/5G-in-edge-computing-Benefits-applications-and-challenges">IoT and edge computing</a> have distinct demands for high speed and low latency. In many cases, sensors are sending mission-critical information to edge or cloud-based devices to be aggregated, analyzed and acted upon. Examples are <a target="_blank" href="https://www.rantcell.com/do-autonomous-vehicles-need-5g.html" rel="noopener">self-driving vehicles</a>, assembly line equipment and city surveillance cameras that constantly send and receive data.</p> <p>5G's low-power requirements extend battery life, making it a <a href="https://www.techtarget.com/searchnetworking/feature/5G-driving-IoT-innovation-Key-use-cases-and-applications">perfect match for IoT networks</a>. This capability enables enterprises to be innovative in their architecture designs because devices won't have to be tied to a power source.</p> <p>One option is multi-access edge computing (<a href="https://www.techtarget.com/searchnetworking/definition/What-is-multi-access-edge-computing-Benefits-and-use-cases">MEC</a>), a type of edge computing that reduces reliance on centralized cloud servers by enabling local data processing on mobile and cellular <a href="https://www.techtarget.com/whatis/definition/base-station">base stations</a> or other edge nodes. 5G and MEC are closely intertwined. For example, MEC enhances 5G's network slicing capabilities and can make radio access networks (RANs) more responsive, while 5G's low latency and high bandwidth make MEC more effective in real-time applications.</p> <p>Experts recommend enterprises use an application's requirements to select the best wireless connectivity option -- understanding that 5G might be overkill in some cases.</p> <h3>5G and SD-WAN</h3> <p>Organizations can <a href="https://www.techtarget.com/searchnetworking/tip/5G-and-SD-WAN-pair-is-a-game-changer-for-branch-connectivity">pair 5G and SD-WAN</a> to manage wired and wireless connections to remote offices as well as home offices. The combination redefines WAN deployment strategies and offers significant benefits when organizations determine how best to connect distributed workforces.</p> <p>SD-WAN could also be useful in helping sites toggle between 4G and 5G connections, automatically selecting the appropriate link for the demands of the application and traffic conditions. Some industries, including retail, could employ SD-WAN to provision 5G as a primary option for pop-up locations, with secondary links via MPLS and broadband.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/wireless_wan_diagram-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/wireless_wan_diagram-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/wireless_wan_diagram-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/wireless_wan_diagram-f.png 1280w" alt="Basic diagram of 5G wireless WAN architecture" height="301" width="560"> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="Enterprise 5G use cases"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Enterprise 5G use cases</h2> <p><a href="https://www.techtarget.com/searchnetworking/tip/Top-5G-use-cases-for-business-include-fixed-wireless-healthcare">Use cases for enterprise 5G</a> are expanding rapidly as businesses evaluate where the cellular technology could improve their operations. Here are six of the most common ones:</p> <ol class="default-list"> <li><b>Retail.</b> <a href="https://www.techtarget.com/searchnetworking/tip/FWA-use-cases-for-next-generation-connectivity">5G fixed wireless access</a> (FWA) can replace broadband connections, enabling faster connectivity and more flexible management. By combining it with SD-WAN, companies could provision and manage hundreds of locations.</li> <li><b>Healthcare.</b> The healthcare sector is using technology to make greater use of limited resources, including surgical staff. <a href="https://www.techtarget.com/searchnetworking/feature/5G-in-healthcare-9-benefits-and-use-cases">Initial 5G deployments</a> have been mostly geared to improving connectivity for existing mobile devices and patient engagement tools, such as portals, heart monitors and other wearables. However, 5G's low latency could soon enable surgeons to operate remotely via robotic applications. Hospitals also plan to use 5G to transmit critical diagnostic data and images that can be shared among emergency departments, ambulances and field teams to provide faster and more comprehensive care.</li> <li><b>Sports venues.</b> Sports organizations -- among them the National Football League, National Hockey League, National Basketball Association, Major League Baseball and NASCAR -- have deployed 5G to enrich the fan experience through real-time access to video highlights, such as instant replay and more immersive applications.</li> <li><b>Manufacturing.</b> Companies have started to use 5G to speed connectivity from IoT sensors on machines to the cloud for more complex real-time analytics. 5G's speed and low latency mean information extracted from the analytics can be put to use for real-time decision-making that could <a href="https://www.techtarget.com/searchnetworking/feature/10-ways-5G-is-transforming-manufacturing">improve operations on the factory floor</a>.</li> <li><b>Smart cities and autonomous vehicles.</b> Again, the low latency, capacity and throughput of 5G make it a prime candidate for innovation in city management and transportation. Streetlights, signals and other <a href="https://www.techtarget.com/searchnetworking/feature/5G-for-public-safety-Improved-networks-for-first-responders">public safety applications</a> can benefit from 5G to change patterns based on real-time events or AI models. <a href="https://www.techtarget.com/searchnetworking/feature/5G-in-the-automotive-industry-Real-world-uses-and-benefits">Autonomous vehicles</a>, which use AI, machine learning and analytics to process information in real time, can communicate over 5G to automatically adjust speeds in response to road conditions or increased traffic.</li> <li><b>Utilities. </b>Electricity and water companies are among <a href="https://www.techtarget.com/searchnetworking/feature/Private-5G-for-utilities-Benefits-use-cases-and-deployment">utilities increasingly turning to private 5G</a> to manage and secure their vulnerable infrastructures and improve worker safety. Private 5G lets utilities extend their networks to regions with poor connectivity and enables automated metering, monitoring and remote control, even as it helps improve communication and coordination of field crews.</li> </ol> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/networking-5g_business_use_cases.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/networking-5g_business_use_cases_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/networking-5g_business_use_cases_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/networking-5g_business_use_cases.png 1280w" alt="5G use cases" height="372" width="559"> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="5G enterprise challenges"> <h2 class="section-title"><i class="icon" data-icon="1"></i>5G enterprise challenges</h2> <p>For all of 5G's benefits, <a href="https://www.techtarget.com/searchnetworking/feature/The-pros-and-cons-of-5G-networks">enterprises should be mindful of its challenges</a> as they consider the future of their wireless and wired infrastructure.</p> <h3>Network security concerns</h3> <p>5G can simultaneously support more connected users and devices than previous cellular technology, but that also means companies have to assess and monitor many more vectors of exposure. 5G also requires far more extensive infrastructure that must be protected from threats. Experts warn that hackers could use a 5G network to exploit existing vulnerabilities or develop new modes of attack. Finally, the 5G standard itself does not support application-level end-to-end encryption, and that gap early in the connection process can leave enterprises open to attack.</p> <h3>Staffing and training</h3> <p>As with any evolving technology, finding <a href="https://www.techtarget.com/searchnetworking/tip/What-5G-skills-are-most-in-demand">qualified IT staff to integrate 5G</a> will be an ongoing challenge. IT staff need specific skills to oversee a network that seamlessly shifts between wired and wireless connectivity. They must also be able to troubleshoot myriad technical issues as well as manage 5G-enabled network components that range from simple IoT sensors to complicated machinery.</p> <h3>Cost</h3> <p>5G requires a hefty investment to reap its full reward. Legacy network components must be swapped out with 5G-compatible ones. Companies also have to buy new wireless gear to ensure adequate coverage.</p> <h3>Signal interference</h3> <p>Perhaps more than any other wireless technology, 5G requires network teams to pay close attention to site surveys. The easiest use cases are venues with open spaces all under one roof. A site survey can reveal the extent of signal penetration challenges -- specially coated windows, walls, etc. -- and radio dead spots, as well as how much effort would be needed to mitigate them either with a facility redesign or additional equipment, such as antennas.</p> <p>Although enterprises might face some indoor coverage challenges with 5G, <a href="https://www.techtarget.com/searchnetworking/tip/Indoor-5G-gets-a-boost-as-small-cells-come-to-the-rescue">small cell technology can help</a>.</p> <h3>Availability of 5G</h3> <p>Companies that want to take full advantage of 5G enterprise-wide must first determine whether the technology is fully available at all their locations.</p> <p>Service providers have largely succeeded in making 5G available in densely populated areas. Their focus is now shifting to deploying 5G capabilities to more rural and remote areas, and they are <a href="https://www.techtarget.com/searchnetworking/answer/5G-fixed-wireless-access-market-grows-in-the-US">increasingly using FWA</a> to extend broadband internet to those areas. However, service levels -- among them speed and latency -- might not match what enterprise users get in larger cities. That's because carriers targeting rural areas might rely on lower-capacity options that range from employing lower-frequency bands to layering 5G on top of existing LTE backbones to extend 5G services. Building the infrastructure necessary to support high-speed mmWave transmission in rural areas <a href="https://www.techtarget.com/searchnetworking/tip/Top-5G-limitations-for-businesses-include-lack-of-range-devices">still poses a financial and logistical challenge</a>.</p> </section> <section class="section main-article-chapter" data-menu-title="How AI is changing 5G"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How AI is changing 5G</h2> <p>AI has touched nearly every technology sector, and 5G is no exception. <a href="https://www.techtarget.com/searchenterpriseai/feature/How-5G-and-artificial-intelligence-may-influence-each-other">AI and 5G impacts go both ways</a>. Users -- both consumers and enterprises -- expect top performance from their AI apps and platforms. At the same time, carriers and enterprises employ AI to make their 5G networks more intelligent and flexible.</p> <p>For example, <a href="https://www.techtarget.com/searchnetworking/feature/5G-and-AI-What-enterprises-need-to-know">private 5G underpins AI applications</a> that use edge-to-cloud video analytics to spot manufacturing defects, or provide predictive maintenance and coordination of robots in warehouses. Providers are building AI models that can analyze network traffic to identify trouble spots.</p> <p>They're also starting to use AI to design more energy-efficient and reliable RANs. These new <a href="https://www.techtarget.com/searchnetworking/definition/What-is-artificial-intelligence-radio-access-network-AI-RAN">AI-RANs</a> enable AI to run directly on RAN infrastructure and, in some cases, combine the two functions in a software-defined approach that runs in the cloud. The result, proponents say, is RANs that are more secure, reliable and efficient in their use of network resources, and well suited to edge computing.</p> <p>AI-RANs are an example of Open RAN (<a href="https://www.techtarget.com/searchnetworking/definition/What-is-open-RAN-ORAN-Benefits-and-use-cases">ORAN</a>), a mobile architecture designed to standardize proprietary RANs from different vendors so their components are more open and interoperable, which could drive down costs. Major wireless carriers have begun adopting ORAN. The process of standardizing the interfaces between components is overseen by the <a target="_blank" href="https://www.o-ran.org/" rel="noopener">O-RAN Alliance</a>.</p> </section> <section class="section main-article-chapter" data-menu-title="How to find partners and buy 5G"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How to find partners and buy 5G</h2> <p>5G service is only as good as the devices and applications using it, so organizations should chart a roadmap for when enterprise equipment and applications will be available to support 5G. From that, they can create a timeline for procuring 5G services, then carefully examine <a href="https://www.techtarget.com/searchnetworking/feature/Top-5G-infrastructure-companies-to-consider-in-2025">5G infrastructure companies</a> to find one that fits their needs, especially if they're planning a private 5G network.</p> <p>Businesses have to decide whether to buy, lease or build a 5G network. With those three options, enterprises could buy public 5G services from a mobile operator, lease a 5G network slice or build a private 5G network.</p> <p>Enterprises that want to build their own private 5G network should <a href="https://www.techtarget.com/searchnetworking/feature/7-private-5G-vendors-for-businesses">partner with an integrator, vendor or service provider</a> to help with some of the more nuanced aspects of 5G. For example, 5G can significantly increase network traffic, so organizations must assess if other parts of the network -- such as the VPN -- can handle the load.</p> <p>Enterprises that choose to build their own 5G networks should consider the following four factors:</p> <ol class="default-list"> <li>Spectrum for the radio network.</li> <li><a href="https://www.techtarget.com/searchnetworking/definition/5G-infrastructure">5G infrastructure</a> to provide the required features and interfaces.</li> <li>Small cells or microcells to transmit and receive.</li> <li>Interconnected facilities to link the private 5G network to the public mobile network if required.</li> </ol> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/networking-5g_enterprise_partnerships_and_roles-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/networking-5g_enterprise_partnerships_and_roles-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/networking-5g_enterprise_partnerships_and_roles-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/networking-5g_enterprise_partnerships_and_roles-f.png 1280w" alt="5G providers" height="363" width="560"> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="The future of enterprise 5G"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The future of enterprise 5G</h2> <p>Enterprise 5G is all about innovation and applications. What comes next depends on how effectively enterprises take advantage of 5G's speed, low latency and capacity to push AI, machine learning, real-time analytics and other advancements deeper into their operations.</p> <p>New iterations of 5G are arriving on the scene. The first <a href="https://www.techtarget.com/searchnetworking/definition/What-is-5G-Advanced-5GA-or-55G">5G-Advanced standard</a> (3GPP Release 18) came out in June 2024, with initial deployments soon following. Broad rollout of networks and devices is ramping up now and should continue through 2026.</p> <p>Among other benefits, this release was designed to make 5G networks <a href="https://www.techtarget.com/searchnetworking/tip/5G-Advanced-features-include-accurate-timing-AI-support">more intelligent, adaptable and energy-efficient</a>, largely through the deep integration of AI and machine learning. It also added features for the precise timing needed for <a href="https://www.techtarget.com/searchnetworking/definition/What-is-time-sensitive-networking-TSN-vs-5G">time-sensitive networking</a>, which transforms Ethernet -- both wired and wireless -- into a deterministic, real-time network. This gives 5G the guaranteed low latency and reliability required for advanced applications, such as industrial automation and autonomous vehicles. 5G-Advanced also supports extended reality communications, which build on existing <a href="https://www.techtarget.com/searchnetworking/tip/Top-use-cases-for-5G-augmented-and-virtual-reality">augmented and virtual reality applications</a>.</p> <p>A second 5G-Advanced release, 19, was expected to be solidified late in 2025 and build on its predecessor with additional support for network intelligence, low latency and time-sensitive applications. Read more about <a href="https://whatis.techtarget.com/feature/5-Predictions-about-5G-Adoption-in-2021-and-Beyond">what might happen with 5G</a> in the coming years.</p> <p>Meanwhile, the 3GPP is working on <a href="https://www.techtarget.com/searchnetworking/definition/6G">6G</a> technology, expected to launch commercially in 2030 and potentially support data rates of up to 1 Tbps. 6G will build on 5G's capabilities for applications, such as imaging, presence technology and location awareness. 6G technology will be able to selectively use different frequencies to measure electromagnetic absorption rates and adjust frequencies accordingly.</p> <p><i>Chuck Moozakis is editor at large of the Infrastructure group at TechTarget. </i></p> <p><i>David Essex is an industry editor who creates in-depth content on enterprise applications, emerging technology and market trends for several Informa TechTarget websites.</i></p> </section> An enterprise 5G deployment requires extensive planning. This guide helps you understand 5G use cases and deployment options as well as the latest advances in wireless technology. https://cdn.ttgtmedia.com/visuals/digdeeper/6.jpg https://www.techtarget.com/searchnetworking/Enterprise-5G-Guide-to-planning-architecture-and-benefits Wed, 17 Dec 2025 00:00:00 GMT <p><iframe title="Living up to the hype: Lessons from IoT supply chain wins" allowtransparency="true" height="150" width="100%" style="border: none; min-width: min(100%, 430px); height: 150px;" scrolling="no" data-name="pb-iframe-player" src="https://www.podbean.com/player-v2/?i=3xdvm-19d477f-pb&amp;from=pb6admin&amp;pbad=0&amp;share=1&amp;download=1&amp;rtl=0&amp;fonts=Arial&amp;skin=1&amp;font-color=auto&amp;logo_link=episode_page&amp;btn-skin=2baf9e" loading="lazy"></iframe></p> <p>The applications of IoT in supply chain management have always made a lot of sense, at least in theory.</p> <p>The relatively affordable, internet-connected sensors IoT makes possible seem tailor-made for the day-to-day realities and challenges of supply chains. Much of the work of supply chain management (<a href="https://www.techtarget.com/searcherp/Guide-to-supply-chain-management">SCM</a>) involves tracking and optimizing the movement of millions of goods around the globe, from raw materials through manufacturing, distribution, sales and returns. <a href="https://www.techtarget.com/iotagenda/definition/smart-sensor">IoT sensors</a> are ideal vehicles for collecting and transmitting the data companies need for a host of supply chain processes, including traceability that verifies a product's country of origin, cost and quality controls in procurement, inventory optimization in warehouses and timely shipping to stores.</p> <p>But has IoT lived up to its promise a decade after its initial growth spurt and hype?</p> <p>"We are at the stage where we can safely say that we are past the hype and we are seeing some real wins right now," especially in warehouses, transportation, cold chain management and machine maintenance, said Subodha Kumar, a professor at Temple University in Philadelphia. "We have seen fewer stockouts, less spoilage. We have seen less maintenance downtime."</p> <p>In this episode of <i>Enterprise Apps Unpacked</i>, Kumar explains the challenges typically faced by companies implementing IoT in their supply chains, the hurdles that remain for the broader IoT industry and how the widespread availability of inexpensive AI has made IoT more useful.</p> <section class="section main-article-chapter" data-menu-title="AI spurs IoT growth"> <h2 class="section-title"><i class="icon" data-icon="1"></i>AI spurs IoT growth</h2> <div class="imagecaption alignRight"> <img src="https://cdn.ttgtmedia.com/rms/onlineimages/kumar_subodha.jpg" alt="Photo of Temple University Prof. Subodha Kumar">Subodha Kumar </div> <p>Kumar is an expert in the complex interactions between supply chains and digital technology. He is a chair of statistics, operations, data science and information systems at Temple and directs its Ph.D. program in operations and SCM. He is also active in professional associations and journals focused on operations management and IT. For example, a 2025 journal article <a target="_blank" href="https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=8726&amp;context=lkcsb_research" rel="noopener">he co-wrote</a> explores promising applications and research in using IoT in <i>intralogistics</i>: the logistics of moving and storing goods within facilities, such as factories, warehouses and ports.</p> <p>Kumar said there are two major ways generative and agentic AI are changing how IoT is used in supply chains. "They have converted these IoT data into real time decision making," he said, giving the example of the pharmaceutical supply chain. The AI can analyze temperature and humidity data and decide whether to discard the product lot or modify its expiration date. "You can make these decisions in real time. You don't have to wait."</p> <p>Recalls and the ability to trace products are another area of AI use cases that's taking off. Kumar cited the major push by large retailers, including Walmart, to <a href="https://www.techtarget.com/searchcio/Blockchain-for-businesses-The-ultimate-enterprise-guide">use IoT and blockchain</a> to trace the movement of spinach and other vegetables through the supply chain. AI can initiate a recall and then investigate the issues that triggered it.</p> <p>AI and IoT are showing synergies in another "very interesting" way, he said. "These AI-based systems would not work unless we have very granular data. That is also working as a catalyst to grow more IoT-based systems," Kumar said. "More and more companies are deploying these sensors in different places that can pull data in real time."</p> <p>Other topics discussed in the podcast include the following:</p> <ul class="default-list"> <li>Which IoT supply chain applications have the quickest ROI.</li> <li>Where IoT fits in the ecosystem of supply chain applications, including ERP systems.</li> <li>Future applications of AI and IoT in supply chains.</li> </ul> <p><i>David Essex is an industry editor who covers enterprise applications, emerging technology and market trends, and creates in-depth content for several TechTarget websites.</i></p> </section> In this podcast, Temple University professor Subodha Kumar explains trends in using IoT in supply chains, deployment challenges to expect and why AI boosts IoT demand and value. https://cdn.ttgtmedia.com/visuals/digdeeper/5.jpg https://www.techtarget.com/searcherp/podcast/Living-up-to-the-hype-Lessons-from-IoT-supply-chain-wins Mon, 01 Dec 2025 05:00:00 GMT <p>Automotive vehicles -- from passenger cars to commercial autonomous vehicles -- have become intelligent devices, and they rely on increasing amounts of computing power and connectivity to operate.</p> <p>A combination of digital technologies, including machine learning, other types of <a href="https://www.techtarget.com/searchnetworking/feature/5G-and-AI-What-enterprises-need-to-know">AI and the internet of things</a>, drives these advances in the automotive industry. Among the most critical technologies is <a href="https://www.techtarget.com/searchnetworking/definition/5G">5G</a>, the fifth generation of wireless cellular technology.</p> <p>5G connectivity is poised to experience significant growth in the coming years. A report from Global Market Insights valued the market in 5G automotive-grade products at $2.1 billion in 2023 and predicts a compound annual growth rate of 19% between 2024 and 2032.</p> <p>"As consumers and businesses increasingly seek vehicles with advanced connectivity features, the need for high-speed, low-latency communication provided by 5G technology is rising," the report stated. "This demand is driven by the desire for enhanced in-car experiences, such as real-time navigation, infotainment and vehicle-to-everything (V2X) communication, which improves safety and efficiency."</p> <section class="section main-article-chapter" data-menu-title="Benefits of 5G in the automotive industry"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Benefits of 5G in the automotive industry</h2> <p>Each new generation of cellular technology is engineered to improve on the last, and 5G is no exception. 5G brings increased speed and bandwidth to cellular networks compared with its predecessor, 4G, and the <a href="https://www.techtarget.com/searchmobilecomputing/definition/Long-Term-Evolution-LTE">LTE</a> technology that formed the global basis for 4G networks. 5G also has lower latency.</p> <p>Those features of 5G enable numerous use cases in the automotive sector, bringing several key benefits:</p> <ul class="default-list"> <li><b>Faster, more dependable data exchange.</b> This is a keystone benefit of 5G, enabling nodes -- sensors on vehicles, connected vehicles themselves and manufacturing plants -- to share data quickly, consistently and reliably.</li> <li><b>Enhanced and expanded connectivity.</b> Because 5G has higher bandwidth, it can support more connected nodes, more data coming from additional sources and more data being exchanged between nodes, which are essential in <a href="https://www.wardsauto.com/news/archive-wards-it-s-time-to-mandate-v2v-technology-and-do-it-now/797680/" target="_blank" rel="noopener">vehicle-to-vehicle</a> (V2V) and V2X communication. "A car could connect to another car," said Michele Polese, an assistant research professor of electrical and computer engineering at Northeastern University, noting that this is still an emerging capability. "It's called <i>side link</i>, where devices connect so cars can share data."</li> <li><b>New, improved features and capabilities.</b> With faster, reliable data exchange, engineers can deliver capabilities such as <a href="https://www.techtarget.com/searchenterpriseai/definition/driverless-car">autonomous driving</a>. Car manufacturers can also use 5G to remotely update software on their vehicles. "Updates had been done with Wi-Fi, but those earlier updates weren't that intensive. 5G provides the high bandwidth and low latency needed for updates today," said Octavio Garcia, senior analyst at Forrester Research.</li> <li><b>Expansion of smart automotive manufacturing.</b> Automotive factories use public and <a href="https://www.techtarget.com/searchnetworking/definition/private-5G">private 5G</a> networks to support AI and robotics throughout the manufacturing process.</li> <li><b>Increased safety and driving accuracy.</b> Analyses of the data exchanged over 5G networks, combined with machine learning and AI capabilities, enable applications designed to improve vehicle and traffic safety.</li> <li><b>Increased efficiency.</b> 5G creates efficiencies by supporting improved manufacturing processes, optimized logistics and enhanced vehicle connectivity.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="5G-enabled use cases in the automotive sector"> <h2 class="section-title"><i class="icon" data-icon="1"></i>5G-enabled use cases in the automotive sector</h2> <p>The low latency and high bandwidth provided by 5G, along with the data exchange it enables, support numerous applications and use cases. They include the following:</p> <ol class="default-list"> <li><b>Autonomous driving.</b> 5G allows for real-time communication between vehicles, infrastructure such as traffic control systems, and cloud computing in which data is analyzed to generate precise decision-making and actions, thereby enabling computers to safely drive vehicles and navigate without human intervention. "The car cannot carry enough compute to truly drive itself around. It needs access to the network because it offloads data to a server in the cloud," said David Witkowski, senior member of IEEE, an association of electrical and computer engineers and other technologists.</li> <li><b>Fleet management.</b> Sensors on connected vehicles transmit data that enables centralized tracking and management of the vehicles. 5G provides the connectivity for sharing not only vehicle location data from GPS but more detailed, real-time information, Garcia said.</li> <li><b>Platooning.</b> V2V communication enables platooning, where vehicles -- typically commercial trucks -- travel in a synchronized, single-file line. "You need low latency as well as reliability for platooning," Polese said.</li> <li><b>Predictive maintenance.</b> The data generated on connected vehicles can be analyzed to determine what maintenance is required, enabling car owners, fleet managers, manufacturers and service providers to service or repair vehicles before a breakdown occurs or performance is diminished. 5G also supports centralized control and real-time diagnostics, which can reduce downtime and improve operational efficiency.</li> <li><b>Smart roadways and infrastructure.</b> With V2X communication, data can move between vehicles and roadway infrastructure such as traffic lights, public safety systems and road sensors. This enables smart systems to create more efficient traffic flow, reduce accidents, support real-time route adjustments and send alerts about hazards and accidents to emergency services.</li> <li><b>Route optimization.</b> In similar fashion, 5G's ability to quickly and reliably move massive amounts of data enables fleet managers and others to optimize routes in advance or in near real time to respond to changing road conditions.</li> <li><b>Intelligent manufacturing.</b> According to Garcia, 5G supports the use of <a href="https://www.techtarget.com/searcherp/definition/digital-twin">digital twins</a>, robotics, AI and real-time analytics in manufacturing, boosting agility, efficiency and productivity in automotive factories, while also supporting enhanced safety and quality control measures.</li> <li><b>Enhanced driver and passenger experiences.</b> 5G enables real-time updates of driving conditions, as well as personalized information, services and infotainment for drivers and passengers. The capacity provided by 5G is particularly important for AI applications, such as AI-enabled dashboard cameras, Witkowski said.</li> <li><b>Vehicles as mobile hot spots.</b> 5G's support for internet hot spots is another way it accommodates the growing demand for constant connectivity.</li> <li><b> On-vehicle telematics.</b> Data from onboard sensors that need to be monitored, such as those on refrigerated trucks -- where maintaining a constant temperature is essential -- need 5G's capacity, Witkowski said.</li> </ol> </section> <section class="section main-article-chapter" data-menu-title="Key considerations"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Key considerations</h2> <p>The automotive industry has already benefited from 5G, which was introduced in 2019. Experts expect the industry to expand and improve on 5G applications.</p> <p>However, this latest generation of cellular network connectivity is far from universally available. That limits where the automotive sector can deploy applications that rely on 5G.</p> <p>Witkowski explained that some regions have <a href="https://www.techtarget.com/searchnetworking/feature/A-deep-dive-into-the-differences-between-4G-and-5G-networks">5G but with a 4G</a> core, while some only have 4G. Pockets of the United States have no connectivity at all. "That's kind of a lowlight, because many of the things we thought 5G could be haven't materialized."</p> </section> <section class="section main-article-chapter" data-menu-title="The future of 5G in the automotive industry"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The future of 5G in the automotive industry</h2> <p>Although 5G supports significantly more applications, thanks to its latency, reliability and bandwidth advantages, carriers have not fully implemented the technology across their networks.</p> <p>They lack the financial incentive in some markets because they don't anticipate having enough customers to deliver a positive ROI in the desired time frame, Witkowski said.</p> <p>But the customers aren't there because they can't launch their applications unless 5G is already in place. "It leads me to believe that 5G isn't as much of a revolutionary upgrade as we wanted it to be," he added. "We haven't made true use of 5G yet."</p> <p>But Witkowski and others said they expect that carriers will continue to build out their 5G networks and that more customers, including in the automotive sector, will take advantage of 5G's capabilities. It will happen through the process of using 5G to expand the reach of applications they've already developed and by continuing to develop new ways to harness 5G's power.</p> <p>And while some are looking ahead to the next generation, <a href="https://www.techtarget.com/searchnetworking/definition/6G">6G</a>, others suggest it might be worth delaying its anticipated 2030 arrival, given where 5G adoption is today.</p> <p>As for the automotive sector, Witkowski said 5G is proving capable of handling the industry's applications and use cases as they exist now.</p> <p><i>Mary K. Pratt is an award-winning freelance journalist with a focus on covering enterprise IT and cybersecurity management.</i></p> </section> 5G's speed and bandwidth enable numerous applications, from smart manufacturing to autonomous driving, route optimization, predictive maintenance and in-vehicle entertainment. https://cdn.ttgtmedia.com/rms/onlineimages/iot_g1204761980.jpg https://www.techtarget.com/searchnetworking/feature/5G-in-the-automotive-industry-Real-world-uses-and-benefits Thu, 13 Nov 2025 12:57:00 GMT <p>Modern manufacturing is undergoing significant changes, and many manufacturers believe that fifth-generation, or <a href="https://www.techtarget.com/searchnetworking/definition/5G">5G</a>, cellular connectivity will be critically important to the future success of the industry.</p> <p>Indeed, adoption of 5G technology is now considered the key to the fourth industrial revolution (<a href="https://www.techtarget.com/searcherp/definition/Industry-40">Industry 4.0</a>), which focuses on improving efficiency and flexibility in manufacturing processes. Achieving these goals requires automation capabilities and seamless exchange of data in an environment where users and devices are always connected.</p> <p>5G provides that environment by enabling high-bandwidth, low-latency and high-capacity wireless connectivity. Not only is 5G connectivity faster, but it is also more secure and stable than previous generations of cellular technology. For manufacturers, the move to 5G technology leads to real-time data analytics that drive increased efficiency, optimized processes, improved flexibility, more safety and reduced costs.</p> <p>Coupled with advanced AI, 5G implementations are enabling manufacturers to cash in on more flexible, efficient and automated processes. They are also taking advantage of AI in applications for real-time quality-control analytics, predictive maintenance, machine-to-machine robotics communication and supply chain optimization.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/Boa8srjKzCI?autoplay=0&amp;modestbranding=1&amp;rel=0&amp;widget_referrer=null&amp;enablejsapi=1&amp;origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0"></iframe> </div> <p>Here are 10 of the most important ways 5G is transforming the manufacturing sector.</p> <section class="section main-article-chapter" data-menu-title="1. Industry 4.0"> <h2 class="section-title"><i class="icon" data-icon="1"></i>1. Industry 4.0</h2> <p>5G serves as the connectivity foundation for Industry 4.0, according to Michael Weller, global practice lead for manufacturing, energy and utilities at telecommunications provider Verizon Business.</p> <p>Industry 4.0 requires a fully digital, data-driven and intelligent manufacturing environment. If Industry 4.0 is the brain, then 5G is the high-speed nervous system, said Vamshi Rachakonda, executive vice president at technology services provider Capgemini, in an email. It is the enabling technology that connects the physical world of the factory with the digital world of software, AI and data analytics.</p> <p>You cannot have a true Industry 4.0 environment with its emphasis on real-time control, predictive analytics and automation without the powerful and reliable connectivity that 5G provides, Rachakonda said.</p> <p>"We see 5G as having a symbiotic relationship with AI in manufacturing," Weller wrote in response to emailed questions. "The technology's low-latency secure connectivity drives Industry 4.0 by enabling smart factories to activate intelligent automation and interconnected manufacturing systems."</p> </section> <section class="section main-article-chapter" data-menu-title="2. Improved data transfer and decision-making"> <h2 class="section-title"><i class="icon" data-icon="1"></i>2. Improved data transfer and decision-making</h2> <p>One significant benefit manufacturers are seeing after adopting 5G is the ability to unlock and act on real-time data from the factory floor, Rachakonda said. No wonder approximately <a title="https://www.capgemini.com/insights/research-library/reindustrialization-of-europe-and-us-2025/" target="_blank" href="https://www.capgemini.com/insights/research-library/reindustrialization-of-europe-and-us-2025/" rel="noopener">75% of executives</a> ranked 5G technology as critical to reindustrialization investments for their organization.</p> <p>The reasons are simple: 5G provides a reliable, high-speed wireless network for connecting thousands of machines, sensors and systems. This capability enables companies to streamline their operations, enhance workforce productivity and reduce costs. He offered the example of mining, where companies are using <a href="https://www.techtarget.com/searchnetworking/definition/private-5G">private 5G</a> networks to run automated vehicles, which boosts efficiency and improves worker safety.</p> <p>5G also facilitates real-time information sharing across factory floors, meeting younger digital-first employees where they are to help them understand manufacturing processes and learn important skills.</p> <p>Many manufacturers are currently operating in "capture and report" mode rather than "capture and react," Weller said. They're collecting IoT data but not yet turning it into actionable insights in real time. 5G technology addresses this gap by providing the connectivity needed to transmit large data sets from the factory floor, enabling real-time AI and <a href="https://www.techtarget.com/searchdatacenter/definition/edge-computing">edge computing</a> integration across business operations.</p> </section> <section class="section main-article-chapter" data-menu-title="3. Flexibility and adaptability"> <h2 class="section-title"><i class="icon" data-icon="1"></i>3. Flexibility and adaptability</h2> <p>Deploying 5G technology and having more than one networking option enable manufacturers to create flexible, adaptable production environments that can evolve with changing demands.</p> <p>"It enables the seamless integration of intelligent systems that define modern smart factories," Weller said. The technology also significantly reduces environmental impact by eliminating copper cabling, which typically contains 13 tons of copper per million linear feet, and by requiring fewer control systems, thereby reducing power consumption. Using 5G to simplify network architecture enables one cellular antenna to replace up to 10 Wi-Fi access points, he said.</p> </section> <section class="section main-article-chapter" data-menu-title="4. Increased support and longevity for devices and batteries"> <h2 class="section-title"><i class="icon" data-icon="1"></i>4. Increased support and longevity for devices and batteries</h2> <p>The more that organizations use technology such as 5G and AI, the more that important things, such as battery life of connected devices, are affected, said Jeff Kagan, a wireless industry analyst.</p> <p>"Power has become one of the most vital commodities. Battery power does not last forever. That's why improvements in batteries to keep devices online and working are key," Kagan said in an email interview.</p> <p>The increasing need for power for new technologies like AI is likely to outstrip supply, Kagan said, requiring new ways of thinking and power policies that consider the needs of tomorrow. People do not want to see their electricity bills go up to support AI and other power-hungry technologies, he said.</p> <p>5G connectivity can also provide the following benefits:</p> <ul class="default-list"> <li><b>Reliability.</b> Private 5G networks provide a stable, consistent connection that isn't susceptible to interference from other devices, which is critical for preventing business disruption.</li> <li><b>Support.</b> The reliability of 5G enables far more effective remote support. A technician can connect from anywhere in the world and get a real-time view of a machine's operations to diagnose a problem, guide an on-site technician and make adjustments.</li> <li><b>Battery life.</b> 5G's power-efficient design extends sensor battery life from months to several years and enables smaller batteries that reduce waste and lower costs. This is critical for managing the massive number of new devices that IoT sensor technology requires.</li> </ul> <p>"With its low latency and higher capacity, 5G will enable ultra-reliable connections for mission-critical tasks, while also introducing new power demands that can affect battery performance, particularly on older devices," Weller said. "The overall impact will vary significantly depending on the device type, network infrastructure and application."</p> </section> <section class="section main-article-chapter" data-menu-title="5. Real-time equipment monitoring"> <h2 class="section-title"><i class="icon" data-icon="1"></i>5. Real-time equipment monitoring</h2> <p>5G's high-speed connectivity enables real-time <a href="https://www.techtarget.com/searcherp/definition/supply-chain-visibility-SCV">supply chain visibility</a> and data-driven decision-making while boosting overall equipment effectiveness, machine uptime and secure protection of critical systems. 5G also enables flexible network integration with other connected devices, ensuring uninterrupted communication across supply chain components, Weller said.</p> <p>Manufacturing environments are becoming increasingly visual and data-intensive, which calls for strong wireless networks to support real-time <a href="https://www.techtarget.com/searchenterpriseai/definition/machine-vision-computer-vision">computer vision</a>, digital collaboration tools and immersive worker experiences. Ultimately, 5G enables manufacturers to quickly respond to changes while maintaining optimal performance.</p> </section> <section class="section main-article-chapter" data-menu-title="6. AR/VR-based remote assistance"> <h2 class="section-title"><i class="icon" data-icon="1"></i>6. AR/VR-based remote assistance</h2> <p>At the data layer, 5G supports massive <a href="https://www.techtarget.com/iotagenda/definition/IoT-integration">IoT integration</a> by streaming high volumes of sensor data without lag, enabling instant AI insights and harnessing edge computing for faster decision-making, according to Jay Lawrence, CEO of Equus Compute Solutions, a provider of digital infrastructure services, including 5G connectivity. Remote operations become more practical because managers can monitor equipment virtually, conduct digital audits and troubleshoot issues without costly delays.</p> <p>5G technology also creates opportunities for remote sites that use satellite connectivity where fiber infrastructure isn't feasible. These locations are often the most dangerous and technologically behind, so they benefit significantly from enhanced connectivity, Weller said.</p> <p>5G's ultra-reliable, low-latency connectivity creates the essential backbone for interconnected workers, mobile robotics, sensors, scanners, cameras and augmented reality/virtual reality (<a href="https://www.techtarget.com/whatis/definition/augmented-reality-AR">AR</a>/VR) systems that drive the flexible, efficient operations essential for modern manufacturing.</p> <p>"For employees, immersive AR and VR training supports faster skill development, connected tools simplify complex tasks, and seamless data-sharing accelerates collaboration," Lawrence said in emailed responses. "Quality control processes are strengthened by AI-powered vision systems that detect defects instantly, continuous monitoring that enforces compliance and real-time alerts that enable immediate corrective action."</p> </section> <section class="section main-article-chapter" data-menu-title="7. Reduced security vulnerabilities"> <h2 class="section-title"><i class="icon" data-icon="1"></i>7. Reduced security vulnerabilities</h2> <p>5G networks provide the connectivity needed to deploy security options that create protective layers around legacy manufacturing systems, addressing vulnerabilities in decades-old operating systems while maximizing machine uptime and productivity.</p> </section> <section class="section main-article-chapter" data-menu-title="8. Smart manufacturing practices"> <h2 class="section-title"><i class="icon" data-icon="1"></i>8. Smart manufacturing practices</h2> <p>5G enables wireless connectivity for mobile automation, including autonomous mobile robots, automated guided vehicles and material-handling equipment, such as forklifts and pallet handlers.</p> <p>While manufacturers are currently implementing low-risk AI projects in non-core areas due to security and computing concerns, 5G is providing the reliable infrastructure needed to support mobility and real-time coordination of technology in discrete manufacturing applications, such as pick-and-pack operations, pre-inspection and basic assembly, Weller said.</p> <p>Meanwhile, smart factories benefit from the convergence of robotics, AI and IoT into unified systems that enable autonomous operations and scalable, fully automated ecosystems, according to Lawrence.</p> </section> <section class="section main-article-chapter" data-menu-title="9. Edge computing benefits"> <h2 class="section-title"><i class="icon" data-icon="1"></i>9. Edge computing benefits</h2> <p>5G's true potential is often realized when it is combined with edge computing -- a model where data is processed locally, right on the factory floor, instead of being sent to a distant cloud, Rachakonda explained. The combination of 5G's speed and edge computing's local processing power enables decisions to be made in milliseconds, marking the next major step in creating truly intelligent, autonomous industrial environments.</p> </section> <section class="section main-article-chapter" data-menu-title="10. Reduced overhead costs"> <h2 class="section-title"><i class="icon" data-icon="1"></i>10. Reduced overhead costs</h2> <p>5G delivers significant cost savings through reduced wired network complexity, lower infrastructure requirements and decreased power and cooling needs.</p> <p>The benefits of 5G extend directly to the bottom line, with <a href="https://www.computerweekly.com/news/366627978/AI-driven-predictive-maintenance-gaining-traction">predictive maintenance</a> reducing downtime, lower energy consumption driving efficiency, and fewer infrastructure requirements cutting setup costs, Lawrence said.</p> <p>"Machine productivity is also elevated, as real-time optimization and AI-driven performance maximize throughput while automated updates minimize interruptions," he said.</p> </section> <section class="section main-article-chapter" data-menu-title="How 5G and AI will affect the future of manufacturing"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How 5G and AI will affect the future of manufacturing</h2> <p>In addition to the benefits that 5G is already bringing to manufacturing, when combined with the capabilities of AI, 5G connectivity will boost data analysis and automation, enabling manufacturers to become even more nimble, efficient and scalable. Manufacturers will increasingly benefit from 5G's low latencies, high-speed data capabilities and unmatched bandwidth.</p> <p>Further, 5G will enable communication among machines, robots and devices on the factory floor to share and act on data in real time. That will allow for greater efficiencies, increased production and decreased downtimes.</p> <p>"The future of manufacturing is about using data to make better, faster decisions, and 5G provides the robust, potentially lower-cost, low-latency connectivity needed to make that a reality," Rachakonda said. "It moves operations beyond the constraints of wired connections and enables the widespread use of technologies like AI, IoT and advanced automation that are the hallmarks of a modern, competitive manufacturing operation."</p> <p>Manufacturers will need such advanced connectivity to support their increased demand for next-generation technologies, Lawrence said. 5G offers unparalleled scalability with its ability to connect thousands of IoT sensors, machines and systems to a single facility, and its reliability ensures mission-critical operations run smoothly, thereby avoiding costly delays and disruptions.</p> <p>"More than just an upgrade, 5G serves as the enabling fabric of the smart manufacturing revolution," he said.</p> <p><i>David Weldon is a freelance writer in the Boston area who covers topics related to IT, data management, infosec, healthcare tech and workforce management.</i></p> </section> 5G's bandwidth, latency and capacity advantages are essential to a vision of manufacturing that exploits AI, IoT and data analytics for greater flexibility and efficiency. https://cdn.ttgtmedia.com/rms/onlineimages/map_globe_g1278866306.jpg https://www.techtarget.com/searchnetworking/feature/10-ways-5G-is-transforming-manufacturing Sun, 02 Nov 2025 14:00:00 GMT <p>Most telecom experts agree that the future of 5G technology lies in edge computing, in which 5G wireless networks with distributed computing resources are placed near the "edge" of the network or close to where data is generated.</p> <p>The goal of 5G edge computing is to reduce latencies or delays so that organizations can process more data faster or store data locally for reliability or regulatory reasons. 5G, with its higher bandwidth, provides the connectivity backbone that makes edge deployments much more viable. It brings computing closer to the source, so the two together can support demanding new applications.</p> <section class="section main-article-chapter" data-menu-title="What is 5G edge computing?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What is 5G edge computing?</h2> <p>5G edge computing is a paradigm in which computing, storage and network functions are placed closer to users or data sources, such as sensors, rather than being concentrated in remote data centers.</p> <p>"5G is the wireless protocol that we use to transmit over our devices to a tower and ultimately base station," said Jack Fritz, principal in Deloitte Consulting's technology, media and telecommunications practice. He added that combining 5G with edge technology brings more computing power to users' wireless applications.</p> <p>A key architectural model under 5G edge computing is multi-access edge computing (<a href="https://www.techtarget.com/searchnetworking/definition/What-is-multi-access-edge-computing-Benefits-and-use-cases">MEC</a>), sometimes called <i>mobile edge computing</i>. MEC is defined by telecom standards-setting bodies European Telecommunications Standards Institute and Third Generation Partnership Project to provide an IT service environment, including computing, storage and network at the edge, enabling applications and services to run there with less latency, improved bandwidth efficiency and more control over where data is stored. MEC also supports multiple access technologies, including cellular, Wi-Fi and other technologies, so it is not limited to just one kind of network link.</p> <p>The 5G standard contains specifications for how to support edge computing in the 5G core -- that is, a 5G network's central control and management software -- as well as the <a href="https://www.techtarget.com/searchnetworking/definition/radio-access-network-RAN">radio access network</a>. The architecture generally <a target="_blank" href="https://www.3gpp.org/technologies/edge-computing" rel="noopener">involves</a> the following:</p> <ul class="default-list"> <li><b>Edge application servers </b>deployed at edge nodes to host applications and services.</li> <li><b>Edge enabler clients</b>,<b> </b>which reside on user devices and communicate with edge enabler servers so that the device can discover and connect with edge services.</li> <li><b>User-plane function</b>, which<b> </b>plays a key role in data transfer and packet processing, enabling traffic to be broken out or anchored locally so that data doesn't always have to travel back to core network servers.</li> </ul> <h3>Key components</h3> <p>Edge computing typically involves several components, including the following:</p> <ul class="default-list"> <li><b>Edge devices.</b> These are the actual endpoints generating or consuming data. Examples include IoT <a href="https://www.techtarget.com/iotagenda/definition/smart-sensor">smart sensors</a>, cameras, vehicles, smartphones and robots that connect to edge nodes for processing.</li> <li><b>Edge nodes and servers.</b> These include local computing units deployed at cell towers, base stations, on-premises sites or regional data centers. They <a target="_blank" href="https://www.ibm.com/think/topics/edge-computing" rel="noopener">host applications</a> and perform data processing near the source.</li> <li><b>Network infrastructure.</b> This connectivity layer includes 5G base stations, small cells, routers and switches that link devices to the edge and the cloud, ensuring low-latency data transport.</li> <li><b>Virtualization and containerization platforms.</b> These include technologies, such as Kubernetes and virtual machines, that enable multiple applications to run securely and efficiently on shared edge infrastructure.</li> <li><b>Edge orchestration and management systems.</b> These tools and platforms handle application deployment, workload migration, monitoring and scaling at distributed edge sites.</li> <li><b>Security services.</b> These services include encryption, authentication, access control and threat detection, protecting edge nodes and connected devices. Edge security must be able to cover distributed environments.</li> <li><b>Cloud integration layer.</b> This layer of interfaces links the edge with central cloud data centers for coordination, backup and large-scale analytics.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Benefits of 5G in edge computing"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Benefits of 5G in edge computing</h2> <p>When 5G networks are paired with edge computing, applications can operate with faster responsiveness, higher reliability and greater efficiency than with traditional cloud models. The 5G-edge combination also supports real-time decision-making, enables more immersive experiences and provides the infrastructure for industries such as healthcare, transportation and manufacturing to innovate at scale.</p> <p>Among the benefits of 5G edge computing are the following:</p> <ul class="default-list"> <li><b>Lower latency. </b>Because processing happens near the device rather than in faraway cloud servers, response times are drastically shortened. This makes applications like augmented reality (<a href="https://www.techtarget.com/whatis/definition/augmented-reality-AR">AR</a>), virtual reality (VR), remote surgery and autonomous vehicles feasible, since even milliseconds of delay can make the difference between success and failure.</li> <li><b>Bandwidth efficiency. </b>Not all raw data needs to travel across the entire network. Edge computing enables filtering, compression and preliminary analysis to occur locally, which reduces network congestion and cuts transmission costs.</li> <li><b>Reliability and resilience. </b>Edge nodes can continue operating even when connections to central clouds are weak or disrupted. This local independence helps ensure that critical applications, such as factory automation and emergency services, remain available.</li> <li><b>Enabling new applications.</b> By supporting real-time analytics and interaction, 5G edge computing makes it possible to deploy advanced use cases such as smart cities, connected healthcare, immersive gaming and industrial IoT.</li> <li><b>Data privacy and security. </b>Processing sensitive information at or near its source helps organizations comply with data sovereignty laws and reduces the risk of exposure during long-distance transfers.</li> </ul> <p>"From the context of the cyber side, I can now have a resilient network using 5G and AI," said Dave Krauthamer, field CTO of QuSecure, which makes a <a href="https://www.techtarget.com/searchsecurity/definition/post-quantum-cryptography">post-quantum cryptography</a> platform. "One of the elements we have is the ability to enhance the cryptographic fabric in real time based on threat patterns."</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/EmmNb0zhvxc?autoplay=0&amp;modestbranding=1&amp;rel=0&amp;widget_referrer=null&amp;enablejsapi=1&amp;origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0"></iframe> </div> </section> <section class="section main-article-chapter" data-menu-title="Applications of 5G in edge computing"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Applications of 5G in edge computing</h2> <p>Among the applications that take advantage of the responsiveness, reliability and efficiency of 5G in edge computing are the following:</p> <ul class="default-list"> <li><b>Autonomous vehicles and intelligent transport. </b>Edge nodes near roads can process sensor and camera data in real time, enabling safer navigation, collision avoidance and vehicle-to-infrastructure communication with very low latency.</li> <li><b>Smart manufacturing. </b>Factories <a target="_blank" href="https://5g-acia.org/whitepapers/industrial-5g-edge-computing-use-cases-architecture-and-deployment/" rel="noopener">use</a> 5G edge computing for robotics coordination, predictive maintenance and real-time quality control by processing data from sensors and cameras directly on-site.</li> <li><b>AR and VR. </b>Immersive applications for training, remote assistance and entertainment rely on 5G edge to minimize lag and provide smooth, real-time rendering.</li> <li><b>Healthcare and remote medicine. </b>Wearables and connected devices stream patient data to local edge nodes for instant analysis, while telemedicine and even remote surgery benefit from the ultra-low-latency connection.</li> <li><b>Smart cities and public safety. </b>Video analytics for surveillance, crowd monitoring and traffic management are conducted at the edge to deliver real-time insights for urban efficiency and safety.</li> <li><b>Retail and customer experience. </b>Edge computing enables cashier-less checkout, personalized offers in real time and AR-based shopping experiences in physical stores.</li> <li><b>Energy and utilities. </b>Smart grids and remote asset monitoring take advantage of 5G edge for real-time balancing, outage detection and predictive maintenance of energy infrastructure.</li> <li><b>Logistics and supply chain. </b>Edge-enabled tracking helps companies monitor fleets, shipments and warehouses in real time, improving efficiency and reducing losses.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Challenges of 5G edge computing"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Challenges of 5G edge computing</h2> <p>While 5G edge computing offers powerful capabilities for real-time processing and advanced applications, it also faces the following hurdles:</p> <ul class="default-list"> <li><b>High deployment costs. </b>Building out distributed edge infrastructure, such as servers, nodes and localized data centers, requires significant capital investment and ongoing maintenance.</li> <li><b>Complex infrastructure management. </b>Coordinating workloads across many small, distributed sites is far more complex than managing centralized cloud infrastructure.</li> <li><b>Interoperability issues. </b>Different vendors and standards can create compatibility problems, making it harder to ensure smooth integration of devices, applications and networks.</li> <li><b>Security and privacy risks. </b>With more distributed points of processing, the <a href="https://www.techtarget.com/whatis/definition/attack-surface">attack surface</a> expands. Ensuring consistent security across edge nodes is a significant challenge.</li> <li><b>Latency variability. </b>Although edge computing reduces latency, real-world conditions like network congestion and user mobility can still cause delays and disrupt service.</li> <li><b>Skills and expertise gaps. </b>Designing, deploying and managing 5G edge products requires expertise in telecommunications, IT and cloud-native software -- skills that are still scarce in the workforce. For this and other reasons, the powerful combination of 5G and edge computing still has a way to go before reaching its full potential in real-world applications.</li> <li><b>Uneven deployment of 5G. </b>Similar to the latency issues, the <a target="_blank" href="https://www.mdpi.com/2227-7390/13/16/2634#:~:text=However%2C%20despite%20its%20numerous%20advantages,5G%20in%20evolving%20digital%20ecosystems." rel="noopener">uneven deployment</a> of 5G in the U.S. and other parts of the world can create disincentives for developing edge applications that rely on ubiquity.</li> </ul> <p>"It feels like the handset carriers or even the networks on which these handsets run are probably being disingenuous, where you see 5G show up on your phone and there is no 5G," said Thomas Pace, co-founder and CEO of cloud security company NetRise. "On paper, the benefits are low latency, high bandwidth, better reliability -- all that stuff. Those are all the promises of 5G. I am not seeing them."</p> <p><i>Cynthia Brumfield is a writer, analyst, publisher and instructor specializing in cybersecurity. She is the author of the Wiley book, </i>Cybersecurity Risk Management: Mastering the Fundamentals Using the NIST Cybersecurity Framework<i>.</i></p> </section> 5G and edge computing need each other to reach their full potential. Learn the benefits and challenges of decentralizing compute power and data on ultra-fast wireless networks. https://cdn.ttgtmedia.com/rms/onlineimages/iot_a253400028.jpg https://www.techtarget.com/searchnetworking/feature/5G-in-edge-computing-Benefits-applications-and-challenges Thu, 30 Oct 2025 13:26:00 GMT <p>A neural network is a machine learning (<a href="https://www.techtarget.com/searchenterpriseai/definition/machine-learning-ML">ML</a>) model designed to process data in a way that mimics the function and structure of the human brain. Neural networks are intricate networks of interconnected nodes, or <a href="https://www.techtarget.com/searchcio/definition/artificial-neuron">artificial neurons</a>, that collaborate to tackle complicated problems.</p> <p>Also referred to as <i>artificial neural networks (ANNs)</i>, neural nets or deep neural networks, neural networks represent a type of <a href="https://www.techtarget.com/searchenterpriseai/definition/deep-learning-deep-neural-network">deep learning</a> technology that's classified under the broader field of <a href="https://www.techtarget.com/searchenterpriseai/definition/AI-Artificial-Intelligence">AI</a>.</p> <p>Neural networks are widely used in a variety of applications, including <a href="https://www.techtarget.com/searchenterpriseai/definition/image-recognition">image recognition</a>, predictive modeling, decision-making and natural language processing (<a href="https://www.techtarget.com/searchenterpriseai/definition/natural-language-processing-NLP">NLP</a>). Examples of significant commercial applications over the past 25 years include handwriting recognition for check processing, <a href="https://www.techtarget.com/searchenterpriseai/feature/Speech-to-text-for-deaf-users-aids-in-accessibility">speech-to-text transcription</a>, oil exploration data analysis, weather prediction and <a href="https://www.techtarget.com/searchenterpriseai/definition/facial-recognition">facial recognition</a>.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/yOf2ssqJFFk?autoplay=0&amp;modestbranding=1&amp;rel=0&amp;widget_referrer=null&amp;enablejsapi=1&amp;origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0"></iframe> </div> <section class="section main-article-chapter" data-menu-title="How do artificial neural networks work?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How do artificial neural networks work?</h2> <p>An ANN usually involves many <a href="https://www.techtarget.com/whatis/definition/processor">processors</a> operating in parallel and arranged in tiers or layers. These tiers, or layers, fall under three categories -- an input layer, a number of hidden layers, and<i> </i>an output layer. The first tier -- analogous to optic nerves in human visual processing -- receives the raw input information. Its job is to process, analyze, and categorize the incoming data and then pass it on to the next layer.</p> <p>Instead of the original raw input, each successive tier receives the output from the preceding tier, the same way neurons further from the optic nerve receive signals from those closer to it. There may be many hidden layers in an ANN and they all function in the same way -- analyze and process the output from the previous layer and then pass it on to the next layer for further analysis and processing.</p> <p>Simple neural networks have fewer hidden layers. Deep neural networks have several hidden layers and millions of interlinked neurons that may have more or less influence on the other neurons. The large number of layers and neurons allow deep ANNs to process complex problems and map any input type to any output type.</p> <p>The last tier of an ANN, intuitively named the <i>output layer</i>, produces the system's result. This layer may have one or multiple nodes, depending on the problem being addressed by the ANN. For example, <a href="https://www.techtarget.com/whatis/definition/binary">binary</a> classification problems require only one node in the output layer, while multi-class classification problems require multiple output nodes.</p> <p>Each processing node in the ANN has its own small sphere of knowledge, including what it has seen and any rules it was originally programmed with or developed for itself. The tiers are highly interconnected, which means each node in Tier <i>N</i> will be connected to many nodes in Tier <i>N-1</i> -- its inputs -- and in Tier <i>N+1</i>, which provides input data for the Tier <i>N-1</i> nodes. There could be one or more nodes in the output layer, from which the answer it produces can be read.</p> <p>Each individual node or neuron carries information, and the connections between neurons are regulated by weights and biases (also known as thresholds). Weights are assigned to every input layer and they determine how much each variable contributes to the output. A variable with a higher weight contributes more to the output compared to variables with a lower weight.</p> <p>Once the input goes through all the layers of the ANN, the output is determined. First, the inputs are multiplied by their respective weights, then they are summed. This total goes through an activation function, which determines the output. The activation function is important because it enables the neural network to learn more complex patterns over time.</p> <p>Next, the output is compared to the threshold. If the output exceeds the threshold, the node is activated, and the output becomes the input for the next layer in the ANN and is passed to it for further processing. This is known as a feedforward mechanism, meaning information flows only in one direction -- from input to output.</p> <p>Most ANNs are <a href="https://www.techtarget.com/searchenterpriseai/feature/How-neural-network-training-methods-are-modeled-after-the-human-brain">feedforward</a>, although they can also be trained to move in the opposite direction (from output to input). This mechanism, known as backpropagation, is generally used to calculate the error associated with each neuron in the ANN and accordingly adjust the model's parameters.</p> <p>ANN <a href="https://www.techtarget.com/whatis/definition/algorithm">algorithms</a> continuously adjust their weights and bias using <a href="https://www.techtarget.com/searchenterpriseai/definition/reinforcement-learning">reinforcement learning</a> and a method called <a href="https://www.techtarget.com/searchenterpriseai/definition/gradient-descent">gradient descent</a>. The algorithm's goal is to adjust its weights in order to reduce output errors. The more the algorithm is trained, the more its parameters adjust to further reduce errors (also known as minimizing the cost function).</p> <p>ANNs are noted for being <a href="https://www.techtarget.com/searchenterpriseai/tip/Explore-real-world-use-cases-for-adaptive-AI">adaptive</a>, which means they modify themselves as they learn from initial training, and subsequent runs provide more information about the world. The most basic learning model is centered on weighting the input streams, which is how each node measures the importance of input data from each of its predecessors. Inputs that contribute to getting the right answers are weighted higher.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineImages/deep_neural_network.jpg"> <img data-src="https://www.techtarget.com/rms/onlineImages/deep_neural_network_mobile.jpg" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineImages/deep_neural_network_mobile.jpg 960w,https://www.techtarget.com/rms/onlineImages/deep_neural_network.jpg 1280w" alt="A graphic illustrating how the multiple layers in a neural network connect with all the other layers leading to a result" height="342" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>Each layer in a neural network consists of small, individual neurons, interlinked to the other neurons. A number called the weight represents the connections between the nodes. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="Applications of artificial neural networks"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Applications of artificial neural networks</h2> <p>Image recognition was one of the first areas in which neural networks were successfully applied. A specific type of ANNs called convolutional neural networks (<a href="https://www.techtarget.com/searchenterpriseai/definition/convolutional-neural-network">CNNs</a>) is used for image-related tasks, such as image recognition, pattern recognition and computer vision. CNNs include multiple hidden layers that perform mathematical functions -- specifically, functions from <a href="https://aibusiness.com/ml/five-ways-to-learn-about-machine-learning-online">linear algebra</a> -- to identify patterns and extract relevant features from input images. Different layers extract different features from the input. At the output end, the CNN recognizes the image and can even classify it as a specific type.</p> <p><a href="https://www.techtarget.com/searchenterpriseai/definition/machine-vision-computer-vision">Computer vision technology</a> is another useful application of ANNs. It allows ANNs to identify, extract information from, and classify both images and videos. A deep neural network that's been trained on large volumes of relevant data can perform computer vision tasks at almost the same accuracy -- and much higher speeds -- than humans. Some of the applications of computer vision include the following:</p> <ul class="default-list"> <li>Self-driving cars can recognize road signs, obstacles and people to adjust movement (turn, stop, swerve, etc.).</li> <li>Cameras with facial recognition capabilities can identify human faces and recognize specific attributes, like facial hair, to identify specific individuals.</li> <li>Traffic cameras can detect and flag traffic violations and intelligently manage and optimize traffic flows.</li> <li><a href="https://www.techtarget.com/whatis/definition/medical-imaging">Medical imaging</a> machines can analyze imaging documents to capture useful insights that support diagnostic decision-making, identify tumors, monitor patient vital signs, and track patients' chronic conditions.</li> <li>Robots can identify defects in products on the assembly line or monitor equipment to flag potential issues (predictive maintenance) before they occur.</li> <li>Image labeling systems in retail can capture image details to help retailers pinpoint missing items and to provide precise search results to customers.</li> </ul> <p>Apart from image and video recognition, ANNs are also used for <a href="https://www.techtarget.com/searchcustomerexperience/definition/speech-recognition">speech recognition</a> and NLP.</p> <p>The most obvious example of ANNs recognizing and responding to human speech is their use in <a href="https://www.techtarget.com/searchcustomerexperience/definition/virtual-assistant-AI-assistant">virtual assistants</a>, like Apple's Siri and Amazon's Alexa. Siri and Alexa use ANNs to understand human input and, in response, perform various tasks -- play a song, send an email, show the weather, etc.</p> <p>ANNs also enable computers to understand natural human language and respond in kind. NLP powered by ANNs is used in chatbots, to analyze and summarize documents containing unstructured (e.g., text or images) data, to generate new content (e.g., for marketing), and to perform customer sentiment analysis by analyzing customer content on social media and other places.</p> <p><a href="https://www.techtarget.com/whatis/definition/recommendation-engine">Recommendation engines</a> also rely on ANNs to analyze a user's behavioral and preference history and, accordingly, provide personalized recommendations. Netflix and Amazon are two of the best examples of ANNs driving recommendation engines and enabling the brands to connect with customers in more personalized and scalable ways.</p> <p>In general, the technology <a href="https://www.techtarget.com/searchenterpriseai/ehandbook/Neural-network-applications-in-business-run-wide-fast-and-deep">uses of neural networks</a> have expanded from just image recognition to many additional areas, including the following:</p> <ul class="default-list"> <li><a href="https://www.techtarget.com/searchcustomerexperience/definition/chatbot">Chatbots</a>.</li> <li>Computer vision.</li> <li>NLP, translation and language generation.</li> <li>Speech recognition.</li> <li>Recommendation engines.</li> <li>Stock market forecasting.</li> <li>Delivery driver route planning and optimization.</li> <li>Medical diagnosis and disease recognition.</li> <li>Drug discovery and development.</li> <li><a href="https://www.techtarget.com/whatis/definition/social-media">Social media</a>.</li> <li>Personal assistants.</li> <li><a href="https://www.techtarget.com/whatis/definition/pattern-recognition">Pattern recognition</a>.</li> <li>Sequence recognition.</li> <li>Data processing.</li> <li>Data mining</li> <li>Regression analysis.</li> <li>Process and quality control.</li> <li>Targeted marketing through social network filtering and behavioral data insights.</li> <li>Generative AI.</li> <li><a href="https://www.techtarget.com/whatis/definition/quantum-theory">Quantum chemistry</a>.</li> <li><a href="https://www.techtarget.com/searchbusinessanalytics/definition/data-visualization">Data visualization</a>.</li> <li>Email spam filtering.</li> <li>Financial modeling.</li> <li><a href="https://www.techtarget.com/whatis/definition/robotics">Robotics</a>.</li> <li>Infrastructure reliability analysis.</li> <li>Black-box modeling in geoscience.</li> <li><a href="https://www.techtarget.com/searchsecurity/definition/cybersecurity">Cybersecurity</a>.</li> <li>Financial fraud detection.</li> <li>Materials science research.</li> </ul> <p>The prime uses of ANNs involve any process that operates according to strict rules or patterns and has large amounts of data. If the amount of data involved is too large for a human to make sense of in a reasonable amount of time, the process is likely a good candidate for automation through artificial neural networks.</p> </section> <section class="section main-article-chapter" data-menu-title="How do neural networks learn? How are neural networks trained?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How do neural networks learn? How are neural networks trained?</h2> <p><i>Training</i> a neural network means teaching it how to perform a certain task. Typically, an ANN is initially trained or fed large amounts of data. Training consists of providing input and telling the network what the output should be. For example, to build a network that identifies the faces of actors, the initial training might be a series of pictures, including actors, non-actors, masks, statues and animal faces. Each input is accompanied by matching identification, such as actors' names or "not actor" or "not human" information. Providing the answers enables the model to adjust its internal weighting to do its job better.</p> <p>For example, if nodes David, Dianne and Dakota tell node Ernie that the current input image is a picture of Brad Pitt, but node Durango says it's George Clooney, and the training program confirms it's Pitt, Ernie decreases the weight it assigns to Durango's input and increases the weight it gives to David, Dianne and Dakota.</p> <p>Basically, the ANN first processes a large <a href="https://www.techtarget.com/whatis/definition/data-set">data set</a> that might contain labeled or unlabeled data. This allows it to learn how to process new, previously unseen data. The more data it is trained on, the better its learning capabilities and the more accurate its output over time.</p> <p>In defining the rules and making determinations -- the decisions of each node on what to send to the next layer based on inputs from the previous tier -- neural networks use several principles. These include gradient-based training, <a href="https://www.techtarget.com/searchenterpriseai/definition/fuzzy-logic">fuzzy logic</a>, genetic algorithms and <a href="https://www.techtarget.com/searchenterpriseai/definition/What-is-Bayes-theorem">Bayesian</a> methods. They might be given some basic rules about object relationships in the data being modeled.</p> <p>For example, a facial recognition system might be instructed, "Eyebrows are found above eyes," or "Mustaches are below a nose. Mustaches are above and/or beside a mouth." Preloading rules can make training faster and the model more powerful faster. But it also includes assumptions about the nature of the problem, which could prove to be either irrelevant and unhelpful, or incorrect and counterproductive, making the decision about what, if any, rules to build unimportant.</p> <p>Further, the assumptions people make when training algorithms cause neural networks to amplify cultural biases. <a href="https://www.techtarget.com/searchenterpriseai/feature/6-ways-to-reduce-different-types-of-bias-in-machine-learning">Biased data sets are an ongoing challenge</a> in training systems that find answers on their own through pattern recognition in data. If the data feeding the algorithm isn't neutral -- and almost no data is -- the machine propagates bias.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineImages/bi_ezine-how_ai_systems_amplify_bias.png"> <img data-src="https://www.techtarget.com/rms/onlineImages/bi_ezine-how_ai_systems_amplify_bias_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineImages/bi_ezine-how_ai_systems_amplify_bias_mobile.png 960w,https://www.techtarget.com/rms/onlineImages/bi_ezine-how_ai_systems_amplify_bias.png 1280w" alt="Infographic on how AI amplifies bias" height="336" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>The problem with biased data sets exists in the training of neural systems. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <p></p> </section> <section class="section main-article-chapter" data-menu-title="Types of neural networks"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Types of neural networks</h2> <p>Neural networks are sometimes described in terms of their depth, including how many layers they have between input and output, or the model's so-called hidden layers. This is why the term neural network is used almost synonymously with deep learning. Neural networks can also be described by the number of hidden nodes the model has, or in terms of how many input layers and output layers each node has. Variations on the classic neural network design enable various forms of forward and backward propagation of information among tiers.</p> <p>Specific types of ANNs include the following:</p> <h3>Feed-forward neural networks</h3> <p>One of the simplest variants of neural networks, these pass information in one direction, through various input nodes, until it makes it to the output node. The network might or might not have hidden node layers, making their functioning more interpretable. It's prepared to process large amounts of noise. This type of ANN computational model is used in technologies such as facial recognition and computer vision.</p> <h3>Recurrent neural networks</h3> <p>More complex in nature, recurrent neural networks (<a href="https://www.techtarget.com/searchenterpriseai/definition/recurrent-neural-networks">RNNs</a>) save the output of processing nodes and feed the result back into the model. This is how the model learns to predict the outcome of a layer. Each node in the RNN model acts as a memory cell, continuing the computation and execution of operations.</p> <p>This neural network starts with the same front propagation as a feed-forward network, but then goes on to remember all processed information to reuse it in the future. If the network's prediction is incorrect, then the system self-learns and continues working toward the correct prediction during <a href="https://www.techtarget.com/searchenterpriseai/definition/backpropagation-algorithm">backpropagation</a>. This type of ANN is frequently used in text-to-speech conversions.</p> <h3>Convolutional neural networks</h3> <p>Convolutional neural networks (CNNs) are one of the most popular models used today. This computational model uses a variation of multilayer <a href="https://www.techtarget.com/whatis/definition/perceptron">perceptrons</a> and contains one or more convolutional layers that can be either entirely connected or pooled. These convolutional layers create feature maps that record a region of the image that's ultimately broken into rectangles and sent out for nonlinear processing.</p> <p>The CNN model is particularly popular in the realm of image recognition. It has been used in many of the most advanced applications of AI, including facial recognition, text digitization and NLP. Other use cases include paraphrase detection, signal processing and image classification.</p> <h3>Deconvolutional neural networks</h3> <p><a href="https://www.techtarget.com/searchenterpriseai/definition/deconvolutional-networks-deconvolutional-neural-networks">Deconvolutional neural networks</a> use a reversed CNN learning process. They try to find lost features or signals that might have originally been considered unimportant to the CNN system's task. This network model can be used in image synthesis and analysis.</p> <h3>Modular neural networks</h3> <p>These contain multiple neural networks working separately from one another. The networks don't communicate or interfere with each other's activities during the computation process. Consequently, complex or big computational processes can be performed more efficiently.</p> <h3>Perceptron neural networks</h3> <p>These represent the most basic form of neural networks and were introduced in 1958 by Frank Rosenblatt, an American psychologist, who is also considered the father of deep learning. In fact, the perceptron is the oldest neural network.</p> <p>Rosenblatt published his research about perceptrons in the 1958 paper "<a target="_blank" href="https://www.academia.edu/60542953/The_perceptron_a_probabilistic_model_for_information_storage_and_organization_in_the_brain" rel="noopener">The Perceptron: a probabilistic model for information storage and organization in the brain</a>." In the paper, he explained how he got the IBM 704 computer to learn how to distinguish between two sets of cards. Rosenblatt concluded the paper by suggesting that the study of perceptrons might lead to a better understanding of "those fundamental laws of organization which are common to all information handling systems."</p> <p>A single-layer perceptron can only perform simple, linear computational tasks since it only has one layer of neurons between the input and output layers. This makes it unsuitable for more complex tasks.</p> <p>The perceptron takes in the input, weighs it and then sums up the weights and finally produces the output. As with other ANNs, the weights and thresholds of the neurons in a perceptron are adjustable.</p> <p>The perceptron is specifically designed for binary classification tasks, enabling it to differentiate between two classes based on input data. Simple single-layer perceptrons can be built using <a href="https://www.techtarget.com/whatis/definition/open-source">open source</a> machine learning frameworks like TensorFlow<b>.</b></p> <p>Neural networks are not the same as machine learning. In fact, ANNs are a subset of the broader field of machine learning.</p> <h3>Multilayer perceptron networks</h3> <p>Multilayer perceptron (MLP) networks, also known as feedforward neural networks, consist of multiple layers of neurons, including an input layer, one or more hidden layers, and an output layer. Each layer is fully connected to the next, meaning that every neuron in one layer is connected to every neuron in the subsequent layer. Every layer transforms the received input and passes it on to the next layer until the final output is generated at the output layer. This highly interconnected neuronal architecture enables MLPs to learn complex patterns and relationships in data, making them suitable for various classification and <a href="https://www.techtarget.com/searchenterpriseai/feature/What-is-regression-in-machine-learning">regression tasks</a>. MLPs can also be trained to work on <a href="https://www.techtarget.com/searchdatacenter/definition/parallel-processing">parallel computing</a> tasks.</p> <p>Despite the use of the word "perceptron" in the name multilayer perceptron network, MLPs are not comprised of perceptrons but of sigmoid neurons. Also, it uses non-linear activation functions. It is these features that allow MLPs to work on complex, non-linear real-world problems, including computer vision and NLP.</p> <p>One drawback of MLPs is that they are computationally expensive. Since they comprise many layers, training MLPs is a slow process. Also, MLPs are prone to overfitting, which can lead to sub-optimal generalization of new, unseen data.</p> <h3>Radial basis function neural networks</h3> <p>Radial basis function (RBF) neural networks are a type of feed-forward neural networks that use a three-layer architecture. They also have universal approximation capabilities and use radial basis functions, such as <a href="https://www.techtarget.com/whatis/feature/Model-collapse-explained-How-synthetic-training-data-breaks-AI">Gaussian</a> functions, as activation functions. RBFs are typically used for non-linear function approximation and <a href="https://www.techtarget.com/searchenterpriseai/news/365532836/How-a-time-series-forecasting-vendor-uses-Lightning-PyTorch">time series prediction</a> tasks, as well as in control systems. They can learn quickly and offer efficient performance for non-linear system identification, classification and regression problems. Also, the simple architecture makes it easy to understand and implement RBF neural networks -- despite the fact that they require three-stage training.</p> <h3>Transformer neural networks</h3> <p>As one of the more cutting-edge types of neural networks, <a href="https://www.techtarget.com/searchenterpriseai/feature/Transformer-neural-networks-are-shaking-up-AI">transformer neural networks are reshaping NLP</a> and other fields through a range of advancements. Introduced by researchers from Google and the University of Toronto in a <a target="_blank" href="https://arxiv.org/pdf/1706.03762" rel="noopener">2017 paper</a>, transformers are specifically designed to process sequential data, such as text, by effectively capturing relationships and dependencies between elements in the sequence, regardless of their distance from one another.</p> <p>One of the Google researchers also published a follow-up article in which he stated that the transformer is "a novel neural network architecture based on a self-attention mechanism that we believe to be particularly well suited for language understanding." They also explained how they enabled a transformer to outperform both CNNs and RNNs on academic English to German and English to French translation benchmarks.</p> <p>Transformer neural networks have gained popularity as an alternative to CNNs and RNNs because their "attention mechanism" enables them to capture and process multiple elements in a sequence simultaneously, which is a distinct advantage over other neural network architectures. It is this mechanism that makes transformers highly suitable for complex NLP tasks, such as <a href="https://www.smartcitiesdive.com/news/american-city-county-and-smart-cities-dive-are-combining/754194/">text translations</a>.</p> <h3>Generative adversarial networks</h3> <p><a href="https://www.techtarget.com/searchenterpriseai/definition/generative-adversarial-network-GAN">Generative adversarial networks</a> consist of two neural networks -- a generator and a discriminator -- that compete against each other. The generator creates fake data, while the discriminator evaluates its authenticity. These types of neural networks are widely used for generating realistic images and data augmentation processes.</p> </section> <section class="section main-article-chapter" data-menu-title="Advantages of artificial neural networks"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Advantages of artificial neural networks</h2> <p>Artificial neural networks offer the following benefits:</p> <ul class="default-list"> <li><b>Parallel processing.</b> ANNs' parallel processing abilities mean the network can perform more than one job at a time.</li> <li><b>Feature extraction.</b> Neural networks can automatically learn and extract relevant features from raw data, which simplifies the modeling process. However, traditional ML methods differ from neural networks in the sense that they often require manual feature engineering.</li> <li><b>Information storage.</b> ANNs store information on the entire network, not just in a database. This ensures that even if a small amount of data disappears from one location, the entire network continues to operate.</li> <li><b>Nonlinearity.</b> The ability to learn and model nonlinear, complex relationships helps model the real-world relationships between input and output.</li> <li><b>Fault tolerance.</b> ANNs come with <a href="https://www.techtarget.com/searchdisasterrecovery/definition/fault-tolerant">fault tolerance</a>, which means the corruption or fault of one or more cells of the ANN won't stop the generation of output.</li> <li><b>Gradual corruption.</b> This means the network slowly degrades over time instead of degrading instantly when a problem occurs.</li> <li><b>Unrestricted input variables.</b> No restrictions are placed on the input variables, such as how they should be distributed.</li> <li><b>Observation-based decisions.</b> ML means the ANN can learn from events and make decisions based on the observations.</li> <li><b>Unorganized data processing.</b> ANNs are exceptionally good at organizing large amounts of data by processing, sorting and categorizing it.</li> <li><b>Ability to learn hidden relationships.</b> ANNs can learn the hidden relationships in data without commanding any fixed relationship. This means ANNs can better model highly volatile data and nonconstant variance.</li> <li><b>Ability to generalize data.</b> The ability to generalize and infer unseen relationships on unseen data means ANNs can predict the output of unseen data.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Disadvantages of artificial neural networks"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Disadvantages of artificial neural networks</h2> <p>Their numerous benefits notwithstanding, it's important to note that neural networks also have some drawbacks, including the following:</p> <ul class="default-list"> <li><b>Lack of rules.</b> The lack of rules for determining the proper network structure means the appropriate ANN architecture can only be found through trial, error and experience.</li> <li><b>Computationally expensive.</b> Neural networks such as ANNs use many computational resources. Therefore, training neural networks can be expensive and time-consuming, requiring significant processing power and memory. This can be a barrier for organizations with limited resources or those needing real-time processing.</li> <li><b>Hardware dependency.</b> The requirement of processors with parallel processing abilities makes neural networks dependent on hardware.</li> <li><b>Numerical translation.</b> The network works with numerical information, meaning all problems must be translated into numerical values before they can be presented to the ANN.</li> <li><b>Lack of trust.</b> The lack of explanation behind probing solutions is one of the biggest disadvantages of ANNs. The inability to explain the <i>why</i> or <i>how</i> behind the solution generates a lack of trust in the network.</li> <li><b>Inaccurate results.</b> If not trained properly, ANNs can produce incomplete or inaccurate results.</li> <li><b>Black box nature.</b> Because of their <a href="https://www.techtarget.com/whatis/definition/black-box-AI">black box AI</a> model, it can be challenging to grasp how neural networks make their predictions or categorize data.</li> <li><b>Overfitting.</b> Neural networks are susceptible to <a href="https://www.techtarget.com/whatis/definition/overfitting-in-machine-learning">overfitting</a>, particularly when trained on small data sets. They can end up learning the noise -- focusing on non-relevant factors such as the typeface in a document -- in the training data instead of the underlying patterns, which can result in poor performance on new and unseen data.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="History and timeline of neural networks"> <h2 class="section-title"><i class="icon" data-icon="1"></i>History and timeline of neural networks</h2> <p>The <a href="https://www.techtarget.com/searchenterpriseai/tip/History-of-generative-AI-innovations-spans-9-decades">history of neural networks</a> spans several decades and has seen considerable advancements. The following examines the important milestones and developments in the history of neural networks:</p> <ul class="default-list"> <li><b>1940s.</b> In 1943, mathematicians Warren McCulloch and Walter Pitts built a circuitry system that ran simple algorithms and was intended to approximate the functioning of the human brain.</li> <li><b>1950s.</b> In 1958, Rosenblatt created the perceptron, a form of artificial neural network capable of learning and making judgments by modifying its weights. The perceptron featured a single layer of computing units and could handle problems that were linearly separate.</li> <li><b>1970s.</b> Paul Werbos, an American scientist, developed the backpropagation method, which facilitated the training of multilayer neural networks. It made deep learning possible by enabling weights to be adjusted across the network based on the error calculated at the output layer.</li> <li><b>1980s.</b> Cognitive psychologist and computer scientist Geoffrey Hinton, computer scientist Yann LeCun and a group of fellow researchers began investigating the concept of connectionism, which emphasizes the idea that cognitive processes emerge through interconnected networks of simple processing units. This period paved the way for modern neural networks and deep learning models.</li> <li><b>1990s.</b> Jürgen Schmidhuber and Sepp Hochreiter, both computer scientists from Germany, proposed the long short-term memory recurrent neural network framework in 1997.</li> <li><b>2000s.</b> Hinton and his colleagues at the University of Toronto pioneered restricted Boltzmann machines, a sort of generative artificial neural network that enables <a href="https://www.techtarget.com/searchenterpriseai/definition/unsupervised-learning">unsupervised learning</a>. RBMs opened the path for deep belief networks and deep learning algorithms.</li> <li><b>2010s.</b> Research in neural networks picked up great speed around 2010. The <a href="https://www.techtarget.com/searchdatamanagement/definition/big-data">big data</a> trend, where companies amassed vast troves of data, and parallel computing gave <a href="https://www.techtarget.com/searchenterpriseai/definition/data-scientist">data scientists</a> the training data and computing resources needed to run complex ANNs. In 2011, Google's speech recognition team discovered that deep learning is a powerful approach for speech recognition. This discovery led to large-scale modifications in Google's Android operating system. In the same year, a collaboration between machine learning researcher Andrew Ng and Googler Jeff Dean led to the development of a massively large unsupervised neural network that offered unprecedented performance on computer vision tasks. In 2012, a neural network named AlexNet won the ImageNet Large Scale Visual Recognition Challenge, an image classification competition. Around this time, researchers at Caltech and elsewhere discovered that graphics processing units (<a href="https://www.techtarget.com/searchvirtualdesktop/definition/GPU-graphics-processing-unit">GPUs</a>) could be used to handle the huge computational demands of large/complex neural networks.</li> <li><b>2020s and beyond.</b> Neural networks continue to undergo rapid development, with advancements in architecture, training methods and applications. Researchers are exploring new network structures such as transformers and <a href="https://www.techtarget.com/searchenterpriseai/definition/graph-neural-networks-GNNs">graph neural networks</a>, which excel in NLP and understanding complex relationships. Similarly, Kolmogorov-Arnold Networks (KANs) are being studied for applications involving non-linear and interdependent variable relationships, such as weather modeling and fluid dynamics. Additionally, techniques such as transfer learning and self-supervised learning are enabling neural networks and deep learning models to learn from smaller data sets and generalize better. These developments are driving progress in fields such as healthcare, autonomous vehicles, facial recognition, language translations, and wearables.</li> </ul> <p><i>Discover the process for building a machine learning model, including data collection, preparation, training, evaluation and iteration. Follow these </i><a href="https://www.techtarget.com/searchenterpriseai/feature/How-to-build-a-machine-learning-model-in-7-steps"><i>essential steps to kick-start your ML project</i></a><i>.</i></p> </section> A neural network is a machine learning (ML) model designed to process data in a way that mimics the function and structure of the human brain. https://cdn.ttgtmedia.com/visuals/digdeeper/4.jpg https://www.techtarget.com/searchenterpriseai/definition/neural-network Mon, 27 Oct 2025 12:00:00 GMT <p>Modern distributed computing architectures support significant technological advances, such as AI and smart manufacturing. Each computing model is key to supporting advanced applications that transform the landscape.</p> <p>Digital enterprises have sprawling virtual environments that demand a flexible and resilient infrastructure capable of keeping up with ever-increasing processing and storage requirements. Estimates predict connected devices will top 40 billion globally in the next five years. With a massive spending increase on AI application development, cloud providers are <a href="https://www.constructiondive.com/news/OpenAI-Oracle-Stargate-data-center-AI-infrastructure-capacity-push/753823/">investing hundreds of billions of dollars in data center expansion</a>.</p> <p>Advanced digital applications require a flexible, efficient and reliable infrastructure. The underlying processing and storage models that facilitate this are cloud computing, edge computing and fog computing. Each has an important role in the infrastructure. Though often placed in opposition to each other, the models can be complementary.</p> <section class="section main-article-chapter" data-menu-title="Cloud vs. edge vs. fog computing"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Cloud vs. edge vs. fog computing</h2> <p>All digital models have their origins in <a href="https://www.techtarget.com/searchdatacenter/definition/grid-computing">grid computing</a>, a concept developed in the 1990s. Grid computing builds on the idea of aggregating computing resources for processing-intensive requirements in applications such as scientific research, game design and financial risk management. The digital computing models common in networking include the following:</p> <ul class="default-list"> <li><b>Cloud computing.</b> Provides centralized resources with high scalability and processing power, ideal for long-term analysis and storage.</li> <li><b>Edge computing.</b> Processes data directly at or near the source, useful for real-time applications with low latency requirements.</li> <li><b>Fog computing.</b> Serves as an intermediary layer, analyzing data importance before transmitting to the cloud and providing distributed processing across the network.</li> </ul> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/cloud_vs_edge_vs_fog_computing-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/cloud_vs_edge_vs_fog_computing-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/cloud_vs_edge_vs_fog_computing-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/cloud_vs_edge_vs_fog_computing-f.png 1280w" alt="Comparison chart showing the major differences between cloud computing, edge computing and fog computing, such as processing power, security, use cases and data handling" height="482" width="560"> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <h3>Cloud computing</h3> <p>Cloud computing supports a wide range of services, including IaaS and SaaS. This enables cloud computing to provide compute and storage services as needed on a <a href="https://www.techtarget.com/searchcloudcomputing/tip/Cloud-licensing-explained-What-businesses-need-to-know">pay-per-use or subscription model</a>, eliminating the need for clients to invest in capital equipment upfront.</p> <p>Cloud computing <a href="https://www.techtarget.com/whatis/feature/The-history-of-cloud-computing-explained">emerged in the mid-2000s</a> when online retailer Amazon launched the IaaS market with its Elastic Compute Cloud (<a href="https://www.techtarget.com/searchaws/definition/Amazon-Elastic-Compute-Cloud-Amazon-EC2">EC2</a>) service on demand. EC2 used excess capacity from its online commerce operations to deliver low-cost, high-volume virtualized compute services. Amazon did the same with storage through its <a href="https://www.techtarget.com/searchaws/definition/Amazon-Simple-Storage-Service-Amazon-S3">Simple Storage Service</a> offerings.</p> <p>The benefits are clear; organizations can quickly increase processing and storage capacity. Cloud computing uses a consolidated computing model, which enables clients to access resources from a centralized environment. Cloud services can be private or multi-tenant, with clients sharing hardware resources.</p> <p>Cloud computing security uses comprehensive measures such as encryption, access controls and continuous monitoring to protect data and applications stored in remote data centers. This enables businesses to use cloud services without compromising sensitive information.</p> <h3>Edge computing</h3> <p>Computing is increasingly distributed and requires more effective delivery of processing power for latency-sensitive applications. Edge computing plays a key role in accelerating application performance and improving efficiency.</p> <p>Edge computing is where processing and storage occur close to the data creation and consumption point. Its hardware -- including edge servers and <a href="https://www.techtarget.com/searchdatacenter/definition/What-is-hyper-converged-infrastructure-Guide-to-HCI">hyperconverged infrastructure</a> appliances -- runs in secondary or tertiary data centers. Cloud providers often partner with third-party vendors or telecom operators to extend their services to the edge for localized processing.</p> <p>Use cases for edge computing include applications that require real-time processing, such as autonomous vehicles, <a href="https://www.techtarget.com/searcherp/feature/AR-vs-VR-vs-MR-Differences-similarities-and-manufacturing-uses">augmented and virtual reality</a>, and smart cities.</p> <p>Edge computing security features include encryption, authentication and physical safeguards to prevent unauthorized access while keeping sensitive information closer to its source rather than sending it to cloud servers.</p> <h3>Fog computing</h3> <p>Fog computing is essentially an extension of edge computing. It's a more distributed model that involves multiple levels of processing and storage. While fog computing provides the network infrastructure with computational processing between edge devices and cloud computing facilities, it isn't limited to the edge or the cloud. It supports use cases such as complex analytics and other data processing at decentralized points across the network.</p> <p>Fog computing security creates multiple layers of protection across distributed processing nodes between edge devices and the cloud. It combines local authentication, encrypted data transmission and centralized monitoring to protect information as it travels through different levels of network infrastructure.</p> </section> <section class="section main-article-chapter" data-menu-title="How these models align for advanced applications"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How these models align for advanced applications</h2> <p>Rather than assuming fog, edge and cloud computing are adversarial models, it's helpful to consider how they can work together. Each model has a unique role in supporting application use cases, which can be complementary in certain environments. Take the following example.</p> <p>Cloud computing environments are often multi-tenant. While this keeps costs low, it also introduces questions around security and regulatory compliance. Due to the distance between data creation and consumption points, <a href="https://www.techtarget.com/searchcloudcomputing/tip/Explore-the-pros-and-cons-of-cloud-computing">cloud computing isn't optimized</a> to support applications with low-latency requirements. Enter edge computing.</p> <p>Edge computing is a natural extension of cloud computing. It applies cloud services close to the data creation and consumption points to support real-time analytics. The nature of edge computing deployments aligns well with localized data residency requirements, therefore addressing security and privacy concerns.</p> <p>However, data isn't always processed at the point of creation. Fog computing is useful in more intricate use cases where data processing takes place at different network junctures. It's important in large-scale applications that apply analysis across locations and devices, such as large-scale IoT implementations.</p> <p><i>Amy Larsen DeCarlo has covered the IT industry for more than 30 years, as a journalist, editor and analyst. As a principal analyst at GlobalData, she covers managed security and cloud services.</i></p> </section> Cloud, edge and fog computing all support modern applications. Cloud computing offers centralized resources, edge enables real-time processing and fog connects them hierarchically. https://cdn.ttgtmedia.com/rms/onlineimages/maze_g676210320.jpg https://www.techtarget.com/searchnetworking/answer/Fog-computing-vs-edge-computing-Whats-the-difference Mon, 25 Aug 2025 00:00:00 GMT <p>AI technologies are quickly maturing as a viable means of enabling and supporting essential business functions. However, creating business value from <a href="https://www.techtarget.com/searchenterpriseai/definition/AI-Artificial-Intelligence">artificial intelligence</a> requires a thoughtful approach that balances people, processes and technology.</p> <p>AI takes many forms: <a href="https://www.techtarget.com/searchenterpriseai/tip/AI-vs-machine-learning-vs-deep-learning-Key-differences">machine learning, deep learning</a>, predictive analytics, natural language processing, computer vision and automation. Companies must <a href="https://www.techtarget.com/whatis/podcast/Steps-to-build-a-successful-AI-strategy-for-your-business">start with a solid foundation</a> and a realistic view to determine the competitive advantages an AI implementation can bring to their business strategy and planning.</p> <p>"Artificial intelligence encompasses many things," according to John Carey, managing director at business management consultancy AArete. "And there's a lot of hyperbole and, in some cases, exaggeration about how intelligent [AI] really is."</p> <p>This article outlines the benefits and drawbacks businesses might experience when adding AI to their environments, discusses the prerequisites needed to <a href="https://www.techtarget.com/searchenterpriseai/tip/Integrate-and-modernize-legacy-systems-with-AI">integrate AI</a> in a business setting and provides the incremental steps to follow for a successful implementation.</p> <section class="section main-article-chapter" data-menu-title="AI implementation prerequisites"> <h2 class="section-title"><i class="icon" data-icon="1"></i>AI implementation prerequisites</h2> <p>The successful implementation of AI in a business setting can be challenging. But a detailed understanding of the following factors and conditions before execution can considerably enhance the result:</p> <ul class="default-list"> <li><b>Data labeling.</b> <a href="https://www.techtarget.com/whatis/definition/data-labeling">Labeling data</a> is a crucial step in the preprocessing pipeline for machine learning and model training. It entails organizing the data in a way that gives it context and significance. Businesses should assess whether they have a data-driven culture within their operations and evaluate whether they have access to enough data to support the deployment of AI/machine learning efforts.</li> <li><b>Strong data pipeline.</b> Organizations should strive to <a href="https://www.techtarget.com/searchdatamanagement/feature/Best-practices-and-pitfalls-of-the-data-pipeline-process">build a solid data pipeline</a> to ensure data from all various sources is combined for rapid data analysis and business insights. A strong data pipeline also offers reliable data quality.</li> <li><b>Data quality.</b> Before training an AI model, organizations should evaluate and enhance their data quality, as it affects the accuracy and efficacy of the trained model. Evaluating and enhancing data quality involves <a href="https://www.techtarget.com/searchenterpriseai/tip/Clean-data-is-the-foundation-of-machine-learning">cleaning and preprocessing data</a> to remove errors and inconsistencies, as well as ensuring that it's unbiased and accurately reflects real-world scenarios. For example, when predicting <a href="https://www.techtarget.com/searchcustomerexperience/definition/customer-churn-customer-attrition">customer churn</a>, the data must represent a range of customer behaviors. Insufficient data might require businesses to generate <a href="https://www.techtarget.com/searchcio/definition/synthetic-data">synthetic data</a>, which could lead to less accurate results.</li> <li><b>The right AI model.</b> The success of any AI implementation can be seriously hampered by the <a href="https://www.techtarget.com/searchenterpriseai/tip/4-main-types-of-AI-explained">choice of AI model a business uses</a>. A large data set combined with an inadequate AI model could produce a large amount of training data that the model is incapable of processing efficiently. This can lead to issues such as <a href="https://www.techtarget.com/whatis/definition/overfitting-in-machine-learning">overfitting</a> or underfitting. Therefore, selecting the right AI model is imperative before implementing an AI strategy.</li> <li><b>AI integration into existing systems.</b> Organizations often struggle to incorporate AI into their current infrastructure, especially with legacy systems. APIs can help overcome this struggle, as they enable new AI tools to access existing data without overhauling the entire system. <a href="https://www.techtarget.com/searchapparchitecture/definition/middleware">Middleware</a> further helps with AI integration by acting as an intermediary that facilitates communication and data exchange between legacy systems and modern AI applications. <a href="https://www.techtarget.com/searchcio/tip/Digital-transformation-tips-and-best-practices">Embracing digital transformation</a>, such as upgrading legacy systems to cloud-based architectures, can also help achieve effective AI integration.</li> <li><b>AI implementation roadmap.</b> Before starting an AI implementation, outline its market launch and how its success will be measured. The roadmap should detail the execution steps, the support required at each stage and the <a href="https://www.techtarget.com/searchbusinessanalytics/definition/key-performance-indicators-KPIs">KPIs</a> to assess success.</li> </ul> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/ess-ai_nirvana-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/ess-ai_nirvana-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/ess-ai_nirvana-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/ess-ai_nirvana-f.png 1280w" alt="List of 13 steps involved in successful business AI implementation." height="374" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>These 13 steps can help organizations achieve AI implementation. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="13 steps to AI implementation"> <h2 class="section-title"><i class="icon" data-icon="1"></i>13 steps to AI implementation</h2> <p><a href="https://www.techtarget.com/searchenterpriseai/feature/5-AI-risks-businesses-must-confront-and-how-to-address-them">Early implementation of AI</a> isn't necessarily a perfect science and might need to be experimental at first -- beginning with a hypothesis, followed by testing and measuring results. Early ideas will likely be flawed, so an incremental approach to deploying AI is likely to produce better results than a big-bang approach.</p> <p>The following 13 steps can help organizations ensure a successful AI implementation in the enterprise.</p> <h3>1. Build data fluency and understanding</h3> <p>Practical conversations about AI require a basic understanding of how data powers the entire process. "Data fluency is a real and challenging barrier -- more than tools or technology combined," said Penny Wand, executive coach at LAH Insight LLC. "Executive understanding and support will be required to understand this maturation process and drive sustained change."</p> <h3>2. Define your primary business drivers for AI</h3> <p>"To successfully implement AI, it's critical to learn what others are doing inside and outside your industry to spark interest and inspire action," Wand explained. When devising an AI implementation, <a href="https://www.techtarget.com/searchenterpriseai/tip/9-top-applications-of-artificial-intelligence-in-business">identify top use cases</a> and assess their value and feasibility.</p> <p>In addition, consider who should champion the project, identify external data sources, determine how to monetize data externally and create a backlog to ensure project momentum is maintained.</p> <h3>3. Identify areas of opportunity</h3> <p>Focus on business areas with high variability and significant payoff, said Suketu Gandhi, a partner and chair of strategic operations at digital transformation consultancy Kearney. Teams comprising business stakeholders who have technology and data expertise should use metrics to <a href="https://www.techtarget.com/searchenterpriseai/tip/How-businesses-can-measure-AI-success-with-KPIs">measure the effect of an AI implementation</a> on the organization and its people.</p> <h3>4. Evaluate your internal capabilities</h3> <p>Once use cases are identified and prioritized, business teams need to map out how these applications align with their company's existing technology and human resources. Education and training can help bridge the technical skills gap internally, while corporate partners can facilitate on-the-job training.</p> <p>Meanwhile, outside expertise could accelerate promising AI applications.</p> <h3>5. Provide employee training and support</h3> <p>Organizations should invest in <a href="https://www.techtarget.com/searchcio/definition/change-management-strategy">change management strategies</a> to address employee concerns and resistance to AI adoption. This involves engaging employees early in the process and offering them ongoing support and training during the transition.</p> <p>Providing comprehensive <a href="https://www.techtarget.com/whatis/feature/10-top-artificial-intelligence-certifications-and-courses">training on AI concepts</a>, AI-powered tools and their specific applications will help employees understand the technology, appreciate its benefits and alleviate any apprehensions they might have. Additionally, executives and team leaders should actively participate in AI initiatives, demonstrating their commitment and encouraging employees to engage with the technology.</p> <h3>6. Select the vendors and partners</h3> <p>Vendor and partner selection for AI implementation is a crucial step for organizations. When selecting vendors, companies should explore those with relevant industry expertise and a proven track record in similar AI projects. This ensures they can deliver measurable results.</p> <p>It's also important to assess the technical capabilities of potential vendors to ensure their <a target="_blank" href="https://www.morganlewis.com/blogs/sourcingatmorganlewis/2024/01/key-considerations-when-evaluating-an-ai-vendor" rel="noopener">methods</a> are compatible with existing systems and will scale well in the future. Vendors interested in long-term partnerships should be considered, as they are most likely invested in mutual success.</p> <p>Due diligence should be conducted when selecting vendor candidates by checking references and evaluating their financial stability. Once an AI vendor is selected, the company should present clear service-level agreements during the negotiation process to avoid misunderstandings and maintain accountability throughout the partnership.</p> <h3>7. Identify suitable candidates</h3> <p>It's important to narrow a broad opportunity to a practical AI deployment -- for example, invoice matching, IoT-based facial recognition, predictive maintenance on legacy systems or customer buying habits. "Be experimental," Carey said, "and include as many people [in the process] as you can."</p> <h3>8. Pilot an AI project</h3> <p>To turn a candidate for AI implementation into an actual project, Gandhi believes a <a href="https://www.techtarget.com/searchbusinessanalytics/feature/How-to-structure-and-manage-a-data-science-team">team of AI, data and business process experts</a> is needed to gather data, <a href="https://www.techtarget.com/searchenterpriseai/tip/Types-of-AI-algorithms-and-how-they-work">develop AI algorithms</a>, deploy scientifically controlled releases and measure influence and risk.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/ess-ai_deployment-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/ess-ai_deployment-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/ess-ai_deployment-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/ess-ai_deployment-f.png 1280w" alt="AI deployment quotes from industry leaders." height="301" width="559"> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <h3>9. Establish a baseline understanding</h3> <p>The successes and failures of early AI projects can help increase understanding across the entire company. "Ensure you keep the humans in the loop to build trust and engage your business and process experts with your data scientists," Wand said.</p> <p>Recognize that the path to AI starts with understanding the data and good old-fashioned rearview mirror reporting to establish a baseline of understanding. Once a baseline is established, it's easier to see how the actual AI deployment proves or disproves the initial hypothesis.</p> <h3>10. Measure the ROI</h3> <p>To evaluate the effectiveness of AI implementations, organizations must <a href="https://www.techtarget.com/searchenterpriseai/tip/How-to-measure-the-ROI-of-enterprise-AI-initiatives">measure the AI initiative's ROI</a>. To achieve this, they must first set clear KPIs that align with their business objectives. Cost savings, revenue growth, customer satisfaction and operational efficiency are important metrics to monitor, as is user engagement, which can also be a sign of successful integration.</p> <p>Qualitative metrics, such as enhanced product quality and innovation, should also be considered.</p> <h3>11. Scale incrementally</h3> <p>The overall process of creating momentum for an AI deployment begins with achieving small victories, Carey reasoned. Incremental wins can build confidence across the organization and inspire more stakeholders to pursue similar AI implementation experiments from a stronger, more established baseline. "Adjust algorithms and business processes for scaled release," Gandhi suggested. "Embed [them] into normal business and technical operations."</p> <h3>12. Guide overall AI capabilities to maturity</h3> <p>As AI projects scale, business teams need to improve the overall lifecycle of AI development, testing and deployment. To ensure sustained success, Wand offers three core practices for maturing overall project capabilities:</p> <ul class="default-list"> <li>Build a modern data platform that streamlines how to collect, store and structure data for reporting and analytical insights based on data source value and desired KPIs for businesses.</li> <li>Develop an organizational design that establishes business priorities and supports agile development of <a href="https://www.techtarget.com/searchdatamanagement/definition/data-governance">data governance</a> and modern data platforms to drive business goals and decision-making.</li> <li>Create and build the overall management, ownership, processes and technology necessary to manage critical data elements focused on customers, suppliers and members.</li> </ul> <h3>13. Continuously improve AI models and processes</h3> <p>Once the overall system is in place, business teams need to identify opportunities for continuous <a href="https://www.techtarget.com/searchenterpriseai/tip/How-to-formulate-a-winning-AI-strategy">improvement in AI models and processes</a>. AI models can degrade over time or in response to rapid changes caused by disruptions.</p> <p>Teams also need to monitor feedback and resistance to an AI deployment from employees, customers and partners.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/LUNuqJGkVoM?autoplay=0&amp;modestbranding=1&amp;rel=0&amp;widget_referrer=null&amp;enablejsapi=1&amp;origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0"></iframe> </div> </section> <section class="section main-article-chapter" data-menu-title="What advantages can businesses gain from adopting AI?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What advantages can businesses gain from adopting AI?</h2> <p>Recent cutting-edge developments in generative AI, such as <a href="https://www.techtarget.com/whatis/definition/ChatGPT">ChatGPT</a> and <a href="https://www.techtarget.com/searchenterpriseai/definition/Dall-E">Dall-E</a> image generation tools, have demonstrated the significant effect of AI systems on the corporate world. A March 2025 McKinsey Global Survey revealed a dramatic surge in global AI adoption -- from approximately 55% in 2023 to 78% in 2025.</p> <p>Some of the many <a href="https://www.techtarget.com/searchenterpriseai/feature/6-key-benefits-of-AI-for-business">benefits that businesses can gain by adopting AI</a> include the following:</p> <ul class="default-list"> <li>Improved accuracy and efficiency in decision-making processes.</li> <li>Increased automation and productivity in business operations.</li> <li>Enhanced customer experience through personalized recommendations and interactions with chatbots and intelligent agents.</li> <li>Enhanced data analysis and insights to inform business strategies.</li> <li>Improved risk management and fraud detection.</li> <li>Cost savings due to process automation and optimization.</li> <li>Enhanced competitiveness and differentiation in the marketplace.</li> <li>Advanced innovation and the ability to create new products and services.</li> <li>Scalability and efficient management of large amounts of data.</li> <li>An opportunity to venture into new markets with unique AI options.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Common AI implementation mistakes"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Common AI implementation mistakes</h2> <p>Businesses that neglect to take the recommended steps when deploying AI risk committing the following mistakes:</p> <ul class="default-list"> <li>Adopting too many tools simultaneously.</li> <li>Having unclear business objectives.</li> <li>Ignoring <a href="https://www.techtarget.com/searchdatabackup/feature/AI-and-GDPR-How-is-AI-being-regulated">privacy and security concerns</a> that come with AI.</li> <li>Not collaborating with the right partners.</li> <li>Not involving stakeholders and affected employees in the decision-making process.</li> <li>Relying too much on the <a href="https://www.techtarget.com/whatis/definition/black-box-AI">black box models of AI</a>.</li> <li>Not performing enough testing and validation.</li> <li>Overlooking change management.</li> <li>Underestimating the complexity of AI.</li> <li>Neglecting <a href="https://www.techtarget.com/searchenterpriseai/tip/Generative-AI-ethics-8-biggest-concerns">ethical considerations</a>.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="What are the key challenges in implementing AI in an organization?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What are the key challenges in implementing AI in an organization?</h2> <p>During each step of the AI implementation process, problems will arise. "The harder challenges are the human ones, which has always been the case with technology," Wand said.</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> The harder challenges are the human ones, which has always been the case with technology. </figure> <figcaption> <strong>Penny Wand</strong>Executive coach, LAH Insight LLC </figcaption> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>A steering committee vested in the outcome and representing the firm's primary functional areas should be established, she added. Instituting organizational change management techniques to encourage data literacy and trust among stakeholders can go a long way toward overcoming human challenges.</p> <p>"AI capability can only mature as fast as your overall data management maturity," Wand advised, "so create and execute a roadmap to move these capabilities in parallel."</p> <p>Key challenges that organizations typically face during an AI implementation include the following:</p> <ul class="default-list"> <li><b>Data management challenges.</b> Data management challenges include ensuring high data quality -- accuracy, completeness and timeliness -- to achieve effective AI performance. <a href="https://www.techtarget.com/searchbusinessanalytics/feature/8-types-of-bias-in-data-analysis-and-how-to-avoid-them">Poor data quality can lead to biased results</a>, requiring strong data governance. Integrating data from various sources, especially legacy systems, can also be complex.</li> <li><b>Model governance.</b> Model governance is crucial for maintaining AI reliability and ethical standards. Organizations need frameworks for security, testing and ethical compliance, and they must manage version control and <a href="https://www.techtarget.com/searchdatamanagement/tip/How-data-lineage-tools-boost-data-governance-policies">data lineage</a> to ensure models are based on trustworthy data.</li> <li><b>Performance consistency.</b> Maintaining consistent AI model performance is crucial, especially at scale. Variability in model performance can arise from changes in data inputs or shifts in underlying business processes. Organizations should use <a href="https://www.techtarget.com/whatis/definition/machine-learning-operations-MLOps">machine learning operations</a> practices for repeatable model development and deployment, including regular performance evaluations and updates based on new data and business advancements.</li> <li><b>Integration with existing systems.</b> Integrating AI implementation with existing systems, such as <a href="https://www.techtarget.com/searchcustomerexperience/definition/CRM-customer-relationship-management">CRM</a> or <a href="https://www.techtarget.com/searcherp/definition/ERP-enterprise-resource-planning">ERP</a> tools, can be complex and often requires significant adjustments to legacy infrastructure.</li> <li><b>Determining intellectual property ownership.</b> <a href="https://www.techtarget.com/searchcontentmanagement/answer/Is-AI-generated-content-copyrighted">Determining ownership of AI-generated or AI-assisted outputs</a> can be challenging, especially when multiple human and machine agents are involved. Businesses must address the risk of <a href="https://www.techtarget.com/whatis/definition/intellectual-property-IP">intellectual property</a> rights infringement or misappropriation, including unauthorized uses of AI systems such as copying, <a href="https://www.techtarget.com/searchsoftwarequality/definition/reverse-engineering">reverse-engineering</a> and hacking.</li> <li><b>Effective utilization of LLMs.</b> Finding the ideal mix between <a href="https://www.techtarget.com/whatis/definition/large-language-model-LLM">LLMs</a> and human expertise to produce high-quality, compelling and SEO-friendly content is an enormous challenge for organizations using AI. While ignoring AI technologies can reduce productivity and competitiveness, relying too much on AI can lead to poor content and plagiarism threats. To combat this challenge, businesses should thoroughly evaluate their processes to establish the optimal combination of AI and human input.</li> <li><b>Customer trust.</b> Customer acceptance challenges can arise if an organization isn't transparent about its AI implementation, which can raise concerns regarding data privacy and trust in AI-decision-making processes. Businesses should be transparent about their AI use, focusing on data security and demonstrating how AI complements human expertise rather than replacing it.</li> <li><b>Shortage of AI skills.</b> A key challenge in AI implementation is the shortage of skilled professionals with expertise in data science, machine learning, programming and domain knowledge. To address this, businesses can invest in <a href="https://www.techtarget.com/searchitchannel/feature/Generative-AI-upskilling-demands-multiple-methods-partners">upskilling their current workforce</a> through training programs and workshops.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="How can businesses ensure ethical AI implementation?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How can businesses ensure ethical AI implementation?</h2> <p>Responsible use of AI technologies is becoming increasingly important as AI systems are rapidly integrated into various sectors. For instance, a healthcare organization developing an AI tool for diagnosing medical conditions could assess its potential effects on patient privacy, consent and equity beforehand. This assessment would involve reviewing how patient data is collected, stored and used, ensuring the AI tool doesn't reinforce existing biases or produce unequal health outcomes across different patient groups.</p> <p>Organizations can address ethical and governance issues surrounding AI by establishing robust governance frameworks and addressing potential risk factors, such as bias, discrimination and privacy violations.</p> <p>Here are several <a target="_blank" href="https://ijsra.net/sites/default/files/IJSRA-2024-0235.pdf" rel="noopener">practices</a> organizations can adopt to ensure ethical AI implementation:</p> <ul class="default-list"> <li>Create and execute strategies for bias mitigation, such as training AI models on diverse data sets and regularly assessing them for fairness to help with AI discrimination.</li> <li>Ensure AI systems are transparent, explainable and auditable so stakeholders can understand the decision-making processes.</li> <li>Compliance with regulations such as <a href="https://www.techtarget.com/whatis/definition/General-Data-Protection-Regulation-GDPR">GDPR</a> and <a href="https://www.techtarget.com/searchcio/definition/California-Consumer-Privacy-Act-CCPA">CCPA</a> should be considered, as these laws not only set standards for data protection and user privacy but also build trust with consumers.</li> <li>Set up clear and ethical standards and guidelines for AI development and use.</li> <li>Involve diverse stakeholders in the AI development process to address various perspectives and concerns.</li> <li>Foster a culture of organizational awareness and accountability by training employees in ethical AI practices and encouraging them to identify and report ethical risks.</li> <li>Incentivize ethical behavior within the organization to further reinforce the importance of <a href="https://www.techtarget.com/searchenterpriseai/definition/responsible-AI">responsible AI</a> use.</li> </ul> <p><b>Editor's note:</b> <i>This article was updated in August 2025 to provide updated survey information and improve the reader experience.</i></p> <p><i>Kinza Yasar is a technical writer for WhatIs with a degree in computer networking.</i></p> </section> AI technologies can enable and support essential business functions. But organizations must have a solid foundation in place to bring value to their business strategy and planning. https://cdn.ttgtmedia.com/rms/onlineimages/ai_a238006601.jpg https://www.techtarget.com/searchenterpriseai/tip/10-steps-to-achieve-AI-implementation-in-your-business Fri, 22 Aug 2025 00:00:00 GMT <p>IoT security is the technology segment focused on safeguarding connected devices and networks in the internet of things. IoT involves adding internet connectivity to a system of interrelated computing devices, mechanical and digital machines, objects, animals and people.</p> <p>Each <a href="https://www.techtarget.com/iotagenda/definition/thing-in-the-Internet-of-Things">thing</a> has a <a href="https://www.techtarget.com/iotagenda/definition/unique-identifier-UID">unique identifier</a> and the ability to automatically transfer data over a network. However, enabling devices to connect to the internet opens them up to serious vulnerabilities if they aren't properly protected.</p> <p>The term <i>IoT</i> is broad, and as this technology evolves, the term continues to broaden. From watches to thermostats to video game consoles, nearly every technological device can interact with the internet, or other devices, in some capacity.</p> <p>IoT security is a significant aspect of IoT and has resulted in a variety of methodologies falling under that umbrella. Application programming interface (<a href="https://www.techtarget.com/searchapparchitecture/definition/application-program-interface-API">API</a>) security, public key infrastructure (<a href="https://www.techtarget.com/searchsecurity/definition/PKI">PKI</a>) authentication and network perimeter security are just a few of the methods IT organizations use to combat the growing threat of cybercrime and <a href="https://www.techtarget.com/searchsecurity/definition/cyberterrorism">cyberterrorism</a> rooted in vulnerable IoT devices.</p> <p>This is even more important for consumer IoT ecosystems, where users typically aren't cybersecurity experts and can be more vulnerable to cyberattacks. When investing in IoT systems and devices, such as in a <a href="https://www.techtarget.com/iotagenda/definition/smart-home-or-building">smart home</a>, consumers must make a concerted effort to implement robust security measures to prevent cybersecurity breaches and to mitigate attacks if they occur.</p> <section class="section main-article-chapter" data-menu-title="Why is IoT security important?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Why is IoT security important?</h2> <p>Due to the unique characteristics of IoT devices and the vast amount of data they handle, a constant threat of cyberattacks exists. Numerous examples of high-profile incidents, where a common IoT device was used to infiltrate and attack a larger network, demonstrate the need for more comprehensive IoT security. The following are key reasons why IoT security is important:</p> <ul class="default-list"> <li><b>Attack surface.</b> As more IoT systems and devices connect to the internet, the potential surface area cybercriminals can attack continues to grow, creating more opportunities for breaches and disruptions.</li> <li><b>Critical infrastructures.</b> IoT technology enhances functionality and the ability to learn and improve infrastructure functions. As a result, it's being used more in critical infrastructure, such as power grids and water, sewer and transportation systems -- increasing the likelihood of security breaches.</li> <li><b>Data protection and privacy.</b> It's not uncommon for IoT systems and devices to capture, process and transmit sensitive data, such as personally identifiable information (<a href="https://www.techtarget.com/searchsecurity/definition/personally-identifiable-information-PII">PII</a>). This makes them high-value targets for cybercriminals.</li> <li><b>Compliance.</b> IoT systems and devices support various compliance requirements, particularly data privacy ones.</li> <li><b>Business impact.</b> Cyberattacks impairing mission-critical IoT assets could result in loss of productivity, financial damage, reputational damage and legal liability.</li> </ul> <p>The ever-looming possibility of vulnerabilities, <a href="https://www.techtarget.com/searchsecurity/definition/data-breach">data breaches</a>, ransomware attacks and other risks associated with IoT device use underscores the need for strong IoT security. IoT security is vital for enterprises, as it includes a range of techniques, strategies, protocols and actions that aim to mitigate the increasing IoT vulnerabilities of modern businesses. It is also essential for consumer IoT applications, such as smart homes.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/mLg95dLm-Gs?autoplay=0&amp;modestbranding=1&amp;rel=0&amp;widget_referrer=null&amp;enablejsapi=1&amp;origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0"></iframe> </div> </section> <section class="section main-article-chapter" data-menu-title="Examples of IoT security threats"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Examples of IoT security threats</h2> <p>The more ways devices connect to each other, the more opportunities threat actors have to intercept them. <a href="https://www.techtarget.com/whatis/definition/HTTP-Hypertext-Transfer-Protocol">HTTP</a> and APIs are just two of the channels IoT devices rely on that hackers can intercept.</p> <p>The IoT umbrella doesn't only include internet-based devices, either. Appliances that use Bluetooth technology also count as IoT devices and require IoT security. The following are examples of IoT security threats and vulnerabilities:</p> <ul class="default-list"> <li><b>Inadequate authentication.</b> Without strong authentication measures, especially with passwords and role-based authentication, IoT devices and systems are vulnerable to malware attacks. Multifactor authentication (<a href="https://www.techtarget.com/searchsecurity/definition/multifactor-authentication-MFA">MFA</a>) helps alleviate device vulnerability.</li> <li><b>Lack of encryption.</b> IoT systems and devices must have security that prevents the processing and transmission of sensitive data formatted as plain text. Data at rest and in motion must be encrypted.</li> <li><b>Lack of patching and updating.</b> IoT systems and devices that use older firmware and application code increase system vulnerability. Users must keep security software current with vendor updates and patches.</li> <li><b>Unsafe access controls.</b> Strong passwords and MFA strengthen <a href="https://www.techtarget.com/searchsecurity/definition/access-control">access controls</a>. Additional steps, such as properly configuring access permissions and using role-based authentication, also strengthen access security.</li> <li><b>Risky network perimeter.</b> IoT systems and devices must have secure network access, such as strong firewalls. Networks should be checked to identify unsafe ports and unnecessary services.</li> <li><b>Cyberattacks using artificial intelligence.</b> While AI is an important resource for IoT security, hackers can also use it to automate and scale attacks on IoT ecosystems. AI-based cybersecurity systems should be considered as part of a defense-in-depth security structure.</li> <li><b>Distributed-denial-of-service, spoofing and botnet attacks.</b> <a href="https://www.techtarget.com/searchsecurity/definition/distributed-denial-of-service-attack">DDoS</a> attacks send out a flood of data that overwhelms a device, rendering it unstable or shutting it down. Spoofing attacks impersonate legitimate IoT devices, sending false data or commands. Compromised IoT systems can be turned into botnets that can launch DDoS attacks.</li> <li><b>Replayed data.</b> Cybercriminals can hack into a system and capture legitimate data packets that can be stored and then replayed to launch unauthorized access. This attack is found in smart locks and industrial controls. The <a href="https://www.techtarget.com/searchnetworking/definition/anti-replay-protocol">anti-replay protocol</a> addresses this issue.</li> <li><b>Resource limitations.</b> Not all IoT devices have the computing power to integrate sophisticated firewalls or antivirus software. Users must evaluate prospective purchases to ensure that the product can deliver adequate cybersecurity protection.</li> <li><b>Inadequate physical device security.</b> IoT devices and system units should be located in physically secure areas, as opposed to public or remote locations. Hackers and vandals can damage devices, steal data and install malware.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="How to protect IoT systems and devices"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How to protect IoT systems and devices</h2> <p>Enterprises can use the following tools and technologies to improve their data protection protocols and security posture:</p> <ul class="default-list"> <li><b>Introduce IoT security during development.</b> Most IoT security risks and issues can be overcome with better preparation, particularly during the research and development process at the start of any consumer, enterprise or industrial IoT (<a href="https://www.techtarget.com/iotagenda/definition/Industrial-Internet-of-Things-IIoT">IIoT</a>) device development. Enabling security by default is critical, along with providing the most recent operating systems and using secure hardware.</li> <li><b>Use PKI and digital certificates.</b> PKI can secure client-server connections between multiple networked devices. Using a two-key asymmetric cryptosystem, PKI facilitates the encryption and decryption of private messages and interactions using <a href="https://www.techtarget.com/searchsecurity/definition/digital-certificate">digital certificates</a>. These systems help to protect the cleartext information that users input into websites to complete private transactions. E-commerce wouldn't be able to operate without the security of PKI.</li> <li><b>Ensure network security.</b> Networks provide a huge opportunity for threat actors to remotely control IoT devices. Because networks involve both digital and physical components, on-premises IoT security should address both types of access points. Protecting an IoT network includes ensuring port security, disabling port forwarding and never opening ports when not needed; using antimalware, firewalls, intrusion detection systems and intrusion prevention systems; blocking unauthorized Internet Protocol (IP) addresses; and ensuring systems are patched and up to date.</li> <li><b>Prioritize API security.</b> APIs are the backbone of most sophisticated websites. For example, they let travel agencies aggregate flight information from multiple airlines into one location. Unfortunately, hackers can compromise these channels of communication, making <a href="https://www.techtarget.com/searchapparchitecture/definition/API-security">API security</a> necessary for protecting the integrity of data being sent from IoT devices to back-end systems and ensuring only authorized devices, developers and apps communicate with APIs. T-Mobile's 2018 data breach exposed the consequences of poor API security: Due to a leaky API, the mobile giant exposed the personal data of more than 2 million customers, including billing ZIP codes, phone numbers and account numbers.</li> </ul> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/5_iot_privacy_and_security_best_practices-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/5_iot_privacy_and_security_best_practices-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/5_iot_privacy_and_security_best_practices-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/5_iot_privacy_and_security_best_practices-f.png 1280w" alt="List of five IoT privacy and security best practices." height="290" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>There are several steps to take when mitigating IoT security challenges. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="Other IoT security methods and best practices"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Other IoT security methods and best practices</h2> <p>The following is a list of activities that should be part of every organization's IoT security efforts:</p> <ul class="default-list"> <li><b>Network access control.</b> <a href="https://www.techtarget.com/searchnetworking/definition/network-access-control">NAC</a> can help identify and inventory IoT devices connecting to a network. This provides a baseline for tracking and monitoring devices.</li> <li><b>Segmentation.</b> IoT devices that need to connect directly to the internet should be segmented into their own networks and have restricted access to the enterprise network. Network segments should monitor for anomalous activity, taking action if an issue is detected.</li> <li><b>Security gateways.</b> Acting as an intermediary between IoT devices and the network, <a href="https://www.techtarget.com/searchsecurity/feature/6-questions-to-ask-before-evaluating-secure-web-gateways">security gateways</a> have more processing power, memory and capabilities than the IoT devices themselves, which lets them add features such as firewalls to ensure hackers can't gain access to the IoT devices they connect.</li> <li><b>Patch management and continuous software updates.</b> It's critical to provide a way to update devices and software either over network connections or through automation. Having a coordinated disclosure of vulnerabilities is also important for updating devices as soon as possible. Consider end-of-life strategies as well.</li> <li><b>Training.</b> IoT and operational system security are new to many existing security teams. Security staff must keep up to date with new or unknown systems, learn new architectures and programming languages, and be ready for new security challenges. C-level and cybersecurity teams should receive regular <a href="https://www.techtarget.com/searchsecurity/tip/Top-10-cybersecurity-online-courses">cybersecurity training</a> to keep up with modern threats and security measures.</li> <li><b>Team integration.</b> Along with training, integrating disparate and regularly siloed teams can be useful. For example, having programming developers work with security specialists can help ensure the proper controls are added to devices during the development phase.</li> <li><b>Consumer education.</b> Consumers must be made aware of the <a target="_blank" href="https://www.nist.gov/itl/applied-cybersecurity/nist-cybersecurity-iot-program/consumer-iot-cybersecurity" rel="noopener">dangers of IoT systems</a> and provided steps to stay secure, such as updating default credentials and applying software updates. Consumers can also play a role in requiring device manufacturers to create secure devices by refusing to use those that don't meet high-security standards.</li> <li><b>Enforcement and automation of zero-trust policies.</b> The <a href="https://www.techtarget.com/searchsecurity/definition/zero-trust-model-zero-trust-network">zero-trust model</a> dictates that all users -- whether inside or outside the organization's network -- must be verified, authorized and continually evaluated for security configuration and posture before being given access to applications and data. Automating zero-trust policies and enforcing them can mitigate security threats against IoT devices.</li> <li><b>Multifactor authentication.</b> MFA adds an extra layer of security by requiring more than one form of identification when requesting access to a device or network. By enforcing MFA policies, both enterprises and home users can improve the security of IoT devices.</li> <li><b>Machine learning.</b> ML technology can be used to secure IoT devices by automating the management and scanning of devices throughout the entire network. Since every device connected to the network is scanned, it stops assaults automatically before IT teams are alerted.</li> </ul> <p>The following is a brief list of IoT security best practices:</p> <ul class="default-list"> <li>Revise and replace outdated security credentials with strong passwords and MFA.</li> <li>Update and patch firmware and applications as often as possible, following vendor guidelines; consider using automatic updates.</li> <li>Monitor device logs to detect suspicious activity, such as sign-ins, access to various resources and changes in security policies.</li> <li>Enable data encryption for data at rest and in transit. This is especially important for third-party services, such as the cloud.</li> <li>Keep an accurate and current device inventory. It's essential to keep track of authorized devices and identify suspicious ones.</li> <li>Test IoT device security using penetration tests and other predictive analyses. This helps identify vulnerabilities and improve security.</li> <li>Build security into IoT ecosystems and institute a schedule of regular system reviews and tests.</li> <li>Establish a culture of security for IoT ecosystems, using strong passwords that are regularly changed.</li> <li>Provide security awareness and training to users.</li> </ul> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineImages/networking-iot_network_design-f.png"> <img data-src="https://www.techtarget.com/rms/onlineImages/networking-iot_network_design-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineImages/networking-iot_network_design-f_mobile.png 960w,https://www.techtarget.com/rms/onlineImages/networking-iot_network_design-f.png 1280w" alt="Diagram of IoT security architecture components." height="336" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>Protecting the network is a key responsibility of IoT security. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="Which IoT devices are most vulnerable to security breaches?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Which IoT devices are most vulnerable to security breaches?</h2> <p>Because they're connected to the internet, all IoT systems and devices face the risk of attack. The following is a list of systems and devices typically found in these ecosystems.</p> <h3>Consumer environments and smart homes</h3> <ul class="default-list"> <li>Smart watches.</li> <li>Smart door locks.</li> <li>Smart thermostats.</li> <li>Smart garage doors.</li> <li>Home security systems.</li> <li>Lighting systems.</li> <li>Smart appliances, such as stoves, refrigerators and coffee makers.</li> <li>Smart baby monitors.</li> <li>Smart pet tracking.</li> </ul> <h3>Commercial ecosystems</h3> <ul class="default-list"> <li>Building access control systems.</li> <li>Smart building management systems.</li> <li>Smart elevators.</li> <li>Smart monitoring systems, using CCTV and motion detectors.</li> <li>Smart heating, ventilation and cooling systems.</li> <li>Smart door locking systems.</li> <li>Specialized medical equipment.</li> <li>Video cameras.</li> <li>Smart printers.</li> <li>Various sensors.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Which industries are most vulnerable to IoT security threats?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Which industries are most vulnerable to IoT security threats?</h2> <p>IoT security hacks can happen anywhere -- from a smart home to a manufacturing plant to a connected car. The severity of the attack depends on the system, the data collected and the information it contains.</p> <p>For example, an attack disabling the brakes of a connected car or hacking a connected health device, such as an insulin pump, can be life-threatening. Likewise, an attack on a refrigeration system housing medicine that's monitored by an IoT system can ruin the viability of a medication if temperatures fluctuate. Similarly, an attack on critical infrastructure, such as an oil well, energy grid or water supply, can be disastrous.</p> <p>Other attacks, however, can't be underestimated. For example, an attack against smart door locks could potentially let a burglar enter a home. Or, in other security breaches, an attacker could pass malware through a connected system to scrape PII, wreaking havoc for those affected.</p> <p>Generally speaking, industries that are most vulnerable to IoT security threats include, but aren't limited to, the following:</p> <ul class="default-list"> <li>Retail companies.</li> <li>Trucking industry.</li> <li>Consumer electronics.</li> <li>Utilities and critical infrastructure.</li> <li>Healthcare.</li> <li>Education.</li> <li>Government agencies.</li> <li>Financial institutions.</li> <li>Energy and utility companies.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Notable IoT security breaches and IoT hacks"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Notable IoT security breaches and IoT hacks</h2> <p>Security experts have warned of the potential risk of large numbers of insecure devices connected to the internet since the IoT concept first originated in the late 1990s. Many attacks subsequently have made headlines, including refrigerators and TVs being used to send spam, as well as hackers infiltrating baby monitors and talking to children. Many IoT hacks don't target the devices themselves; rather, they use IoT devices as an entry point into the larger network.</p> <p>The following are some notable IoT security incidents:</p> <ul class="default-list"> <li><b>Stuxnet.</b> In 2010, researchers revealed that the Stuxnet virus was used to physically damage Iranian centrifuges, with attacks starting in 2006 but the primary attack occurring in 2009. Considered one of the earliest examples of an IoT attack, Stuxnet targeted <a href="https://www.techtarget.com/whatis/definition/SCADA-supervisory-control-and-data-acquisition">supervisory control and data acquisition</a> systems in industrial control systems, using malware to infect instructions sent by programmable logic controllers. Attacks on industrial networks have continued, with malware such as CrashOverride -- also known as Industroyer -- Triton and VPNFilter targeting vulnerable <a href="https://www.techtarget.com/whatis/definition/operational-technology">operational technology</a> and IIoT systems.</li> <li><b>TRENDnet.</b> In 2012, a backdoor coding error permitted public access to live feeds from home IP-based streaming security cameras. The Federal Trade Commission forced the company to improve its webcam security practices.</li> <li><b>IoT botnet.</b> In December 2013, a researcher at enterprise security firm Proofpoint Inc. discovered the first IoT botnet. According to the researcher, more than 25% of the botnet was made up of devices other than computers, including smart TVs, baby monitors and household appliances.</li> <li><b>Jeep.</b> In 2015, security researchers Charlie Miller and Chris Valasek executed a wireless hack on a Jeep, changing the radio station on the car's media center, turning its windshield wipers and air conditioner on, and stopping the accelerator from working. They said they could also kill the engine, engage the brakes and disable the brakes altogether. Miller and Valasek were able to infiltrate the car's network through Chrysler's in-vehicle connectivity system, Uconnect.</li> <li><b>Mirai.</b> This is one of the largest IoT botnets to date. It first attacked journalist Brian Krebs' website and French web host OVH in September 2016; the attacks clocked in at 630 gigabits per second and 1.1 terabits per second, respectively. The following month, <a href="https://www.techtarget.com/searchnetworking/definition/domain-name-system">domain name system</a> service provider Dyn's network was targeted, making a number of websites, including Amazon, Netflix, Twitter and <em>The New York Times</em>, unavailable for hours. The attacks infiltrated the network through consumer IoT devices, including IP cameras and routers. A number of Mirai variants have since emerged, including Hajime, Hide 'N Seek, Masuta, PureMasuta, Wicked and Okiru.</li> <li><b>St. Jude.</b> In a January 2017 notice, the Food and Drug Administration warned that the embedded systems in radio frequency-enabled St. Jude Medical implantable cardiac devices -- including pacemakers, defibrillators and resynchronization devices -- could be vulnerable to security intrusions and attacks.</li> <li><b>Ring.</b> Hackers gained access to Ring home security system cameras in 2019 using old and weak passwords.</li> <li><b>Big-IP boxes.</b> In July 2020, Trend Micro discovered an IoT Mirai botnet downloader that was adaptable to new malware variants, which would help deliver malicious payloads to exposed Big-IP boxes. The samples found also exploited recently disclosed or unpatched vulnerabilities in common IoT devices and software.</li> <li><b>Verkada.</b> In March 2021, security camera startup Verkada had 150,000 of its <a href="https://www.computerweekly.com/news/252497593/Attack-on-surveillance-cameras-a-warning-over-security-ethics">live camera feeds hacked</a> by a group of Swiss hackers. These cameras monitored activity inside schools, prisons, hospitals and private company facilities, such as Tesla.</li> <li><b>Remote code execution vulnerabilities.</b> In late 2022, hackers began exploiting a series of 13 IoT vulnerabilities related to remote code execution. They installed a modified version of the Mirai malware on compromised devices, giving them unauthorized control over the affected systems.</li> <li><b>Akuvox.</b> In March 2023, Akuvox's smart intercom was found to have zero-day flaws that allowed remote eavesdropping and surveillance.</li> <li><b>Trusted Platform Module.</b> Also in March 2023, vulnerabilities related to buffer overflow were found in the <a href="https://www.techtarget.com/whatis/definition/trusted-platform-module-TPM">Trusted Platform Module</a> 2.0 protocol, putting billions of IoT devices at risk.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="IoT security standards and legislation"> <h2 class="section-title"><i class="icon" data-icon="1"></i>IoT security standards and legislation</h2> <p>Many IoT security frameworks and standards have been developed. These provide tools and checklists to help companies create and deploy secure IoT devices. The following are some primary IoT security standards, regulations and frameworks.</p> <h3>International standards</h3> <ul class="default-list"> <li><b>International Organization for Standardization (ISO)/International Electrotechnical Commission (IEC) 27400:2022.</b> This standard provides guidance on IoT security and privacy risks, principles and controls.</li> <li><b>ISO/IEC 27001:2022.</b> This is a global standard for information security management systems that can be used in IoT environments.</li> <li><b>IEC 62443 series.</b> These standards address cybersecurity for industrial automation and control systems, especially for industrial IoT.</li> <li><b>European Telecommunications Standards Institute EN 303 645:2024.</b> This European standard covers consumer IoT device security.</li> </ul> <h3>European Union regulations</h3> <ul class="default-list"> <li><b>Cyber Resilience Act.</b> This regulation addresses the implementation of cybersecurity on AI-based products.</li> <li><b>Radio Equipment Directive.</b> This radio equipment regulatory framework addresses cybersecurity safeguards for wireless devices.</li> <li><b>General Data Protection Regulation.</b> Commonly known as GDPR, this regulation protects the collection and processing of personal data on IoT devices.</li> <li><b>Network and Information Security Directive 2.</b> This directive, also known as NIS2, provides guidance on cybersecurity for numerous digital systems, including IoT.</li> </ul> <h3>U.S. regulations</h3> <ul class="default-list"> <li><b><a href="https://www.techtarget.com/searchsecurity/tip/Cyber-Trust-Mark-certification-and-how-IoT-devices-qualify">Cyber Trust Mark</a>.</b> This is a voluntary labeling program developed by the Federal Communications Commission to help consumers identify secure IoT products.</li> <li><b>IoT Cybersecurity Improvement Act of 2020.</b> This legislation establishes cybersecurity standards for IoT devices.</li> <li><b>Executive Order 14028.</b> This 2021 executive order, "Improving the Nation's Cybersecurity," advocated for stronger cybersecurity standards across federal systems, including IoT.</li> <li><b>California IoT Cybersecurity Law SB-327.</b> This law requires manufacturers to implement reasonable security features in consumer IoT devices.</li> </ul> <h3>Security frameworks</h3> <ul class="default-list"> <li><b>National Institute for Standards and Technology SP 800-213 (2021). </b>This Special Publication, IoT Device Cybersecurity Guidance for the Federal Government, provides detailed guidance for security on IoT devices.</li> <li><b>IoT Security Assurance Framework.</b> This framework, also known as IoTSF, provides guidance for ensuring the security of IoT devices and systems throughout their lifecycle.</li> <li><b>Open Worldwide Application Security Project IoT Top 10.</b> The nonprofit foundation OWASP lists security risks associated with IoT development.</li> <li><b>Industrial Internet Security Framework.</b> This provides guidance on risks and security for IIoT systems.</li> </ul> <p><i>IoT endpoints have emerged as major targets for cybercriminals. Discover the </i><a href="https://www.techtarget.com/iotagenda/tip/5-IoT-security-threats-to-prioritize"><i>top IoT security threats</i></a><i> and how to prioritize them.</i></p> </section> IoT security is the technology segment focused on safeguarding connected devices and networks in the internet of things. https://cdn.ttgtmedia.com/visuals/digdeeper/4.jpg https://www.techtarget.com/iotagenda/definition/IoT-security-Internet-of-Things-security Tue, 05 Aug 2025 00:00:00 GMT <p>Sensor data is the output of a device that detects, analyzes and responds to some type of input from the physical environment. The output is used to provide information to an end user or as input to another system or to guide a process. Sensors can be used to detect just about any physical element.</p> <p>Sensor data is an integral component of internet of things (IoT) and edge computing environments and initiatives. In IoT, almost any entity imaginable can be outfitted with a <a href="https://www.techtarget.com/iotagenda/definition/unique-identifier-UID">unique identifier</a> and the capacity to transfer data over a network. Much of the data transmitted is sensor data.</p> <p>The huge volume of data produced and transmitted from sensing devices provides a variety of useful information that's often critical to system operation and enterprise decision-making. It is a <a href="https://www.techtarget.com/searchdatamanagement/definition/big-data">big data</a> challenge that businesses are addressing with sensor data analytics.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/7CQftX_tBy0?si=nZ47lPkT1YU-GpT6?autoplay=0&amp;modestbranding=1&amp;rel=0&amp;widget_referrer=null&amp;enablejsapi=1&amp;origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0"></iframe> </div> <section class="section main-article-chapter" data-menu-title="How sensor data works"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How sensor data works</h2> <p>Sensors gather and generate information based on the physical conditions surrounding them. Sensors usually include the following:</p> <ul class="default-list"> <li>A <a href="https://www.techtarget.com/whatis/definition/processor">processor</a> to convert physical signals into digital data.</li> <li>A connector between the sensor and the system analyzing the data.</li> <li>Communications capabilities to transmit data to people or machines.</li> <li>A power source.</li> </ul> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/iota-sensor_in_action.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/iota-sensor_in_action_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/iota-sensor_in_action_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/iota-sensor_in_action.png 1280w" alt="Diagram showing how IoT sensors collect and transmit data to the cloud." height="316" width="559"> <figcaption> <i class="icon pictures" data-icon="z"></i>IoT sensors take physical readings and transmit them to the cloud for processing. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <p>IoT is a large physically connected and <a href="https://www.techtarget.com/searchnetworking/definition/What-is-a-wireless-sensor-network-WSN">wireless sensor network</a> containing an array of IoT devices with sensors attached. Both wired and wireless sensor systems combine specialized <a href="https://www.techtarget.com/whatis/definition/transducer">transducers</a> with a communications infrastructure to monitor and record conditions at various locations. IoT devices communicate with one another without human intervention.</p> <p>IoT sensor data exists in three stages on the network that involve elements of data management:</p> <ol class="default-list"> <li><b>Creation.</b> Sensors gather and transmit data used for a variety of smart devices. They do this by collecting signals and turning them into data.</li> <li><b>Transmission.</b> Data generated is sent to other machines using <a href="https://www.techtarget.com/iotagenda/tip/Top-12-most-commonly-used-IoT-protocols-and-standards">network protocols</a>, such as Message Queueing Telemetry Transport, Hypertext Transfer Protocol and Constrained Application Protocol. Transmission methods vary based on loss-tolerance, security and timeliness requirements.</li> <li><b>Storage.</b> Data is stored in various formats and accessed for subsequent use, data analysis and forecasting. In some cases, it's sent in real time immediately after creation. In others, it's stored for a period of time before being sent to its next destination in batches. Storage and bandwidth limitations can dictate the amount of data transmitted and the way it's sent. Cloud-based storage is used for high-volume sensor data.</li> </ol> </section> <section class="section main-article-chapter" data-menu-title="Types of sensors"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Types of sensors</h2> <p>Sensors are usually named after the physical parameter they measure. The following is a list of sensor types and how they work:</p> <ul class="default-list"> <li><b>Temperature sensors.</b> These include thermocouples that indicate temperature by measuring a change in voltage, infrared sensors that detect emitted infrared energy and infer temperature based on intensity, and <a href="https://www.techtarget.com/whatis/definition/semiconductor">semiconductors</a> that detect temperature based on the conductivity of a semiconductor.</li> <li><b>Proximity sensors. </b>These detect the presence or absence of a nearby object or material. Inductive proximity sensors sense the presence of a metallic object using an electromagnetic field. Photoelectric ones use a beam of light to detect objects. Ultrasonic sensors use sound to detect the presence of objects.</li> <li><b>Motion sensors. </b>Accelerometers, gyroscopes and other motion sensors detect physical movement. They can use technology found in proximity sensors and are often used in security systems to detect the presence of people.</li> <li><b>Gas sensors.</b> These detect carbon dioxide and other gases, calculating the amount of an element in the air. Other examples of gas sensors are air quality sensors, which detect chemicals that <a href="https://www.techtarget.com/iotagenda/tip/Seven-use-cases-of-IoT-for-sustainability">indicate air pollution</a>; breathalyzers, which detect alcohol in the air; and humidity sensors, which measure the air's water content.</li> <li><b>Level sensors.</b> These include point level sensors that measure the level of a liquid or dry material and indicate whether it's above or below what it should be. Continuous level sensors provide continuous level readings.</li> <li><b>Light sensors.</b> Light-dependent <a href="https://www.techtarget.com/whatis/definition/resistor">resistors</a> and other similar sensors measure changes in circuit resistance to determine changes in light intensity.</li> <li><b>Pressure sensors.</b> These are devices such as a strain gauge, which has a spring element that changes shape as force is applied, affecting resistance and changing the pressure reading. Differential pressure sensors measure the difference between two pressures connected to each side of the sensor.</li> <li><b>Chemical sensors.</b> These include chlorine residual sensors, which measure the amount of chlorine in water, and pH sensors, which check the hydrogen-ion activity in a solution to measure its acidity.</li> <li><b>Biomedical sensors. </b>Also called biometric sensors, these include medical devices, such as optical heart rate sensors, which use light-sensitive <a href="https://www.techtarget.com/whatis/definition/diode">diodes</a> to determine volume changes in the capillaries above a person's wrist. They can include pulse oximeters that shine a light-emitting diode light through the finger of a patient, analyze the character of the light and use that data to determine the amount of oxygen in the blood.</li> </ul> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineImages/iota-new_capabilites_tap_bionetric_sensors-f.png"> <img data-src="https://www.techtarget.com/rms/onlineImages/iota-new_capabilites_tap_bionetric_sensors-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineImages/iota-new_capabilites_tap_bionetric_sensors-f_mobile.png 960w,https://www.techtarget.com/rms/onlineImages/iota-new_capabilites_tap_bionetric_sensors-f.png 1280w" alt="List of ways that biometric sensors are used" height="781" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>Biometric sensors are used in a variety of IoT devices. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="Examples of sensor data"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Examples of sensor data</h2> <p>One of the earliest implementations of sensor data was in World War II, where radar was used to detect objects that previously weren't within the range of sight. The following sensor examples and types of sensor data processing techniques show numerous and diverse sensor applications and use cases:</p> <ul class="default-list"> <li><b>Accelerometers.</b> These detect changes in gravitational acceleration in devices, such as smartphones and game controllers, to determine acceleration, tilt and vibration.</li> <li><b>Photosensors. </b>These detect the presence of visible light, infrared transmission and ultraviolet energy.</li> <li><b>Lidar. </b>Light detection and ranging is a <a href="https://www.techtarget.com/whatis/definition/laser">laser</a>-based method of detection, range-finding and mapping. It typically uses a low-power, eye-safe pulsing laser in conjunction with a camera.</li> <li><b>Charge-coupled devices.</b> <a href="https://www.techtarget.com/searchstorage/definition/charge-coupled-device">CCDs</a> store and display the data for an image in such a way that each pixel is converted into an electrical charge. The intensity of the charge in a CCD is related to a color in the color spectrum.</li> <li><b>Smart grid sensors. </b>These<b> </b>provide real-time data about grid conditions, detecting outages, faults and load, as well as triggering alarms. They're important to the functioning of <a href="https://www.techtarget.com/iotagenda/definition/smart-city">smart cities</a>.</li> <li><b>Gyroscope sensors.</b> These capture the speed and rotation around an axis of an object. For example, gyroscope sensors enable mobile phones to sense the speed they're going and the direction they're facing.</li> <li><b>Infrared sensors.</b> These measure heat in the surrounding air and detect <a href="https://www.techtarget.com/searchnetworking/definition/infrared-radiation">infrared radiation</a>. They are used in gas warning devices, flame detectors and precision temperature measurement.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Time series data vs. sensor data"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Time series data vs. sensor data</h2> <p>The terms <a href="https://www.techtarget.com/iotagenda/blog/IoT-Agenda/Are-time-series-databases-the-key-to-handling-the-IoT-data-deluge"><i>time series data</i></a> and <i>sensor data</i> are similar in meaning. Sensor data can be time series data and vice versa.</p> <p>The term <i>sensor data </i>emphasizes the data source and the method of data collection. This data comes from sensors.</p> <p>The term <i>time series data </i>emphasizes the fact that a given data reading or data point represents some aspect of the physical world over a period of time. Time series data is a series of data collected at different points in time and almost always includes a <a href="https://www.techtarget.com/whatis/definition/timestamp">timestamp</a>.</p> <p>Time series data doesn't always refer to sensor data. For example, stock market data <a target="_blank" href="https://www.analyticsvidhya.com/blog/2021/07/stock-market-forecasting-using-time-series-analysis-with-arima-model/" rel="noopener">over a period of time</a> is time series data that doesn't come from sensor readings. Time series data can deliver data in batches or in a continuous stream.</p> </section> <section class="section main-article-chapter" data-menu-title="Sensor data use cases"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Sensor data use cases</h2> <p>The following are examples of how sensor data is used in real-world settings:</p> <ul class="default-list"> <li><b>Air quality monitoring. </b>Sensors measure environmental pollutants like particulate matter and other gases. Such systems are often found in urban areas where <a href="https://www.techtarget.com/pharmalifesciences/feature/Understanding-the-Link-Between-Air-Pollution-and-Respiratory-Illnesses">pollution causes health risks</a>.</li> <li><b>Industrial automation. </b>These ensure that critical manufacturing systems perform at optimum efficiency and with minimal errors. These <a href="https://www.techtarget.com/iotagenda/definition/smart-manufacturing-SM">smart manufacturing</a> systems use automation sensors to detect equipment malfunctions, and improve production activities and safety.</li> <li><b>Agriculture efficiency. </b>Farmers use <a href="https://www.techtarget.com/iotagenda/definition/smart-farming">smart farming</a> systems that monitor metrics such as air temperature, humidity and soil moisture to ensure that crops produce acceptable yields.</li> <li><b>Wearable devices.</b> <a href="https://www.techtarget.com/iotagenda/definition/smartwatch">Smart watches</a> provide a wealth of health-related data. They use sensors that track metrics such as heart rates, number of steps and sleep patterns.</li> </ul> <p><i>Streamed data can be hard to store and manage because of the volume of data created. Often, it requires the use of artificial intelligence to process. Learn </i><a href="https://www.techtarget.com/searchenterpriseai/tip/How-do-big-data-and-AI-work-together"><i>how big data and AI work together</i></a><i> to process data and train AI and machine learning algorithms.</i></p> </section> Sensor data is the output of a device that detects, analyzes and responds to some type of input from the physical environment. https://cdn.ttgtmedia.com/visuals/digdeeper/3.jpg https://www.techtarget.com/iotagenda/definition/sensor-data Mon, 04 Aug 2025 09:00:00 GMT <p>A smart sensor is a device that takes input from the physical environment and uses built-in compute resources to perform predefined functions when it detects specific input. It can also process data before passing it on.</p> <p>Smart sensors enable more accurate and automated collection of environmental data with less erroneous noise among the accurately recorded information. These devices are used for monitoring and control mechanisms in a variety of environments, including smart grids, battlefield reconnaissance, exploration and science applications.</p> <p>The smart sensor is also a crucial and integral element in the <a href="https://www.techtarget.com/iotagenda/definition/Internet-of-Things-IoT">internet of things</a>. IoT technology makes it possible to provide a unique identifier for almost anything and transmit data from or about those things over the internet or a similar sensor network. One implementation of smart sensors is as components of a <a href="https://www.techtarget.com/iotagenda/definition/WSAN-wireless-sensor-and-actuator-network">wireless sensor and actuator network</a>. These networks can have thousands of nodes, where each is connected to one or more other sensors and sensor hubs as well as to individual actuators.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/iota-sensor_in_action.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/iota-sensor_in_action_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/iota-sensor_in_action_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/iota-sensor_in_action.png 1280w" alt="Diagram showing how IoT sensors collect and transmit data to the cloud." height="316" width="559"> <figcaption> <i class="icon pictures" data-icon="z"></i>A smart sensor has three components: a sensor that captures data, a microprocessor that computes on the output of the sensor, and programming and communications capabilities. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <p>Low-power mobile microprocessors typically provide compute resources in IoT environments. At a minimum, a smart sensor is made of a sensor, a microprocessor and some kind of wireless communication technology. The compute resources are an integral part of the physical design. A sensor that just sends its data along for remote processing isn't considered a smart sensor.</p> <p>A smart sensor might also include several other components besides the primary sensor. These components can include <a href="https://www.techtarget.com/whatis/definition/transducer">transducers</a>, amplifiers, excitation control, analog filters, <a href="https://www.techtarget.com/whatis/definition/analog-to-digital-conversion-ADC">analog-to-digital converters</a> and compensation that provides a built-in correction of less-than-ideal measurements or output. A smart sensor also incorporates software-defined elements that provide functions such as <a href="https://www.techtarget.com/searcherp/answer/Data-migration-vs-data-conversion-What-are-the-differences">data conversion</a>, digital processing and communication to external devices.</p> <section class="section main-article-chapter" data-menu-title="How do smart sensors work?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How do smart sensors work?</h2> <p>A smart sensor connects a raw base sensor to integrated computing resources that enable the sensor's input to be processed. The base sensor is the component that provides the sensing capability. It might be designed to sense heat, light or pressure. Often, the base sensor will produce an analog signal from an application algorithm that must be processed before it can be used. This process is also called <a href="https://www.techtarget.com/whatis/definition/digital-signal-processing-DSP">signal processing</a>.</p> <p>With signal processing, an intelligent sensor's integrated technology comes into play. An onboard microprocessor uses a technique called filtering to <a href="https://www.techtarget.com/searchnetworking/tip/How-types-of-noise-in-data-communication-systems-affect-the-network">remove signal noise</a> and convert the sensor's signal into a usable, digital format.</p> <p>Smart sensor technology also contains integrated communications capabilities that let it connect to a private cloud computing environment or the internet. This lets sensors communicate with external devices.</p> </section> <section class="section main-article-chapter" data-menu-title="What are smart sensors used for?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What are smart sensors used for?</h2> <p>Smart sensors have many uses. They're commonly found in industrial environments and are the driving force behind <a href="https://www.techtarget.com/searcherp/definition/Industry-40">Industry 4.0</a> and industrial automation, robotics and other advanced instrumentation.</p> <p>Factories use smart sensors for diagnostic purposes. Smart temperature sensors ensure machines aren't overheating, and vibration sensors monitor machines at risk of vibrating loose. Smart sensors also enable process control, such as monitoring a manufacturing process and making necessary adjustments so it can meet quality and production goals. Smart sensors automate these tasks that were once manual processes.</p> <p>Smart sensors also play a key role in the advancement of modern security systems. Thermal imaging sensors detect an intruder's body heat. Similarly, devices such as <a href="https://www.techtarget.com/whatis/definition/smart-lock">smart locks</a>, motion sensors, and window and door sensors are commonly connected to a common network. This lets the security sensors work together to create a comprehensive security status picture. They're frequently used in homes and industrial applications to detect various leaks.</p> <p>The following are some other uses for smart sensors:</p> <ul class="default-list"> <li><b>Infrastructure.</b> Utility and energy companies use smart sensors to manage power grids, identify potential infrastructure problems, such as water and waste pipe leaks, and gather data on energy and utility use.</li> <li><b>Agriculture.</b> Smart sensors analyze climate, track soil moisture, ambient temperature and humidity, as well as track livestock.</li> <li><b>Logistics.</b> These applications include the use of RFID devices to track motor vehicles and improve the efficiency of inventory management.</li> <li><b>Public sector. </b>Government agencies, especially those managing smart cities, use smart sensors to monitor traffic flow, respond quickly to emergencies, and monitor air quality.</li> <li><b>Smart homes. </b>Consumers with smart homes <a target="_blank" href="https://www.gartner.com/en/documents/5540495" rel="noopener">use sensors</a> to track and run thermostats, appliance performance, interior and exterior lighting, and security systems.</li> <li><strong>Healthcare.</strong> Smart sensors gather patient health data, such as heart rates and blood oxygen levels; monitor the performance of smart healthcare systems in hospitals and provide environmental data.</li> </ul> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/IC0mkHh7MaA?si=vMQ08hzduPS6-hwq?autoplay=0&amp;modestbranding=1&amp;rel=0&amp;widget_referrer=null&amp;enablejsapi=1&amp;origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0"></iframe> </div> </section> <section class="section main-article-chapter" data-menu-title="What are the different types of smart sensors?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What are the different types of smart sensors?</h2> <p>There are many types of special-purpose sensors in use. Five main types of smart sensors are commonly used in <a href="https://www.techtarget.com/iotagenda/definition/Industrial-Internet-of-Things-IIoT">industrial IoT</a> environments:</p> <ul class="default-list"> <li><b>Level sensors. </b>These measure the volume of space taken up in a container. A vehicle's fuel gauge might be connected to a level sensor that monitors the level of fuel in the tank.</li> <li><b>Temperature sensors. </b>These monitor a component's temperature so a corrective action can be taken if the temperature gets too high or low. For example, a temperature sensor can ensure machinery doesn't overheat.</li> <li><b>Pressure sensors.</b> These are used to monitor the pressure of gases or fluids in a pipeline. A sudden drop in pressure might indicate a leak or a flow control system issue.</li> <li><b>Infrared sensors.</b> These sensors are used in thermal imaging cameras and for temperature monitoring in noncontact infrared thermometers. Other infrared sensors are optical sensors tuned to a frequency that helps them see light in the <a href="https://www.techtarget.com/searchnetworking/definition/infrared-radiation">infrared spectrum</a>. These sensors are used in medical equipment, such as pulse oximetry devices, and in electronic devices designed for remote control operation.</li> <li><b>Proximity sensors.</b> These are used to detect the location of a person or object in relation to the sensor. In retail environments, proximity sensors can track customer movements throughout a store.</li> <li><b>Motion sensors.</b> Similar to proximity sensors, these sensors detect movement; they're often part of building and home security systems.</li> <li><b>Flow sensors.</b> These monitor in-home water systems for leaks and send alerts if one is detected.</li> </ul> <p>Other smart sensors monitor electrical power consumption, vibration in factory equipment, humidity, moisture and light.</p> </section> <section class="section main-article-chapter" data-menu-title="What are the advantages and disadvantages of smart sensors?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What are the advantages and disadvantages of smart sensors?</h2> <p>Smart sensors come with a range of benefits, but they also have challenges and drawbacks.</p> <h3>Smart sensor advantages</h3> <p>The advantages of smart sensors are most prominent when they're used for data collection in austere or remote locations. The following advantages depend on deploying the right type of sensor where they're most needed:</p> <ul class="default-list"> <li><b>Energy efficiency and sustainability. </b>A smart sensor can be programmed to be highly sensitive or receptive to even slight changes in surrounding conditions, such as temperature, humidity, moisture or acoustics. These highly accurate and reliable measurements provide a level of monitoring and data collection that can contribute to energy efficiency and <a href="https://www.techtarget.com/iotagenda/post/IoT-technology-can-advance-environmental-monitoring">sustainability efforts</a>.</li> <li><b>Access to data in difficult environments. </b>Smart sensors can collect data in remote places where it would be difficult or dangerous for people to go. Remotely operated, wireless smart sensors are particularly helpful in challenging environments.</li> <li><b>Real time, high performance. </b>Smart sensors can collect data with consistency and speed when real-time data is needed.</li> <li><b>Built-in analytics and processing.</b> Unlike traditional sensors, smart sensors feature certain built-in analytics and processing capabilities of the signals and data they receive, leading to increased efficiency because they require fewer outside analytics tools or resources.</li> </ul> <h3>Smart sensor disadvantages</h3> <p>Smart sensor developers have consistently upgraded their offerings to address drawbacks. Some of these disadvantages include the following:</p> <ul class="default-list"> <li><b>Susceptibility to tempering and hacking.</b> <a href="https://www.techtarget.com/whatis/definition/threat-actor">Malicious actors</a>, especially those looking to access collected data meant for private use, can do so if a device's cybersecurity measures are insufficient.</li> <li><b>Costs. </b>Many devices are expensive, and the cost of the upkeep required over time can also be cost prohibitive.</li> <li><b>Maintenance.</b> Sensors at some point require recalibration or upgrades because of <a href="https://www.techtarget.com/searchcio/definition/data-latency">data latency</a> or other issues. Ones located in remote settings or challenging environments can be difficult and costly to reach.</li> <li><b>Expertise. </b>Smart sensor systems often require levels of IT expertise that not all organizations have. New hires or training could be needed.</li> <li><b>IoT deployment requirements. </b>Whether in a smart home or an industrial setting, other factors must be taken into consideration before deploying IoT devices, like the power consumption required, the need for stable online connectivity and the ability to handle higher volumes of data.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="How are smart sensors different from base sensors?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How are smart sensors different from base sensors?</h2> <p>Smart sensors include an embedded digital motion processor (DMP), whereas base sensors don't. A DMP is a microprocessor that's integrated into the sensor. It lets the sensor perform onboard processing of the <a href="https://www.techtarget.com/iotagenda/definition/sensor-data">sensor data</a>. This might mean <a href="https://www.techtarget.com/searchdatamanagement/definition/normalization">normalizing the data</a>, filtering noise from electrical signals or performing other types of signal conditioning. In any case, a smart sensor performs data conversion digital processing prior to any communication to external devices.</p> <p>A base sensor is simply a sensor that isn't equipped with a DMP or other compute resources that would let it process data. Whereas a smart sensor produces output that's ready to use, a base sensor's output is raw and must typically be converted into a usable format.</p> <p>Smart sensors are generally preferred over base sensors because they include native processing capabilities. Even so, there are situations where it might be more advantageous to use a base sensor. If an engineer is designing a device and needs complete control over sensor input, then a base sensor would be preferable. Base sensors also cost less than smart sensors because they contain fewer components.</p> </section> <section class="section main-article-chapter" data-menu-title="Standards, regulations and frameworks for smart sensors"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Standards, regulations and frameworks for smart sensors</h2> <p>Owing to their growing importance and use, several standards, regulations, frameworks and groups have emerged in support of smart sensor technology for IoT applications:</p> <ul class="default-list"> <li><b>IEEE 1451. </b>The IEEE developed these standards for smart transducers. 1451.0 describes core functions and connectivity requirements, Among the additional standards in the series are details on transducer electronic data sheets and several various communications protocols.</li> <li><b>ISO/IEC 21813:2019. </b>This International Organization for Standardization and International Electrotechnical Commission framework lets IoT devices, including smart sensors, exchange information with each other.</li> <li><b>ISO/IEC 27400:2022.</b> This standard provides guidance on IoT security and privacy.</li> <li><b>IoXt Alliance Certification. </b>This is an industry organization that supports the development of guidelines for security management in IoT devices.</li> <li><b>U.K. Product Security and Telecommunications Infrastructure Act of 2024. </b>This provides security requirements for IoT devices.</li> <li><b>General Data Protection Regulation.</b> This European Union regulation has requirements for smart sensors that collect personal data.</li> <li><b>U.S. Food and Drug Administration.</b> This agency has requirements for health-related smart sensor devices, such as implants and diagnostic equipment.</li> <li><b>National Institute for Standards and Technology. </b>NIST's SP 800-213 (2021) standard establishes guidance and requirements for cybersecurity of IoT devices in the U.S.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Future of smart sensors"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Future of smart sensors</h2> <p>Key drivers in the growth of smart sensor use are expected to be smart cities, next-generation infrastructure management and industrial production management. Other areas where heavy use is expected include healthcare, especially wearable devices; edge-based integration of AI technology; and driverless motor vehicles, which will depend on information provided by smart sensors. AI is also expected to be a major driver for smart sensors in many markets.</p> <p><i>Smart sensors are most often associated with industrial equipment. Learn more about </i><a href="https://www.techtarget.com/searcherp/tip/Learn-how-manufacturing-data-is-collected"><i>how they're used to collect data in manufacturing settings</i></a><i>.</i></p> </section> A smart sensor is a device that takes input from the physical environment and uses built-in compute resources to perform predefined functions when it detects specific input. It can also process data before passing it on. https://cdn.ttgtmedia.com/visuals/digdeeper/3.jpg https://www.techtarget.com/iotagenda/definition/smart-sensor Fri, 01 Aug 2025 13:45:00 GMT <p>Internet of things device management (<a href="https://www.techtarget.com/iotagenda/definition/IoT-device">IoT device</a> management) refers to the processes and tools used to remotely register, configure, provision, maintain and monitor connected devices from a centralized platform. IoT device management tools enable organizations to have better control of their mobile devices, while also ensuring that their devices are kept working, secure and up to date.</p> <p>Many major cloud providers, such as Amazon Web Services (AWS), Google Cloud and Microsoft Azure, include IoT device management in their offerings. These platforms connect IoT devices to the cloud, where they are then accessed and managed through a central dashboard. IT administrators can access IoT device management with an internet connection from anywhere on any device.</p> <section class="section main-article-chapter" data-menu-title="How does IoT device management work?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How does IoT device management work?</h2> <p>IoT device management works by installing a client software agent on a device that <a href="https://www.techtarget.com/iotagenda/tip/Top-12-most-commonly-used-IoT-protocols-and-standards">uses a standards-based messaging protocol</a>, such as MQTT, to communicate with the management platform. IoT device management provides control over the entire lifecycle of IoT devices.</p> <p>The IoT device management process includes the following:</p> <ul class="default-list"> <li><b>Registering devices.</b> Users must register their devices with their device management platforms before exchanging data.</li> <li><b>Provisioning. </b>This involves modifying devices from their original, off-the-shelf settings to those that enable the devices to be integrated into the users' networks.</li> <li><b>Authentication.</b> This is a way for users to confirm the identities of their devices as they're enrolled in IoT management systems. This guarantees that only authorized devices are enrolled, and it keeps sensitive corporate data secure and prevents breaches.</li> <li><b>Configuration. </b>This is the process of personalizing the functionality of IoT devices. For instance, users can optimize their devices' features with additional code, revise their devices' settings for new requirements or add extra intelligence to their devices.</li> <li><b>Maintenance.</b> IoT maintenance ensures that IoT devices in the field can be updated when necessary so they stay up to date and secure.</li> <li><b>Diagnostics.</b> IoT diagnostics enable companies to monitor their connected devices closely to reduce security failures, firmware bugs and the risk of downtime. Additionally, diagnostics gives organizations the data necessary to <a href="https://www.techtarget.com/searcherp/feature/Predictive-maintenance-Definition-benefits-example-strategy">implement predictive maintenance</a> before minor issues become major problems.</li> <li><b>End of life.</b> When individual devices become obsolete or IoT projects are finished, IoT device management is responsible for securely and cost-effectively decommissioning devices. Companies can retain the devices' data if they are going to replace the decommissioned physical devices or archive the data if they are retiring the devices permanently.</li> </ul> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/iot_device_management_process-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/iot_device_management_process-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/iot_device_management_process-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/iot_device_management_process-f.png 1280w" alt="IoT device management process." height="189" width="559"> <figcaption> <i class="icon pictures" data-icon="z"></i>There are several steps to IoT device management, including provisioning, authentication and configuration. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="Key features of IoT device management"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Key features of IoT device management</h2> <p>The main features of IoT device management include the following:</p> <ul class="default-list"> <li><b>Easy onboarding.</b> IoT device management software should offer a user-friendly and intuitive onboarding process that enables IT admins to easily add new devices to their systems. The software should include support for many types of devices, such as laptops, IoT devices, smartphones and tablets.</li> <li><b>Troubleshooting remotely.</b> IoT device management software should enable remote troubleshooting to reduce manual efforts and resolve user issues quickly.</li> <li><b>Metadata management.</b> An IoT device management platform should enable IT admins to easily view and manage each device's metadata, e.g., the serial number, make, model and current version of the firmware. This helps with managing inventory and tracking assets.</li> <li><b>Analytics and reports.</b> IoT devices generally include <a href="https://www.techtarget.com/searchbusinessanalytics/definition/edge-analytics">edge analytics</a> capabilities. Using graphical user interface dashboards, the software can display detailed analytics insights in real time. The data can then be used to create reports for the business.</li> <li><b>Log management. </b>The software should enable IT admins to view and manage the logs each device generates, which can help identify issues and track device activity.</li> <li><b>Security.</b> IoT device management software should have a wide range of security features, e.g., access control, encryption and authentication, to help prevent data breaches and unauthorized access.</li> <li><b>Over-the-air updates.</b> OTA updates enable IT admins to automatically push updates and patches.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Benefits of IoT device management"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Benefits of IoT device management</h2> <p>The main benefits of IoT device management include the following:</p> <ul class="default-list"> <li><b>Simplified process for updating devices. </b>IoT device management enables IT admins to efficiently update many devices in a controlled, phased manner. Admins can configure devices remotely and simultaneously perform software updates for any number of devices or device groups. Not only does this save a huge amount of time, but it also ensures that users can quickly, efficiently and accurately send and receive critical information from their devices.</li> <li><b>Stringent security. </b>IoT networks <a href="https://www.techtarget.com/searchcustomerexperience/tip/Top-customer-data-privacy-best-practices">handle sensitive corporate and customer data</a>. IoT device management software can help companies protect this data by implementing data encryption and segmentation. The software enables admins to manage, upgrade and update access to certain devices or device groups, ensuring that the devices and data are always secure.</li> <li><b>Adaptation for rapidly changing business models. </b>IoT device management software enables companies to get the most out of their IoT platforms by enabling them to more quickly shift to <a href="https://www.techtarget.com/iotagenda/tip/Top-9-IoT-business-models">new business models</a>. By effectively managing IoT devices, organizations can create better products and services, better understand the needs of their customers and develop new sources of revenue.</li> <li><b>Faster IoT device registration. </b>IoT device management offers tools to enable companies to more quickly develop, configure and deploy connected devices, enabling them to put entire networks into operation immediately.</li> <li><b>Enhanced device organization. </b>Effective device management enables companies to organize devices into groups and hierarchies and manage the pertinent access policies for each group or hierarchy. This streamlines device tracking and operations and helps companies better align their devices with established security and business practices.</li> <li><b>Easier-to-manage remote devices. </b>It can be difficult to access devices in the field that aren't patched or updated. IoT device management enables admins to remotely update, as well as execute reboots, security patches and factory resets, across an entire fleet of IoT devices. In addition, IoT device management enables admins to remotely access, troubleshoot and resolve issues that individual devices might experience.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Drawbacks of IoT device management"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Drawbacks of IoT device management</h2> <p>As the number of IoT devices increases, so does the number of <a href="https://www.techtarget.com/iotagenda/post/Prepare-your-organization-for-these-3-IoT-challenges">difficulties managing them</a>. Some of the most common drawbacks of IoT device management are the following:</p> <ul class="default-list"> <li><b>Access control. </b>One of the major concerns with IoT devices is security, as these devices are often left unsecured and not password-protected -- making them easy targets for cybercriminals. To ensure devices, as well as sensitive corporate and customer data, are protected, companies must control who accesses their devices and their data.<br><br>IoT device management helps organizations identify, track and control how many devices are connected at any time. In addition, most IoT device management tools enable organizations to configure strong access controls. Companies should also ensure that users employ strong and unique passwords or use public key cryptography, as well as regularly update device firmware.</li> <li><b>Device proliferation. </b>In addition to the challenges of managing massive numbers of IoT devices, the explosion of IoT devices can also put a strain on networks as the demand for bandwidth also increases, causing network congestion and outages. IoT device management software usually has features to enable companies to automate and centrally manage device operations.</li> <li><b>Fragmented data. </b>As more IoT devices come online, it can be challenging for companies to manage the volume and variety of the data they generate, as <a href="https://www.techtarget.com/whatis/feature/Structured-vs-unstructured-data-The-key-differences">much of it is unstructured</a> and not easy to use. IoT device management tools can collect, organize and analyze this data.</li> </ul> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/7CQftX_tBy0?autoplay=0&amp;modestbranding=1&amp;rel=0&amp;widget_referrer=null&amp;enablejsapi=1&amp;origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0"></iframe> </div> </section> <section class="section main-article-chapter" data-menu-title="IoT device management use cases"> <h2 class="section-title"><i class="icon" data-icon="1"></i>IoT device management use cases</h2> <p>There are a number of IoT device management use cases, including the following.</p> <h3>Smart home automation</h3> <p>Using IoT device management cloud service platforms, homeowners can remotely manage and monitor their <a href="https://www.techtarget.com/iotagenda/definition/smart-home-or-building">smart home</a> devices, including security cameras, smart locks and thermostats, from a single location. Service providers can use IoT device management platforms to remotely troubleshoot and resolve problems.</p> <h3>Industrial IoT</h3> <p>Organizations can use IoT device management software to manage and monitor their <a href="https://www.techtarget.com/iotagenda/definition/Industrial-Internet-of-Things-IIoT">industrial IoT</a> devices, such as sensors and monitoring systems, to boost operations, increase productivity and reduce downtime.</p> <h3>Healthcare</h3> <p>Companies can implement IoT device management platforms to manage and monitor medical devices, including wearable health trackers and remote patient monitoring systems. And healthcare providers can use these platforms to remotely monitor the health of their patients, track whether patients are taking their medications and identify potential problems before they become serious.</p> <h3>Smart city infrastructure</h3> <p>City officials can use IoT device management to manage and monitor <a href="https://www.techtarget.com/iotagenda/definition/smart-city">smart city</a> infrastructure, including streetlights, waste management and traffic management systems. Additionally, officials can use this software to enhance operations, save money and improve their sustainability efforts by monitoring the performance of their devices and pinpointing areas for improvement.</p> <h3>Connected heating systems</h3> <p>Facility managers and residents can use IoT device management to remotely control and monitor connected heating systems in their commercial buildings and smart homes using tablets or smartphones.</p> </section> <section class="section main-article-chapter" data-menu-title="Popular IoT device management software"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Popular IoT device management software</h2> <p>There are many IoT device management platforms on the market. A sampling of these platforms are the following.</p> <h3>AWS IoT Device Management</h3> <p>This IoT device management software from AWS helps organizations onboard, organize, monitor and manage their IoT devices remotely. AWS IoT Device Management includes a suite of AWS IoT services from device software to control services and analytics services.</p> <h3>Azure IoT Hub</h3> <p>Microsoft's Azure IoT Hub is an IoT device management software hosted on the Azure cloud platform. This software includes features that enable device security, provisioning and management. Azure IoT Hub also includes added services to <a target="_blank" href="https://anywhere.epam.com/business/how-to-build-an-iot-application" rel="noopener">help developers build</a> IoT applications.</p> <h3>Hologram</h3> <p>Hologram is an IoT device management platform for any organization with a globally distributed IoT presence, which makes it challenging to effortlessly establish and manage network connections. Hologram makes it easier for companies to navigate between multiple local carriers as its cellular platform includes SIM cards that switch networks automatically, giving IoT devices coverage across more than 550 carriers in more than 190 countries.</p> <h3>Bosch IoT Suite</h3> <p>Bosch IoT Suite is an IoT device management platform based on open source projects and standards that supports a range of integration features. The tool is designed for managing connected devices at scale, making it ideal for industrial and enterprise use. Bosch IoT Suite features include the use of digital twins, mass device management, device edge management and device inventories.</p> </section> <section class="section main-article-chapter" data-menu-title="Best practices for IoT device management"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Best practices for IoT device management</h2> <p>To ensure an organization's IoT devices function and operate properly, a proper IoT device management process is important. Best practices that pair with IoT device management include the following:</p> <ul class="default-list"> <li><b>Maintaining security.</b> IoT devices should be continually monitored for vulnerabilities throughout their lifecycle. Devices can be remotely patched to address security issues. Strong authentication and zero-trust policies should be followed to prevent unauthorized access or potential data breaches.</li> <li><b>Performing OTA updates.</b> OTA updates are useful to patch vulnerabilities and other issues at scale, as they do not require physical access to each connected device.</li> <li><b>Monitoring devices.</b> Connected IoT devices should be monitored not just to ensure security, but also to ensure device connectivity and usage, which aid in optimizing performance.</li> <li><b>Configuring devices.</b> Standardizing and managing device settings upon setup helps ensure consistency, while also improving scalability.</li> </ul> <p><em>IoT management includes many different practices and processes aimed at improving device function and health throughout its lifetime. Learn more about best practices for <a href="https://www.techtarget.com/searchdatamanagement/feature/IoT-data-management-extends-best-practices-to-the-edge">managing IoT at the edge</a>.</em></p> </section> Internet of things device management (IoT device management) is the processes and tools used to remotely register, configure, provision, maintain and monitor connected devices from a centralized platform. https://cdn.ttgtmedia.com/visuals/digdeeper/5.jpg https://www.techtarget.com/iotagenda/definition/internet-of-things-device-management-IoT-device-management Fri, 01 Aug 2025 09:00:00 GMT <p>The artificial intelligence of things (AIoT) is the combination of <a href="https://www.techtarget.com/searchenterpriseai/definition/AI-Artificial-Intelligence">AI</a> technologies and the internet of things (<a href="https://www.techtarget.com/iotagenda/definition/Internet-of-Things-IoT">IoT</a>) infrastructure. AIoT's goal is to create more efficient IoT operations, improve human-machine interactions, and enhance <a href="https://www.techtarget.com/searchdatamanagement/definition/data-management">data management</a> and analytics.</p> <p>AI is the simulation of human intelligence processes by machines, especially computer systems, and typically uses specialized AI algorithms, along with <a href="https://www.techtarget.com/searchenterpriseai/definition/natural-language-processing-NLP">natural language processing</a>, <a href="https://www.techtarget.com/searchenterpriseai/definition/machine-learning-ML">machine learning</a> speech recognition and machine vision.</p> <p>IoT is a system of connected devices, mechanical and digital machines, or objects with unique identifiers with the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction. For example, a <i>thing</i> in IoT can be a person's heart monitor implant, an automobile with built-in sensors to alert the driver when tire pressure is low, a personal assistant or any other object that can be assigned an <a href="https://www.techtarget.com/searchunifiedcommunications/definition/Internet-Protocol">Internet Protocol</a> address and transfer data over a network.</p> <section class="section main-article-chapter" data-menu-title="Why is AIoT important?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Why is AIoT important?</h2> <p>Considering the capabilities AI can add to an IoT device or supporting network, think of adding AI as raising the performance bar on IoT technology. One of the key attributes of AI is its ability to automate tasks that would otherwise be performed manually.</p> <p>A <a href="https://www.techtarget.com/iotagenda/definition/smart-home-or-building">smart home</a>, for example, has many of its functions -- e.g., security; entertainment; kitchen appliances; and heating, ventilation and air conditioning -- handled by an advanced smart device. Adding AI can help develop an all-encompassing smart home management system that, once programmed, offers performance that can literally schedule, administer and maintain all household activities, while providing an easy-to-use interface to the homeowner.</p> <p>Smart personal assistants become logical extensions of their human owners, as they enable greater capabilities and flexibility in support of their daily activities.</p> </section> <section class="section main-article-chapter" data-menu-title="How does AIoT work?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How does AIoT work?</h2> <p>In AI IoT systems and devices, AI is embedded into infrastructure components, such as programs and chipsets, which are all connected using IoT networks. Application programming interfaces (<a href="https://www.techtarget.com/searchapparchitecture/definition/application-program-interface-API">APIs</a>) are then used to ensure all hardware, software and platform components can operate and communicate without effort from the end user.</p> <p>When operational, IoT devices create and gather data, which AI analyzes to provide insights and improve efficiency and productivity. Insights are gained when an AI system allows the use of processes such as data learning.</p> <p>AIoT systems are generally designed and configured either as cloud-based or edge-based.</p> <h3>Cloud-based AIoT</h3> <p>Commonly referred to as <i>IoT cloud</i>, cloud-based IoT is the management and processing of data from IoT devices using cloud computing platforms. <a href="https://www.techtarget.com/iotagenda/tip/Know-when-to-use-cloudless-IoT-or-stick-to-the-cloud">Connecting IoT devices to the cloud</a> is essential since that's where data is stored, processed and accessed by various applications and services.</p> <p>Cloud-based AIoT is composed of the following four layers:</p> <ol class="default-list"> <li><b>Device layer.</b> This includes several types of hardware, including tags, beacons, sensors, cars, production equipment, embedded devices, and health and fitness equipment.</li> <li><b>Connectivity layer.</b> This layer comprises fields and cloud gateways consisting of a hardware or software element that links cloud storage to controllers, sensors and other intelligent devices.</li> <li><b>Cloud layer.</b> This consists of data processing via an AI engine, data storage, data visualization, data analysis and analytics, and data access via an API.</li> <li><b>User communication layer.</b> This layer is made up of web portals and mobile applications.</li> </ol> <p>Figure 1 depicts the architecture of cloud-based AIoT systems.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/cloud_based_implementation_of_aiot_architecture-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/cloud_based_implementation_of_aiot_architecture-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/cloud_based_implementation_of_aiot_architecture-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/cloud_based_implementation_of_aiot_architecture-f.png 1280w" alt="Cloud-based AIoT implementation" height="370" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>Figure 1. The basic architecture of a cloud-based AIoT implementation includes these four layers. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <h3>Edge-based AIoT</h3> <p>AIoT data can also be <a href="https://www.techtarget.com/searchenterpriseai/feature/How-to-build-scalable-edge-AI-systems">processed at the edge</a>, meaning the data from IoT devices is processed as close to these devices as possible to minimize the bandwidth needed to move data, while avoiding possible delays to data analysis.</p> <p>Edge-based AIoT consists of the following three layers:</p> <ol class="default-list"> <li><b>Collection terminal layer.</b> This covers a range of hardware devices, such as embedded devices, cars, manufacturing equipment, tags, beacons, sensors, mobility devices, and health and fitness equipment, that are connected to the gateway over existing power lines.</li> <li><b>Connectivity layer.</b> This consists of the field gateways that the collection terminal layer is connected to over existing power lines.</li> <li><b>Edge layer.</b> This layer includes facilities for data storage, data processing and insight generation.</li> </ol> <p>Figure 2 depicts an edge-based AIoT implementation.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/edge_based_implementation_of_aiot_architecture-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/edge_based_implementation_of_aiot_architecture-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/edge_based_implementation_of_aiot_architecture-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/edge_based_implementation_of_aiot_architecture-f.png 1280w" alt="Edge AIoT diagram" height="286" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>Figure 2. The AIoT data collected is processed closer to the source, or edge. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="Applications and examples of AIoT"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Applications and examples of AIoT</h2> <p>Although many AIoT applications focus on the implementation of <a href="https://www.techtarget.com/searchenterpriseai/definition/cognitive-computing">cognitive computing</a> in consumer appliances, the following are several examples of the wider use of AIoT:</p> <figure class="main-article-image half-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/autonomous_cars-h.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/autonomous_cars-h_half_column_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/autonomous_cars-h_half_column_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/autonomous_cars-h.png 1280w" alt="How self-driving cars operate" height="274" width="279"> <figcaption> <i class="icon pictures" data-icon="z"></i>Figure 3. Autonomous cars rely on a combination of video cameras and sensor systems to collect information about adjacent vehicles, driving conditions and pedestrians. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <ul class="default-list"> <li><b>Smart cities.</b> Smart technology, such as sensors, lights and meters, collects data designed to improve operational efficiency, drive economic growth and improve residents' quality of life.</li> <li><b>Smart retail.</b> Retailers use smart cameras to recognize shoppers' faces and detect if they've scanned their items at the self-checkout before leaving the store.</li> <li><b>Smart homes.</b> Smart appliances learn through human interaction and response. AIoT appliances can also store and learn from user data to understand user habits to provide customized support.</li> <li><b>Smart office buildings.</b> AI and IoT converge in smart buildings. Companies opt for a network of smart environmental sensors installed within their offices that detect the presence of people and automatically alter the lighting and temperature to maximize energy savings. In addition, <a href="https://www.techtarget.com/searchenterpriseai/news/252516453/How-a-startup-uses-a-facial-recognition-engine-during-COVID">facial recognition technology enables smart buildings</a> to control access by using linked cameras and AI to compare live photos with a database to determine who gets access.</li> <li><b>Enterprise and industrial.</b> Manufacturers use smart chips to detect when equipment isn't functioning properly or a part needs to be replaced.</li> <li><b>Social media and human resources (HR).</b> AIoT tools can be integrated with social media and HR-related platforms to create an AI decision-as-a-service function for HR professionals.</li> <li><b>Autonomous vehicles.</b> These <a href="https://www.techtarget.com/searchenterpriseai/definition/driverless-car">vehicles</a>, as noted in Figure 3, rely on multiple video cameras and sensor systems to gather data about nearby vehicles, monitor driving conditions and look for pedestrians.</li> <li><b>Autonomous delivery robots.</b> Sensors gather data about the robot's environment -- for example, a warehouse -- and then use AI to make traversal-based decisions.</li> <li><b>Healthcare.</b> Medical devices and wearables collect and monitor real-time health data, such as heart rate, and can detect irregular heartbeats.</li> <li><b>Wearable devices.</b> <a href="https://www.techtarget.com/searchmobilecomputing/definition/wearable-technology">Wearable technology</a> can monitor and analyze personal health data to offer insights into a person's fitness, sleep and general well-being.</li> <li><b>C</b><b>ollaborative robots.</b> <a href="https://www.techtarget.com/whatis/definition/collaborative-robot-cobot">Cobots</a> are intended to assist people in the manufacturing and assembly of components. They aid humans in various tasks, such as product production, assembly, packaging and quality control, by using data from IoT devices and AI tools, including computer vision.</li> <li><b>City brains.</b> City brains are intended to promote urban development by combining machine intelligence and real-time municipal data. For example, AIoT systems can process massive logs, videos and data streams from systems and sensors throughout an urban center to detect issues such as illegal parking, road accidents and changing traffic lights.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="What are the benefits and challenges of AIoT?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What are the benefits and challenges of AIoT?</h2> <p>Benefits of AIoT include the following:</p> <ul class="default-list"> <li><b>Increased operational efficiency.</b> AI-integrated IoT devices can analyze data to reveal patterns and insights and adjust system operations to become more efficient.</li> <li><b>Ability to adjust on the fly.</b> Data can be generated and analyzed to identify points of failure, which enable the system to make adjustments as needed.</li> <li><b>Data analytics.</b> Employees don't have to spend as much time monitoring IoT devices, thus saving money.</li> <li><b>Scalability.</b> The number of devices connected to an IoT system can be increased to optimize existing processes or introduce new features.</li> <li><b>Transformational technology.</b> AIoT is transformational and mutually beneficial for both types of technology, as <a href="https://www.techtarget.com/iotagenda/tip/AI-and-IoT-How-do-the-internet-of-things-and-AI-work-together">AI adds value to IoT</a> through machine learning capabilities and improved decision-making processes. IoT adds value to AI through connectivity, signaling and data exchange. AIoT can improve businesses and their services by creating more value from IoT-generated data.</li> <li><b>Enhanced security.</b> IoT devices can be susceptible to security risks. However, AI can identify and avert these risks since AI algorithms can analyze data from sensors to discover anomalies and potential security breaches. For example, AI can analyze security camera footage to spot suspicious activity and notify security staff.</li> <li><b>Reduced human error.</b> Businesses lose millions of dollars each year as a result of <a target="_blank" href="https://www.forbes.com/sites/forbestechcouncil/2021/02/22/why-you-should-consider-the-cost-of-human-error/?sh=5c891b644a32" rel="noopener">human error</a>. By integrating machine learning with IoT technology, organizations can effectively reduce errors. In normal workflows, data must pass through multiple phases or locations, creating more opportunities for human errors, such as data entry mistakes, to occur. AIoT mitigates these risks by analyzing information at its source. Minimizing data movement and reducing the number of intermediaries involved decrease the chances of errors significantly.</li> <li><b>Personalization.</b> While IoT devices can gather information about user preferences and behavior, AI can use this information to further tailor user experiences. For example, a smart speaker can use AI to learn a user's musical preferences and generate customized playlists automatically.</li> </ul> <p>Along with its benefits and use cases, there are also instances where AIoT could fail, causing a backup in production or other negative consequences. For example, autonomous delivery robots that fail might cause a delay in the delivery of a product; smart retail stores could fail to read a customer's face, leading to the customer accidentally stealing a product; or an autonomous vehicle might fail to read its surroundings, such as an oncoming stop sign, and cause an accident.</p> <p>The following are some additional challenges associated with AIoT:</p> <ul class="default-list"> <li><b>Cybersecurity issues.</b> The growing number of devices connected through AIoT increases the risk of <a href="https://www.techtarget.com/searchsecurity/tip/6-common-types-of-cyber-attacks-and-how-to-prevent-them">cyberattacks and security breaches</a>.</li> <li><b>Complexity.</b> IoT and AI technology integration can be challenging and demand particular knowledge and abilities.</li> <li><b>Data management concerns.</b> Effective data management strategies are required for processing the data gathered from various sensors.</li> <li><b>High cost.</b> Implementing AIoT technologies can be costly due to the need for specialized equipment, software and employees.</li> <li><b>Privacy concerns.</b> There are concerns about how data acquired by AIoT devices is handled and stored, which could result in privacy issues and violations.</li> </ul> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/4FxU-xpuCww?autoplay=0&amp;modestbranding=1&amp;rel=0&amp;widget_referrer=null&amp;enablejsapi=1&amp;origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0"></iframe> </div> </section> <section class="section main-article-chapter" data-menu-title="Standards and regulations that impact AIoT"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Standards and regulations that impact AIoT</h2> <p>Currently, the universe of activity associated with AIoT is governed by several standards, regulations and frameworks that ensure safety, privacy and ethical deployment.</p> <p>The following is a list of key initiatives.</p> <h3>AIoT regulatory initiatives</h3> <ul class="default-list"> <li><strong>E</strong><strong>uropean Union (E</strong><strong>U</strong><strong>)</strong><strong> AI Act.</strong> This 2024 legislation establishes a regulatory framework for AI systems, including AIoT.</li> <li><strong>EU Cyber Resilience Act.</strong> This 2024 legislation addresses the implementation of cybersecurity on AI-based products.</li> <li><strong>General Data Protection </strong><strong>Regulation</strong><strong>.</strong> This important 2016 EU legislation protects the collection and processing of personal data.</li> <li><strong>Network and Information Security Directive 2.</strong> This EU directive, launched in 2023, provides guidance on cybersecurity for numerous digital systems, including IoT.</li> <li><strong>California IoT</strong><strong> S</strong><strong>ecurity Law.</strong> This 2020 legislation requires device manufacturers to provide security features and unique passwords in consumer IoT devices.</li> <li><strong>U.S. IoT Cybersecurity Improvement Act.</strong> This 2020 legislation establishes cybersecurity standards for IoT devices.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="AIoT standards and frameworks"> <h2 class="section-title"><i class="icon" data-icon="1"></i>AIoT standards and frameworks</h2> <table class="main-article-table"> <thead> <tr> <td>Standard/Framework</td> <td>Purpose</td> </tr> </thead> <tbody> <tr> <td>ISO/IEC 27001 (2022)</td> <td>Fundamental standard for implementing an information security management system</td> </tr> <tr> <td>ISO/IEC 22989 (2022)</td> <td>Framework and terminology for AI system development</td> </tr> <tr> <td>ISO/IEC 23894 (2023)</td> <td>Guidance for managing risks associated with AI</td> </tr> <tr> <td>NIST SP 800-213 (2021)</td> <td>Guidance on cybersecurity for IoT devices</td> </tr> <tr> <td>NIST AI Risk Management Framework (2023)</td> <td>Framework providing guidance on how to design and develop AI systems with a focus on managing risks</td> </tr> <tr> <td>IEEE P7000 Series</td> <td>Guidance on ethical considerations in the development of advanced technology systems, such as IoT</td> </tr> <tr> <td>U.S. FCC Cyber Trust Mark (2024)</td> <td>Voluntary labeling for secure consumer IoT products</td> </tr> </tbody> </table> </section> <section class="section main-article-chapter" data-menu-title="What is the future of AIoT?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What is the future of AIoT?</h2> <p>With the integration of AI, IoT creates a much smarter system. The goal is to have these systems make accurate judgments without the need for human intervention.</p> <p><a href="https://www.techtarget.com/searchcio/definition/digital-transformation">Digital transformation</a> and the collaboration between AI and IoT have the potential to tap into unrealized customer value in several industry verticals, including edge analytics, autonomous vehicles, personalized fitness, remote healthcare, precision agriculture, smart retail, predictive maintenance and industrial automation.</p> <p>Popular and emerging trends of AIoT include the following:</p> <ul class="default-list"> <li><b>Edge computing.</b> This technology focuses on processing data in proximity to its source instead of relying on centralized cloud servers, offering benefits such as decreased <a href="https://www.techtarget.com/whatis/definition/latency">latency</a>, enhanced efficiency and reduced network congestion.</li> <li><b>Swarm intelligence.</b> Swarm intelligence involves the coordinated behavior of decentralized and self-organized systems. Inspired by natural swarms, such as bees or ants, this technology can be applied to optimize the functioning of IoT devices.</li> <li><b>5G technology.</b> One of the bigger possible innovations in AIoT is the inclusion of <a href="https://www.techtarget.com/searchnetworking/definition/5G">5G</a>. 5G is designed to enable faster transfer of large data files in IoT devices through its higher bandwidth and lower latency.</li> <li><b>Operational efficiencies.</b> AIoT could help solve existing operational problems, such as the expense associated with effective <a href="https://www.techtarget.com/searchhrsoftware/definition/human-capital-management-HCM">human capital management</a> or the complexity of supply chains and delivery models.</li> <li><b>Computer vision.</b> The goal of computer vision is to make machines comprehend and interpret visual information gleaned from the real production environment. It can analyze video streams from cameras, recognize objects and spot anomalies in AIoT applications, enabling in-the-moment automation, monitoring and optimization. Computer vision is revolutionizing the industrial sector, especially in the context of <a href="https://www.techtarget.com/searcherp/definition/Industry-40">Industry 4.0</a>, by empowering companies to improve operational efficiency, implement quality control procedures, enhance preventive maintenance practices and prioritize worker safety measures.</li> <li><strong>Smarter cities.</strong> Within urban environments, extensive use of AIoT improves vehicular traffic management, lighting, waste collection and public safety.</li> <li><strong>Enhanced simulations using digital twins. </strong>The creation of digitized replicas of physical systems helps identify potential system failures, while enhancing overall performance.</li> <li><strong>AI-enhanced cybersecurity.</strong> AI has been demonstrating how it can greatly enhance the prevention, detection and mitigation of cyberthreats.</li> <li><strong>Enhanced environmental sustainability. AIoT built into systems impacting the environment </strong><strong>is</strong><strong> expected</strong><strong> to </strong>reduce energy consumption, improve resource usage and achieve goals for the environment and sustainability.</li> </ul> <p><em>IoT can provide numerous benefits to businesses but can be challenging to deploy. Learn the prerequisites and <a href="https://www.techtarget.com/iotagenda/Ultimate-IoT-implementation-guide-for-businesses">best practices for a successful IoT installation</a>.</em></p> </section> The artificial intelligence of things (AIoT) is the combination of AI technologies and the internet of things (IoT) infrastructure. https://cdn.ttgtmedia.com/visuals/digdeeper/1.jpg https://www.techtarget.com/iotagenda/definition/Artificial-Intelligence-of-Things-AIoT Fri, 01 Aug 2025 09:00:00 GMT <p>Internet of things (<a href="https://www.techtarget.com/iotagenda/definition/Internet-of-Things-IoT">IoT</a>) devices are nonstandard computing hardware -- such as sensors, actuators or appliances -- that connect to a wired or wireless network to transmit data.</p> <p>IoT extends internet connectivity beyond desktop computers, laptops, smartphones, tablets and other typical computing devices. It lets a range of traditionally non-internet-enabled devices and everyday objects connect to networks and the cloud. Embedded with IoT technology, these devices continue to deliver their primary function, but they also can communicate and interact over the internet and be remotely monitored and controlled.</p> <p>IoT devices have industrial and consumer uses, and they're typically integrated into tools such as mobile devices, industrial equipment and medical devices. They are also used in <a href="https://www.techtarget.com/iotagenda/definition/smart-city">smart cities</a>, where they send data or interact with other IoT devices over a network.</p> <p>IoT and IoT devices provide real-time data for industrial or enterprise use cases. They also make daily activities faster, easier and more convenient for consumers.</p> <section class="section main-article-chapter" data-menu-title="Examples of IoT devices"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Examples of IoT devices</h2> <p>Connected devices are part of an ecosystem in which every device talks to other related devices in the environment to automate home and industry tasks. As part of this, they transmit <a href="https://www.techtarget.com/iotagenda/definition/sensor-data">sensor data</a> to users, businesses and other intended parties. The devices can be categorized into three main groups: consumer, enterprise and industrial.</p> <h3>Consumer-connected devices</h3> <p>These devices include smart TVs, smart speakers such as Google Home's Nest, toys, <a href="https://www.techtarget.com/searchmobilecomputing/definition/wearable-technology">wearables</a> and smart appliances. In a <a href="https://www.techtarget.com/iotagenda/definition/smart-home-or-building">smart home</a>, IoT devices are designed to sense and respond to a person's presence or physical contact with the device.</p> <p>In this setup, when a person arrives home, the car communicates with the garage to open the door. Once inside, the thermostat is already adjusted to a preset temperature, and the lighting is set to a comfortable intensity and color.</p> <p>Other smart home devices include sprinklers that adjust the amount of water the lawn needs based on the weather and robotic vacuum cleaners that learn which areas of the home must be cleaned most often. Smart security devices, such as front door cameras, link to a security system that might also include motion detectors, cameras and smart door locks.</p> <h3>Enterprise IoT devices</h3> <p>There is a variety of <a href="https://www.techtarget.com/searchnetworking/definition/edge-device">edge devices</a> designed for businesses available. They vary in capabilities but tend to be geared toward maintaining a facility or improving operational efficiency. Some options include smart locks, smart thermostats, smart lighting and smart security. Consumer versions of these technologies are also available.</p> <p>In the enterprise, smart devices can help with meetings. <a href="https://www.techtarget.com/iotagenda/definition/smart-sensor">Smart sensors</a> located in a conference room can help an employee locate and schedule an available meeting room, ensuring the proper room type, size and features are available.</p> <p>Likewise, retailers can <a href="https://www.techtarget.com/searcherp/tip/RFID-vs-IoT-What-are-the-differences">use radio frequency ID tags</a> to track their goods, increasing inventory accuracy. IoT devices are also used to keep track of inventory as it moves along in the supply chain for <a href="https://www.techtarget.com/searcherp/definition/supply-chain-management-SCM">supply chain management</a>.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineImages/iota-devices.png"> <img data-src="https://www.techtarget.com/rms/onlineImages/iota-devices_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineImages/iota-devices_mobile.png 960w,https://www.techtarget.com/rms/onlineImages/iota-devices.png 1280w" alt="Diagram showing the various types of IoT devices that are available." height="487" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>Consumer, enterprise and industrial IoT devices include smart TVs and smart sensors outfitted for conference rooms and assembly line machines. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <h3>Industrial IoT devices</h3> <p>Factories or other industrial environments rely on industrial IoT (IIoT) devices. These are often sensors used to monitor an assembly line or other manufacturing processes. Sensor data is transmitted to monitoring applications that ensure key processes are running optimally. These same sensors can predict when parts need to be replaced, preventing unexpected downtime. Links to systems using artificial intelligence (AI) enhance IIoT devices.</p> <p>If a smart sensor detects an abnormal condition, indicating a problem has occurred, the system can send a notification to service technicians informing them what's wrong and what parts they need to fix the problem. This saves the technician from coming on-site to diagnose the problem and then having to travel to a warehouse to get the part needed to fix the problem.</p> <p>In the medical industry, IoT devices monitor patient health and track vital signs. If a patient needs attention, these monitors send notifications to the relevant healthcare workers.</p> </section> <section class="section main-article-chapter" data-menu-title="How do IoT devices work?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How do IoT devices work?</h2> <p>IoT devices vary in terms of functionality, but they do have some similarities in how they work. First, IoT devices are physical objects designed to interact with the real world in some way. The device might be a sensor on an assembly line or an intelligent security camera. In either case, the device senses what's happening in its surrounding environment.</p> <p>The devices typically include an integrated central processing unit, firmware and a network adapter. In most cases, IoT devices connect to a <a href="https://www.techtarget.com/searchnetworking/definition/DHCP">Dynamic Host Configuration Protocol</a> server and acquire an Internet Protocol (IP) address that they can use to function on the network. Some IoT devices are directly accessible over the public internet, but most are designed to operate exclusively on private networks.</p> <p>Although not an absolute requirement, many IoT devices are configured and managed through a software application. Some devices have integrated web servers, eliminating the need for an external application.</p> <p>Once an IoT device has been configured and begins to operate, most of its traffic is outbound. A security camera, for example, streams video data; likewise, an industrial sensor streams sensor data. Some IoT devices, such as smart lights, accept inputs.</p> </section> <section class="section main-article-chapter" data-menu-title="IoT gateways"> <h2 class="section-title"><i class="icon" data-icon="1"></i>IoT gateways</h2> <p>Connecting IoT devices with the computing resources they need to perform their activities often requires the use of an <a href="https://www.techtarget.com/iotagenda/definition/IoT-gateway">IoT gateway</a>. Typically used in <a href="https://www.techtarget.com/searchcloudcomputing/tip/Explore-cloud-native-vs-cloud-based-vs-cloud-enabled-apps">cloud-enabled environments</a>, an IoT gateway is a physical device or software application that provides the connection point between the cloud and IoT devices, such as the types described in this article.</p> <p>IoT gateways operate like network <a href="https://www.techtarget.com/searchnetworking/definition/router">routers</a>, moving data between IoT devices and the cloud. They support two-way traffic: Outbound data traffic goes to the cloud, while incoming traffic might be used for various administrative tasks, such as updating firmware or patching applications.</p> <p>Gateways with added intelligence can perform computing tasks in addition to routing data traffic. This is an important distinction between gateways and Wi-Fi routers. Such gateways can perform preprocessing activities at network edges before sending data to the cloud. They also can handle multiple <a href="https://www.techtarget.com/iotagenda/tip/Top-12-most-commonly-used-IoT-protocols-and-standards">IoT protocols</a>.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/7CQftX_tBy0?autoplay=0&amp;modestbranding=1&amp;rel=0&amp;widget_referrer=null&amp;enablejsapi=1&amp;origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0"></iframe> </div> </section> <section class="section main-article-chapter" data-menu-title="What is IoT device management?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What is IoT device management?</h2> <p>Several challenges can hinder the successful deployment of an IoT system and its connected devices, including security, interoperability, power and processing capabilities, scalability and availability. Many of these problems can be addressed with <a href="https://www.techtarget.com/iotagenda/definition/internet-of-things-device-management-IoT-device-management">IoT device management</a>, either by adopting standard protocols or using services offered by a vendor.</p> <p>Device management helps companies integrate, organize, monitor and remotely manage internet-enabled devices at scale, offering features critical to maintaining the health, connectivity and security of the IoT devices along their entire lifecycles.</p> <p>IoT device management contains separate categories, including onboarding devices, configuration, maintenance, diagnostics and end-of-life management.</p> <p>Device management typically follows a pattern such as the following:</p> <ul class="default-list"> <li>Registration and activation.</li> <li>Authentication and authorization.</li> <li>Configuration.</li> <li>Provisioning.</li> <li>Monitoring and diagnostics.</li> <li>Troubleshooting.</li> <li>Firmware updates and patching.</li> </ul> <p>Some examples of standardized device management protocols include the Open Mobile Alliance Device Management for remote management of mobile devices and OMA Lightweight Machine to Machine for sensor networks. IoT device management services and software are available from vendors, including Amazon, Google, IBM and Microsoft.</p> </section> <section class="section main-article-chapter" data-menu-title="IoT device connectivity and networking"> <h2 class="section-title"><i class="icon" data-icon="1"></i>IoT device connectivity and networking</h2> <p>The networking, communication and connectivity protocols used with internet-enabled devices largely depend on the specific IoT application deployed. Just as there are many different IoT applications, there are many different connectivity and communication options, including the following:</p> <ul class="default-list"> <li>Constrained Application Protocol, or CoAP.</li> <li>Datagram Transport Layer Security, or DTLS.</li> <li><a href="https://www.techtarget.com/iotagenda/definition/MQTT-MQ-Telemetry-Transport">MQ Telemetry Transport</a>, or MQTT.</li> <li>Data Distribution Service, or DDS.</li> <li>Advanced Message Queuing Protocol, or AMQP.</li> </ul> <p>Wireless protocols include the following:</p> <ul class="default-list"> <li><a href="https://www.techtarget.com/searchnetworking/definition/IPv6-Internet-Protocol-Version-6">IPv6</a>.</li> <li>Zigbee <a href="https://www.techtarget.com/iotagenda/definition/Bluetooth-Low-Energy-Bluetooth-LE">Bluetooth Low Energy</a>.</li> <li><a href="https://www.techtarget.com/iotagenda/definition/Z-Wave">Z-Wave</a>.</li> </ul> <p>Cellular, satellite, Wi-Fi and Ethernet can also be used.</p> <p>Connectivity options have tradeoffs in terms of power consumption, range and bandwidth. All of these must be considered when choosing connected devices and protocols for an IoT application. These options include high range, power consumption and bandwidth; low range, power consumption and bandwidth; or high range, low power consumption and bandwidth.</p> <p>In most cases, IoT devices connect to an IoT gateway or to another edge device where data can either be analyzed locally or sent to the cloud for analysis. Some devices have integrated data processing capabilities that minimize the amount of data that must be sent to the cloud or data center. This type of processing, which often uses AI and machine learning capabilities built into the device, continues to grow in popularity as IoT devices create more data.</p> </section> <section class="section main-article-chapter" data-menu-title="What security risks do IoT devices pose?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What security risks do IoT devices pose?</h2> <p>The interconnection of traditionally nonintelligent devices raises several questions in relation to security and privacy. IoT technology has moved faster than the mechanisms available to safeguard devices and their users. Fortunately, advances in security technology continue to make these devices secure and resistant to cyberattacks.</p> <p>The following are some IoT security risks that organizations must address:</p> <ul class="default-list"> <li>Increased attack surfaces.</li> <li>Unsecured hardware.</li> <li>Poor asset management.</li> <li><a href="https://www.techtarget.com/searchcloudcomputing/definition/shadow-IT-shadow-information-technology">Shadow IoT</a>.</li> <li>Unencrypted data transmissions.</li> <li><a href="https://www.techtarget.com/searchnetworking/definition/domain-name-system">Domain name system</a> threats.</li> <li><a href="https://www.techtarget.com/searchsecurity/definition/distributed-denial-of-service-attack">Distributed denial-of-service</a>&nbsp;attacks.</li> <li>Malicious node injections.</li> <li>IoT ransomware attacks.</li> <li>Firmware exploits.</li> </ul> <p>Numerous security breaches affecting IoT devices have occurred, detailed below.</p> <h3>CyberAv3ngers</h3> <p>In 2023, cyberattackers compromised Israeli-made Unitronics Vision Series programmable logic controllers and human-machine interfaces. <a target="_blank" href="https://www.cisa.gov/news-events/cybersecurity-advisories/aa23-335a?Offer=ab_ss_reeng_plt_var1" rel="noopener">The group</a>, using the name CyberAv3ngers, targeted water facilities that used the Israel-developed industrial control devices to manage water pressure.</p> <h3>Mars Hydro and LG-LED Solutions</h3> <p>This large data breach was discovered in February 2025. It involved smart grow lamps and climate management systems that had more than 2 billion records in an unprotected database. Among the exposed data were Wi-Fi passwords and IP addresses.</p> <h3>Eleven11Bot</h3> <p>A botnet discovered in early 2025 exploited tens of thousands of unprotected IoT devices, such as webcams, many of which had critical vulnerabilities.</p> <h3>Ransomware attacks on healthcare institutions</h3> <p>To date, dozens of healthcare institutions across the U.S. have faced hundreds of ransomware attacks on unprotected devices, such as patient health monitoring systems. An <a target="_blank" href="https://www.techtarget.com/healthtechsecurity/news/366624205/Cyberattack-causes-system-wide-outage-at-Kettering-Health" rel="noopener">Ohio-based hospital chain</a> experienced a system-wide technology outage when hackers exploited unpatched patient monitoring systems.</p> <p>IoT security measures worth considering include the following:</p> <ul class="default-list"> <li>Implement access confirmation using two-factor and multifactor authentication.</li> <li>Use role-based authentication.</li> <li>Have strong encryption for routers, such as Wi-Fi- Protected Access (WPA) 2 or WPA3.</li> <li>Harden every device.</li> <li>Encrypt data at rest and in motion.</li> <li>Segment networks, setting up a separate IoT network.</li> <li>Use strong passwords that are changed regularly.</li> <li>Patch security systems regularly.</li> <li>Sign up for automatic updates from manufacturers.</li> <li>Turn off unused features.</li> <li>Check device logs and track devices.</li> <li>Shop smart, looking for reputable brands.</li> <li>Look for devices certified by reputable security organizations.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="IoT device security standards and legislation"> <h2 class="section-title"><i class="icon" data-icon="1"></i>IoT device security standards and legislation</h2> <p>The IoT Cybersecurity Improvement Act of 2020 directed the National Institute of Standards and Technology (<a href="https://www.techtarget.com/searchsoftwarequality/definition/NIST">NIST</a>) to develop and publish standards and guidelines on the use and management of IoT devices.</p> <p>NIST developed an IoT device security labeling process for consumers in 2022. Building on that, the Federal Communications Commission in 2023 launched the U.S Cyber Trust Mark program. It provides U.S. consumers with labeled products that meet NIST security criteria.</p> <p>The following are three key standards for IoT security and design:</p> <ul class="default-list"> <li><b>ISO/IEC 30141:2024 Internet of Things -- Reference architecture.</b> This provides IoT <a target="_blank" href="https://www.iso.org/standard/88800.html" rel="noopener">reference architecture</a> for secure and scalable systems.</li> <li><b>ISO/IEC 21823-1:2019 Internet of things (IoT) -- Interoperability for IoT systems.</b> This provides <a target="_blank" href="https://iotbyhvm.ooo/iot-standards-and-regulations-a-comprehensive-guide" rel="noopener">guidance</a> on how IoT systems and devices connect and interoperate with one another</li> <li><b>NIST Special Publication 800-213.</b> This describes how to establish cybersecurity protection for IoT devices.</li> </ul> <p>Whether an organization is already using IoT devices or is considering adopting them, it should be prepared to handle the unique security challenges presented by IoT devices.</p> </section> <section class="section main-article-chapter" data-menu-title="IoT device trends and anticipated growth"> <h2 class="section-title"><i class="icon" data-icon="1"></i>IoT device trends and anticipated growth</h2> <p>The latest IoT Analytics "State of IoT Summer 2024" report predicted that, by 2030, there will be more than <a target="_blank" href="https://iot-analytics.com/number-connected-iot-devices/" rel="noopener">41 billion connected IoT devices</a>.</p> <p>Among the key growth drivers are 5G wireless technology, edge technology using AI, smart homes, wearables, IoT in healthcare and environmental protection. Important trends that will impact device growth include <a href="https://www.techtarget.com/iotagenda/definition/Artificial-Intelligence-of-Things-AIoT">AI of things</a>, smart analytics, digital twins, use of low Earth orbit satellite communications and new security regulations for IoT devices.</p> <p><i>The key to making effective use of IoT devices is to understand</i> <a href="https://www.techtarget.com/iotagenda/feature/How-to-build-an-effective-edge-IoT-architecture"><i>how edge technology and IoT work together</i></a>.</p> <p><i>Sharon Shea contributed to this definition.</i></p> </section> Internet of things (IoT) devices are nonstandard computing hardware -- such as sensors, actuators or appliances -- that connect to a wired or wireless network to transmit data. https://cdn.ttgtmedia.com/visuals/digdeeper/2.jpg https://www.techtarget.com/iotagenda/definition/IoT-device Fri, 01 Aug 2025 00:00:00 GMT <p>IoT is one of the most transformative technologies of the 21st century. It's powering advancements across industries, such as healthcare, transportation and manufacturing, as well as the supply chain.</p> <p>As a key driver of Industry 4.0, <a href="https://www.techtarget.com/iotagenda/definition/Internet-of-Things-IoT">IoT</a> enables smart automation and data-driven decision-making. According to Fortune Business Insights, the market is <a target="_blank" href="https://www.fortunebusinessinsights.com/industry-reports/internet-of-things-iot-market-100307" rel="noopener">projected to grow</a> from $714 billion in 2024 to $4,062 billion by 2032.</p> <p>Beyond its innovative products, tools and applications, IoT offers a wealth of career opportunities. As demand for smart technologies grows across industries, so does the need for skilled professionals who can <a href="https://www.techtarget.com/iotagenda/Ultimate-IoT-implementation-guide-for-businesses">design IoT systems</a> that collect data and translate it into actionable insights.</p> <p>For anyone looking to learn more about designing and building IoT systems, there are many online courses, certifications and degree programs available. IoT courses range from introductory to advanced levels, and some are even free. Explore the following 11 options to learn about IoT and related technologies.</p> <section class="section main-article-chapter" data-menu-title="Beginner online IoT courses"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Beginner online IoT courses</h2> <p>The following are some introductory courses that provide a good starting point for IT and other professionals interested in IoT.</p> <h3>1. Coursera's Industrial Internet of Things (IIoT)</h3> <p>This course is part of the University of Michigan's Digital Technologies and the Future of Manufacturing Specialization. Students learn the concept of IIoT; its applications in manufacturing, including predictive maintenance; and business considerations for deploying IIoT systems. The course also presents several interviews, case studies and presentations from industry experts, who discuss the state of IIoT in their industries.</p> <p><b>What's involved:</b> This course is structured into four modules and includes approximately 10 hours of self-paced video lessons. A certificate is available.</p> <p><b>Cost: </b>Free to audit. The certificate requires a fee or a Coursera Plus subscription.</p> <p><b>Prerequisites:</b> No prior IoT coursework or experience is required.</p> <p><b>Course link: </b><a target="_blank" href="https://www.coursera.org/learn/industrial-internet-of-things" rel="noopener">https://www.coursera.org/learn/industrial-internet-of-things</a></p> <h3>2. Coursera's Introduction and Programming with IoT Boards</h3> <p>This course introduces IoT and teaches students how to program IoT boards. It's geared toward upper-level undergraduates, graduate students and engineers who want to get into IoT. Students learn to program various IoT development kits, including Arduino, <a href="https://www.techtarget.com/whatis/definition/Raspberry-Pi-35-computer">Raspberry Pi</a> and Samsung Artik. They also gain foundational knowledge of how <a href="https://www.techtarget.com/whatis/definition/sensor">sensors</a>, <a href="https://www.techtarget.com/iotagenda/tip/Get-acquainted-with-the-types-of-actuators-in-IoT">actuators</a> and communication protocols work together to create smart and connected applications. A professor at the Pohang University of Science and Technology in South Korea teaches this course.</p> <p><b>What's involved: </b>Approximately seven hours of self-paced content. A certificate is available.</p> <p><b>Cost:</b> Free to audit. The certificate requires a fee or a Coursera Plus subscription.</p> <p><b>Prerequisites:</b> No prior IoT courses or experience are required.</p> <p><b>Course link: </b><a target="_blank" href="https://www.coursera.org/learn/introduction-iot-boards" rel="noopener">https://www.coursera.org/learn/introduction-iot-boards</a></p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/iot_certifications_vs_degrees-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/iot_certifications_vs_degrees-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/iot_certifications_vs_degrees-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/iot_certifications_vs_degrees-f.png 1280w" alt="Table comparing scope, duration, cost and career paths of IoT certifications vs. academic degrees." height="243" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>The requirements for a certificate vs. a degree in IoT technology are different. Find out which is right for you. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <h3>3. Simplilearn's Introduction to IoT</h3> <p>This introductory course covers everything from IoT origins and fundamentals to IoT design, frameworks, development considerations and <a href="https://www.techtarget.com/iotagenda/tip/Top-8-IoT-applications-and-examples-in-business">using IoT in the enterprise</a>. The course is geared toward midlevel professionals to <a href="https://www.techtarget.com/searchcustomerexperience/definition/chief-experience-officer-CXO">chief experience officer</a>-level management professionals who want to use IoT to drive business growth. A certificate is awarded upon completing the course.</p> <p><b>What's involved:</b> Approximately two hours of self-paced video lessons.</p> <p><b>Cost:</b> Free.</p> <p><b>Prerequisites:</b> No prior IoT courses or experience are required.</p> <p><b>Course link:</b> <a target="_blank" href="https://www.simplilearn.com/learn-iot-basics-skillup" rel="noopener">https://www.simplilearn.com/learn-iot-basics-skillup</a></p> <h3>4. Udemy's Internet of things (IoT) for Beginners: Getting Started</h3> <p>This course is targeted at beginners, hobbyists and students exploring IoT fundamentals. It covers both theoretical concepts and hands-on applications using popular development boards, such as Raspberry Pi and Arduino. It also provides a brief introduction to MicroPython. It introduces topics such as identifying various sensors and devices, as well as understanding the differences between <a href="https://www.techtarget.com/iotagenda/definition/microcontroller">microcontrollers</a> and microprocessors. Designed as a quick orientation, this course provides a starting point rather than an in-depth, skill-building experience.</p> <p><b>What's involved:</b> Approximately 80 minutes of on-demand video content spread across 24 lectures.</p> <p><b>Cost:</b> $44.99.</p> <p><b>Prerequisites:</b> No prior IoT experience required.</p> <p><b>Course link:</b> <a target="_blank" href="https://www.udemy.com/course/internet-of-things-iot-for-beginners-getting-started/" rel="noopener">https://www.udemy.com/course/internet-of-things-iot-for-beginners-getting-started/</a></p> </section> <section class="section main-article-chapter" data-menu-title="Intermediate online IoT courses"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Intermediate online IoT courses</h2> <p>IT pros who are acquainted with IoT or who have worked with simple IoT devices might be ready for a more advanced offering, such as the following courses.</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> IoT is booming and is expected to stay that way for years, making it a solid career option. </figure> <i class="icon" data-icon="z"></i> </div> </blockquote> <h3>1. Coursera's Architecting Smart IoT Devices</h3> <p>IoT systems and the <a href="https://www.techtarget.com/iotagenda/definition/smart-home-or-building">smart home</a> or industrial devices they work with have many integrated IoT hardware and software components. This course teaches students about these components, including IoT networks, boards, operating systems and processors. But most importantly, it provides best practices on how to integrate components. Offered by EIT Digital, this course is targeted at learners with some background in programming or <a href="https://www.techtarget.com/iotagenda/definition/embedded-system">embedded systems</a> who are looking to understand how to architect, debug and optimize IoT devices. At the end of the course, students should be able to architect an embedded IoT device.</p> <p><b>What's involved:</b> Approximately 33 hours of self-paced videos, divided into five modules.</p> <p><b>Cost:</b> Free to audit. A certificate is available for a fee or with a Coursera Plus subscription.</p> <p><b>Prerequisites:</b> Some technical background required.</p> <p><b>Course link: </b><a target="_blank" href="https://www.coursera.org/learn/iot-architecture" rel="noopener">https://www.coursera.org/learn/iot-architecture</a></p> <h3>2. Coursera's M2M &amp; IoT Interface Design and Protocols for Embedded Systems</h3> <p>This University of Colorado Boulder course is a hands-on introduction to how embedded devices communicate with each other and the cloud. It has an emphasis on sharing data in modern IoT systems. It also introduces machine-to-machine (<a href="https://internetofthingsagenda.techtarget.com/definition/machine-to-machine-M2M">M2M</a>) systems, embedded system architecture and <a href="https://www.techtarget.com/iotagenda/tip/Top-12-most-commonly-used-IoT-protocols-and-standards">IoT protocols and standards</a>. Participants work with Python, Node.js and AWS to develop connected systems and gain insight into cloud computing infrastructures, microservices and embedded system security.</p> <p><b>What's involved:</b> Approximately eight hours of self-paced content, divided into four modules.</p> <p><b>Cost:</b> Free to audit. A certificate is available for a fee or with a Coursera Plus subscription.</p> <p><b>Prerequisites:</b> Some technical background required.</p> <p><b>Course link:</b> <a target="_blank" href="https://www.coursera.org/learn/m2m-iot-interface-design-embedded-systems" rel="noopener">https://www.coursera.org/learn/m2m-iot-interface-design-embedded-systems</a></p> <h3>3. EDX's UTAustinX: Embedded Systems -- Shape the World: Multi-Threaded Interfacing</h3> <p>This is a hands-on, project-driven program designed to teach learners how to develop real-time embedded computer systems using the Texas Instruments TM4C123 microcontroller. It builds on foundational embedded knowledge and introduces <a href="https://www.techtarget.com/whatis/definition/multithreading">multithreaded programming</a>, modular software development and <a href="https://www.techtarget.com/whatis/definition/interrupt">interrupt</a>-driven design. Students work with peripherals and implement key projects, including a data acquisition system, a simple audio player and an IoT smart object with Wi-Fi communication capability. Labs involve programming in <a href="https://www.techtarget.com/searchwindowsserver/definition/C">C</a>, debugging with tools such as logic analyzers and oscilloscopes, and interacting with physical hardware.</p> <p><b>What's involved: </b>An eight-week, self-paced course requiring approximately eight to 10 hours of study per week.</p> <p><b>Cost: </b>Free to audit, with an optional certificate available for $50-$150; hardware kit costs an additional $30-$60.</p> <p><b>Prerequisites:</b> Some experience and basic programming knowledge are required.</p> <p><b>Course link: </b><a target="_blank" href="https://www.edx.org/learn/embedded-systems/the-university-of-texas-at-austin-embedded-systems-shape-the-world-multi-threaded-interfacing" rel="noopener">https://www.edx.org/learn/embedded-systems/the-university-of-texas-at-austin-embedded-systems-shape-the-world-multi-threaded-interfacing</a></p> <h3>4. Udemy's Raspberry Pi and Arduino -- Go to The Next Level</h3> <p>This course teaches students how to set up and <a href="https://www.techtarget.com/searchitoperations/tip/What-is-a-Raspberry-Pi-used-for">use Raspberry Pi</a> to communicate with Arduino and guides them through custom projects. It shows students how to create serial communication between two devices and build an application based on that connection. The course is for students familiar with Arduino and Raspberry Pi who have a basic understanding of Python and C++ programming. Students create their own Raspberry Pi-based camera and Telegram <a href="https://www.techtarget.com/whatis/definition/bot-robot">bot</a>, as well as an intercom system using the two boards.</p> <p><b>What's involved:</b> Approximately nine hours of on-demand video, divided into 71 lectures.</p> <p><b>Cost:</b> $14.99 with a Udemy subscription plan.</p> <p><b>Prerequisites:</b> Knowledge of Arduino and Raspberry Pi is required.</p> <p><b>Course link:</b> <a href="https://www.udemy.com/course/raspberry-pi-and-arduino/" target="_blank" rel="noopener">https://www.udemy.com/course/raspberry-pi-and-arduino/</a></p> </section> <section class="section main-article-chapter" data-menu-title="Advanced online IoT courses"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Advanced online IoT courses</h2> <p>IoT experts can take their pick from a wide range of courses to expand on their knowledge, including the following.</p> <h3>1. Cognixia's Internet of Things Security Expert Training</h3> <p>Securing systems with internet connectivity and minimal human intervention is challenging. This course is for experts who want to focus on security. Students build, test and deploy Python-based IoT applications while engaging with real-world case studies, from smart cities to health monitoring systems. The curriculum provides the skills needed to design, implement and protect complex IoT ecosystems. The course also covers cryptographic techniques to <a href="https://www.techtarget.com/iotagenda/tip/Internet-of-Things-IOT-Seven-enterprise-risks-to-consider">secure IoT applications and networks</a>. It's targeted at those aiming to lead IoT security initiatives or align their expertise with certifications, such as <a href="https://www.techtarget.com/searchsecurity/definition/Certified-Cloud-Security-Professional-CCSP">Certified Cloud Security Professional</a> or <a href="https://www.techtarget.com/searchsecurity/quiz/Sample-CompTIA-CASP-practice-questions-with-answers">CompTIA Advanced Security Practitioner+</a>.</p> <p><b>What's involved:</b> 16 hours of interactive online sessions structured across three modules.</p> <p><b>Cost:</b> $1,335, often discounted to $1,200. The price includes access to course materials and certification.</p> <p><b>Prerequisites:</b> Foundational knowledge in Python, IoT architecture and basic security concepts is required.</p> <p><b>Course link:</b> <a target="_blank" href="https://www.cognixia.com/course/internet-of-things-security-expert/" rel="noopener">https://www.cognixia.com/course/internet-of-things-security-expert/</a></p> <h3>2. Coursera's Advanced IoT Systems Integration and Industrial Applications</h3> <p>This LearnQuest course teaches professionals to architect enterprise-grade IoT systems across industries, such as manufacturing, logistics and infrastructure. Modules cover <a href="https://www.techtarget.com/searchdatacenter/definition/edge-computing">edge computing</a>, <a href="https://www.techtarget.com/searchcustomerexperience/definition/real-time-analytics">real-time analytics</a>, computer science, security strategies and robotic automation. Students explore how integrated IoT systems can drive transformation in industrial operations. The curriculum emphasizes strategic system design, privacy, compliance and a holistic system-level approach to IoT integration.</p> <p><b>What's involved: </b>The self-paced course takes about 14 hours to complete.</p> <p><b>Cost:</b> Free to audit. A certificate is available for a fee or with a Coursera Plus subscription.</p> <p><b>Prerequisites:</b> Understanding of embedded systems, microcontrollers, sensors and communication protocols is required.</p> <p><b>Course link: </b><a target="_blank" href="https://www.coursera.org/learn/advanced-iot-systems-and-industrial-applications-course-3" rel="noopener">https://www.coursera.org/learn/advanced-iot-systems-and-industrial-applications-course-3</a></p> <h3>3. Coursera's Internet of Things Capstone V2: Build a Mobile Surveillance System</h3> <p>The University of California, San Diego, offers this course for intermediate to advanced learners seeking to solidify their IoT development and integration expertise. It teaches students to design and build an IoT system that uses at least one communication protocol, one actuator and two sensors. Students learn to use mobile platforms to develop systems that connect actuators and sensors to the Arrow Electronics' DragonBoard 410c development board and gain enough programming experience to create a fully functional system. Learners submit a final presentation showcasing their system.</p> <p><b>What's involved:</b> Approximately four hours of self-paced content, divided over four modules.</p> <p><b>Cost:</b> Free to audit. A certificate is available for a fee or with a Coursera Plus subscription.</p> <p><b>Prerequisites:</b> Intermediate-level knowledge of IoT and board and software programming required.</p> <p><b>Course link: </b><a target="_blank" href="https://www.coursera.org/learn/internet-of-things-capstone-version2" rel="noopener">https://www.coursera.org/learn/internet-of-things-capstone-version2</a></p> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading">Read more about IoT's important role</h3> <p><a href="https://www.techtarget.com/whatis/feature/6-best-IoT-conferences-and-events-to-attend">Best IoT conferences and events to attend</a></p> <p><a href="https://www.techtarget.com/whatis/feature/Top-18-IoT-blogs-to-follow">Top IoT blogs to follow</a></p> <p><a href="https://www.techtarget.com/iotagenda/tip/How-IoT-data-collection-works">How IoT data collection works</a></p> </div> </div> </section> <section class="section main-article-chapter" data-menu-title="Other IoT online degrees and specializations"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Other IoT online degrees and specializations</h2> <p>IoT is booming and is expected to stay that way for years, making it a solid career option. In addition to the 11 courses listed above, here are some other training programs to consider:</p> <ul type="disc" class="default-list"> <li>Capella University's <a target="_blank" href="https://www.capella.edu/online-information-technology-degrees/bs-information-technology-program/bachelors-internet-of-things" rel="noopener">Software Development in an Internet of Things Space</a>.</li> <li>Coursera's <a target="_blank" href="https://www.coursera.org/learn/industrial-iot-markets-security" rel="noopener">Industrial IoT Markets and Security</a>.</li> <li>Coursera's <a target="_blank" href="https://www.coursera.org/specializations/internet-of-things" rel="noopener">Internet of Things and AI Cloud Specialization</a>.</li> <li>DeVry University's <a target="_blank" href="https://www.devry.edu/online-programs/bachelors-degrees/information-technology-and-networking/mobile-and-networked-devices-specialization.html" rel="noopener">Bachelor's Degree Specialization in Mobile and Networked Devices</a>.</li> <li>Stanford School of Engineering's <a target="_blank" href="https://online.stanford.edu/courses/xee100-introduction-internet-things" rel="noopener">Introduction to Internet of Things</a>.</li> </ul> <p><i>Looking for more ways to up your skills? Find out more about </i><a href="https://www.techtarget.com/iotagenda/tip/7-IoT-training-certifications-to-take-your-next-career-step"><i>IoT training and certifications that will take your career to the next level</i></a><i>.</i></p> </section> IoT is transforming industries with smart automation and data-driven decisions. The market is growing rapidly, creating career opportunities. Online courses offer training from beginner to expert level. https://cdn.ttgtmedia.com/visuals/German/article/IT-certificate-learning-adobe.jpg https://www.techtarget.com/whatis/feature/11-top-IoT-online-courses-to-boost-your-career-free-and-paid Fri, 01 Aug 2025 00:00:00 GMT <p>Narrowband IoT (NB-IoT) is a wireless internet of things (<a href="https://www.techtarget.com/iotagenda/definition/Internet-of-Things-IoT">IoT</a>) standard that uses low-power wide area network (<a href="https://www.techtarget.com/iotagenda/definition/LPWAN-low-power-wide-area-network">LPWAN</a>) technology. It was developed by the 3rd Generation Partnership Project (3GPP) for connecting IoT devices to established mobile networks. NB-IoT is one of the three main 3GPP LPWAN standards.</p> <p>NB-IoT enables small amounts of infrequent two-way data transmissions between devices and a network, making it ideal for a wide range of devices and services that are low-bandwidth and that have long-life use cases. The NB-IoT communication standard lets IoT devices operate via carrier networks, either within an existing Global System for Mobile Communications (<a href="https://www.techtarget.com/searchmobilecomputing/definition/GSM">GSM</a>) carrier wave, in an unused guard band between Long-Term Evolution (<a href="https://www.techtarget.com/searchmobilecomputing/definition/Long-Term-Evolution-LTE">LTE</a>) channels or independently.</p> <p>One of the goals of NB-IoT is to boost the coverage extension beyond what existing cellular technologies offer. To do that, NB-IoT offers transmission repetitions and different bandwidth allocation configurations in uplink transmission.</p> <p>NB-IoT can enable a broad range of <a href="https://www.techtarget.com/iotagenda/tip/Considerations-for-selecting-rugged-devices-for-IoT">new IoT devices and services</a>. It reduces the power consumption of connected devices while increasing system capacity and bandwidth efficiency, particularly in locations that are not easily covered by traditional cellular technologies. NB-IoT-connected devices can have a battery life of more than 10 years for many use cases.</p> <section class="section main-article-chapter" data-menu-title="How does NB-IoT work?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How does NB-IoT work?</h2> <p>NB-IoT is a data transmission standard designed to enable devices to operate in mobile <a href="https://www.techtarget.com/whatis/definition/carrier-network">carrier networks</a>. It uses low-bandwidth signals to communicate within existing LTE and GSM technologies. The NB-IoT standard uses a small radio band of 180 kilohertz (kHz), specifically designed to support IoT use cases.</p> <p>Specially designed devices and sensors are also used as basic components in NB-IoT systems. These devices collect information from their surroundings and transmit it to NB-IoT <a href="https://www.techtarget.com/whatis/definition/base-station">base stations</a> or transmission nodes. Individual base stations are connected to an <a href="https://www.techtarget.com/iotagenda/definition/IoT-gateway">IoT gateway</a> and IoT cloud application servers for centralized monitoring and data analysis.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/bkq8Te4FnbI?si=S1cEwLFNMgX4O6wq?autoplay=0&amp;modestbranding=1&amp;rel=0&amp;widget_referrer=null&amp;enablejsapi=1&amp;origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0"></iframe> </div> <p>NB-IoT employs a new physical layer with signals and channels to meet the requirements of extended coverage in rural areas and deep indoors while enabling low device complexity. The underlying technology is much less complex than that of GSM/<a href="https://www.techtarget.com/searchmobilecomputing/definition/GPRS">General Packet Radio Services </a>modules.</p> <p>Supported by all major mobile equipment, chipset and module manufacturers, NB-IoT can exist along with second-generation wireless technology (2G), 3G, 4G, Long-Term Evolution-M (LTE-M) and 5G mobile networks.</p> </section> <section class="section main-article-chapter" data-menu-title="What are the benefits of NB-IoT?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What are the benefits of NB-IoT?</h2> <p>NB-IoT offers the following benefits:</p> <ul class="default-list"> <li><b>Bandwidth efficiency.</b> NB-IoT is designed with bandwidth efficiency in mind. It uses a small portion of the spectrum, meaning multiple NB-IoT networks can coexist in the same area without any interference.</li> <li><b>Coverage and connectivity.</b> NB-IoT can help support massive numbers of devices by establishing NB-IoT networks that can connect billions of nodes. Designed for extended coverage indoors, the devices' lower complexity provides long-range connectivity and communication.</li> <li><b>Low cost of devices.</b> Because it's easier to create devices with lower complexity, the devices cost significantly less.</li> <li><b>Low power consumption.</b> NB-IoT does not need to run a heavy operating system, such as Linux, or do a lot of signal processing, making it more power-efficient compared to other cellular technologies.</li> <li><b>Multiyear battery life. </b>The enhanced power consumption capability enables NB-IoT to support devices with multiyear battery lives.</li> <li><b>Security. </b>NB-IoT is secured using <a href="https://www.techtarget.com/searchsecurity/opinion/Understanding-the-importance-of-data-encryption">methods such as data encryption</a>, secure authentication and signaling protection</li> <li><b>Strong signals.</b> NB-IoT signal strengths are typically strong, designed to penetrate multiple layers of brick.</li> </ul> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/the_benefits_of_nb_iot-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/the_benefits_of_nb_iot-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/the_benefits_of_nb_iot-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/the_benefits_of_nb_iot-f.png 1280w" alt="An image showing the benefits of NB-IoT." height="202" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>NB-IoT offers numerous benefits for LPWAN applications. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="What are the challenges of NB-IoT?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What are the challenges of NB-IoT?</h2> <p>There are still a few barriers to using NB-IoT, however, including the following:</p> <ul class="default-list"> <li><b>High latency.</b> NB-IoT typically has high amounts of latency, making it less than ideal for any application that requires fast response times.</li> <li><b>Lack of redundancy.</b> NB-IoT networks typically have limited backup options if coverage is lost or the network experiences an outage. If a network outage happens unexpectedly, for example, NB-IoT device connections will be interrupted.</li> <li><b>Limited data transmission.</b> Voice or video transmission is not an option because NB-IoT can only transmit less than a kilobyte of data per day, which is about equal to a text message. The NB-IoT data upload rate is around 20 kilobits per second (Kbps) -- low compared to competing technologies. Its bandwidth is about 200 KHz.</li> <li><b>Limited device mobility.</b> NB-IoT devices remain connected within a finite environment and only to one network operator. This could mean limitations for uses such as <a href="https://www.techtarget.com/searchmobilecomputing/definition/wearable-technology">wearables</a> that leave specific perimeters. If a person with a wearable device, for example, enters another country, the device might not work if the operator does not have a local presence.</li> <li><b>Limited large data transfers.</b> NB-IoT has a slower data rate, so large quantities of data cannot be transferred quickly.</li> <li><b>Limited support for roaming. </b>Roaming enables LTE-M and NB-IoT users to connect to their IoT devices across countries and mobile networks. However, the network must be supported in each country through which a user plans to connect.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Examples of NB-IoT applications"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Examples of NB-IoT applications</h2> <p>NB-IoT can be used for the following applications:</p> <ul class="default-list"> <li><b>Energy savings.</b> Sensors can be used to save on devices that are often active, such as using automatic light-dimming motion sensors connected to an NB-IoT system in an office building.</li> <li><b>Healthcare.</b> In healthcare, NB-IoT can be useful for remote patient monitoring, asset tracking and environmental monitoring.</li> <li><b>Monitoring temperature levels or optimizing store layouts.</b> NB-IoT sensors can be used to monitor temperature for perishable goods or to optimize a store's layout to receive an ideal return on investment.</li> <li><b>Smart buildings.</b> NB‑IoT-connected sensors can send alerts to facilities managers regarding building maintenance issues. They can also be used for indoor temperature monitoring systems. NB‑IoT can be used to back up a building's <a href="https://www.techtarget.com/searchnetworking/definition/broadband">broadband</a> connection.</li> <li><b>Smart cities. </b>Through smart city deployments,<b> </b>NB‑IoT can help local governments control street lighting, determine when trash bins must be emptied, identify free parking spaces, monitor environmental conditions and survey road conditions.</li> <li><b>Smart farming.</b> NB‑IoT connectivity enables farmers and cities to capture data from environmental sensors containing NB‑IoT modules that can send alerts if anything unusual happens. These sensors can be used to monitor the temperature and humidity of the soil and track the attributes of land, pollution, noise and rain.</li> <li><b>Smart metering.</b> NB‑IoT works well for monitoring water and gas meters using regular and small data transmissions. Network coverage is a major problem in rolling out smart metering, as meters are often installed deep underground, in cellars or in remote rural areas. NB‑IoT coverage and penetration can address this issue.</li> <li><b>Supply chain management (SCM).</b> NB-IoT is a good fit for SCM, as its wide and consistent coverage can be used in various ways, including customer data management and inventory tracking.</li> <li><b>Tracking.</b> NB‑IoT provides a secure, inexpensive way to track people, animals and assets when continuous tracking is not necessary. NB-IoT is good for tracking objects that are not moving all the time.</li> <li><b>Water conservation. </b>NB-IoT water flow sensors can monitor water consumption in buildings.</li> </ul> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/iot-examples_of_nb_iot-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/iot-examples_of_nb_iot-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/iot-examples_of_nb_iot-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/iot-examples_of_nb_iot-f.png 1280w" alt="An illustration showing the uses of NB-IoT, including smart metering, smart appliances, smart cities and smart buildings." height="271" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>NB-IoT has several use cases, including smart metering, smart cities and buildings, agriculture, and smart appliances. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="NB-IoT versus other LPWANs"> <h2 class="section-title"><i class="icon" data-icon="1"></i>NB-IoT versus other LPWANs</h2> <p>NB-IoT is like several other LPWAN technologies in terms of purpose and implementation, including the following:</p> <h3>NB-IoT vs. LTE-M (Cat-M1)</h3> <p>NB-IoT and LTE-M, also called category M1 or Cat-M1, are the two major LPWAN technologies that support massive IoT deployments. While they are both 3GPP-standardized technologies, they address different types of use cases based on their strengths.</p> <p>NB-IoT supports ultra-low complexity devices with a narrow bandwidth of 180 kHz. Because of its narrow bandwidth, the data rate peaks at about 26 Kbps in downlink and approximately 66 Kbps for uplink. NB-IoT uses a subset of LTE's OFDM (Orthogonal Frequency Division Multiple Access) modulation/SC‑FDMA (Single Carrier Frequency Division Multiple Access) for downlink and uplink communications for connectivity versus LTE spread technology. NB-IoT can also be implemented in an LTE carrier's guard band.</p> <p>LTE-M, on the other hand, operates at 1.4 megahertz (<a href="https://www.techtarget.com/searchnetworking/definition/megahertz">MHz</a>) bandwidth with higher device complexity and at a greater cost than NB-IoT. However, with the wider bandwidth, LTE-M can achieve lower latency, data rates up to 1 megabit per second and more accurate device positioning capabilities. LTE-M also provides extended coverage and enables the reuse of the LTE installed base.</p> <p>LTE-M deployment can be done in-band within a standard LTE carrier or standalone in a dedicated spectrum. It uses the free LTE spread spectrum technology. Device manufacturers that want to deploy on current cellular networks can use LTE-M.</p> <p>NB-IoT is extremely flexible. It can operate in 2G, 3G, 4G and 5G bands, and it removes the need for a gateway, which ultimately saves money.</p> <p>NB-IoT and LTE-M devices can sleep for extended periods of time with extended discontinuous reception, a method used in mobile communication to conserve a mobile device's battery life. Both NB-IoT and LTE-M also support enhanced signal coverage per base station.</p> <p>LTE-M, however, is more expensive because several large carriers have patents on the underlying technologies, and LTE-M users pay royalties to these companies for their intellectual property.</p> <h3>NB-IoT vs. LoRa</h3> <p>Long-range (LoRa) WAN technology is a noncellular modulation <a href="https://www.techtarget.com/searchnetworking/answer/What-is-the-difference-between-LoRa-and-LoRaWAN">technology for LoRaWAN</a>, the standard protocol for WAN communications.</p> <p>LoRa is a low-power, long-range wireless communication protocol developed by the <a target="_blank" href="https://lora-alliance.org/about-lora-alliance/" rel="noopener">LoRa Alliance</a>, a nonprofit organization dedicated to standardizing LPWAN technologies as a secure, energy-efficient IoT standard.</p> <p>LoRa is a modulation technology for LoRaWAN, an LPWAN specification intended for long-range communications. LoRa and NB-IoT both operate within LPWAN technology.</p> <p>Although NB-IoT and LoRa are both LPWAN technologies created for low-power devices, NB-IoT -- depending on its configuration -- generally has a lower latency compared to LoRa. This is because of the higher device output power, which can offer higher data rates.</p> <p>NB-IoT operates in the licensed spectrum. However, it can be deployed in-band within a normal LTE carrier or standalone for deployments in a dedicated spectrum. Because the channel width is small, the NB-IoT signal can bury itself inside a larger LTE channel, replace a GSM channel or exist in the guard channels of regular LTE signals.</p> <p>LoRaWAN is a spread spectrum modulation technique designed to facilitate communication between low-power devices and IoT applications. The LoRa wireless system uses unlicensed frequencies available worldwide to communicate with a network. LoRaWAN also uses radio frequency bands between 433 MHz and 928 MHz. Its peak data rate is 50 Kbps per channel and has bandwidths of 125 kHz, 250 kHz and 500 kHz.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/iot-iot_application_considerations-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/iot-iot_application_considerations-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/iot-iot_application_considerations-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/iot-iot_application_considerations-f.png 1280w" alt="An image showing the factors for using the different LPWAN technologies." height="442" width="559"> <figcaption> <i class="icon pictures" data-icon="z"></i>When considering the type of IoT to use, compare factors such as data throughput, extended coverage, latency, mobility and deployment times. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <h3>Sigfox</h3> <p>Sigfox is a proprietary LPWAN that uses an unlicensed spectrum of 100 Hz channels ranging from 868 MHz to 915 MHz. The maximum data rate is 100-600 bits per second. It can only handle very small 12-byte uplink and 8-byte downlink communications.</p> <p>Sigfox is designed to support very small payloads and is ideal for very low-frequency sensors and static applications. It does not offer standardized roaming and only has minimal two‑way messaging. NB-IoT, comparatively, works off a licensed spectrum, is more expensive and is designed for larger payloads.</p> </section> <section class="section main-article-chapter" data-menu-title="The future of NB-IoT"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The future of NB-IoT</h2> <p>The future of NB-IoT as a technology is currently mixed. It has room to grow as it integrates with 5G systems, is deployed in smart cities and other applications, and fits with pushes for energy efficiency and environmental monitoring use cases.</p> <p>Although NB-IoT has been strongly adopted in regions like Europe and Asia, and particularly China, its adoption might be waning in other areas. U.S. operator AT&amp;T discontinued its NB-IoT network in the first quarter of 2025, in favor of its LTE-M network -- which provides more data capacity for fixed and mobile devices. However, other major providers in the U.S., like Verizon and T-Mobile, continue to support the technology, and China accounted for <a target="_blank" href="https://iot-analytics.com/lpwan-market/" rel="noopener">84%</a> of all NB-IoT connections globally in 2023.</p> <p><i>Despite its mixed potential future, NB-IoT still has many use cases. Learn how it is being used in large </i><a href="https://www.techtarget.com/iotagenda/feature/A-guide-to-networks-for-IoT-healthcare-devices"><i>healthcare applications</i></a><i>.</i></p> </section> Narrowband IoT (NB-IoT) is a wireless internet of things (IoT) standard that uses low-power wide area network (LPWAN) technology. https://cdn.ttgtmedia.com/visuals/digdeeper/2.jpg https://www.techtarget.com/whatis/definition/narrowband-IoT-NB-IoT Thu, 31 Jul 2025 10:26:00 GMT <p>The internet of things, or <a href="https://www.techtarget.com/iotagenda/definition/Internet-of-Things-IoT">IoT</a>, provides organizations with real-time data and business insights that, when acted upon, can improve processes and operations to be more accurate, efficient and safer. IT administrators, architects, developers and CIOs planning an IoT deployment must clearly understand what IoT is, how it works, its uses, requirements, tradeoffs and how to implement <a href="https://www.techtarget.com/iotagenda/definition/IoT-device">IoT devices</a> and infrastructure.</p> <section class="section main-article-chapter" data-menu-title="What is IoT and how does it work?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What is IoT and how does it work?</h2> <p>IoT is a network of dedicated devices -- called <i>things</i> -- designed to gather and exchange real-world data across networks. These devices work together to collect information, transmit it for processing and enable actions based on that data.</p> <p><a href="https://www.techtarget.com/whatis/feature/IoT-basics-A-guide-for-beginners">Key concepts of IoT</a> are as follows:</p> <ul class="default-list"> <li><b>Focus on real-world data.</b> Unlike static digital information -- such as documents and images -- IoT devices produce data reflecting physical conditions in real time, enabling businesses to learn what's happening and exercise dynamic control.</li> <li><b>Real-time operation.</b> IoT data must be delivered and processed without delay, making network bandwidth and connectivity crucial. Data usefulness is often measured in seconds, especially for medical monitoring and other such critical applications.</li> <li><b>Data purpose.</b> IoT projects are defined by their business objectives. Often, IoT data forms part of a control loop with cause-and-effect relationships. For example, a sensor detects an unlocked door, and an actuator allows remote locking.</li> <li><b>Scale and scope.</b> IoT deployments can involve hundreds to thousands of sensors collecting various parameters, such as temperature, pressure or location. These vast data collections often fuel big data initiatives, machine learning (ML) and AI projects.</li> </ul> <p>An IoT system includes four basic elements:</p> <ol class="default-list"> <li><b>Things.</b> Every IoT device -- a thing or <a href="https://www.techtarget.com/iotagenda/definition/smart-sensor">smart sensor</a> -- is a small, dedicated computer with embedded processors, firmware, limited memory and network connectivity. They collect specific physical data, transmit it using networks and typically operate on battery power with unique IP addresses.</li> <li><b>Connections.</b> Data travels through conventional IP-based networks (Ethernet, internet) using wireless interfaces (Wi-Fi, 5G). <a href="https://www.techtarget.com/iotagenda/definition/IoT-gateway">IoT gateways</a> collect and preprocess raw <a href="https://www.techtarget.com/iotagenda/definition/sensor-data">sensor data</a> through normalization and filtering.</li> <li><b>Back end.</b> The collected data moves to processing centers (corporate data centers or cloud infrastructure) where it's stored, processed and analyzed using computing clusters.</li> <li><b>Interface.</b> Although IoT enables automation beyond human capabilities, systems include human interfaces (alerts, dashboards, reports) that let operators monitor and control the IoT infrastructure. For example, a <a href="https://www.techtarget.com/iotagenda/definition/smart-home-or-building">smart home </a>needs an interface that lets the homeowner set the indoor temperature.</li> </ol> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/7CQftX_tBy0?autoplay=0&amp;modestbranding=1&amp;rel=0&amp;widget_referrer=null&amp;enablejsapi=1&amp;origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0"></iframe> </div> </section> <section class="section main-article-chapter" data-menu-title="What are the layers of an IoT architecture?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What are the layers of an IoT architecture?</h2> <p>Although the scope and detail of an IoT architectural plan can vary depending on the IoT initiative, leaders must consider how IoT will integrate into the current IT infrastructure.</p> <p>Depending on the specific model, an <a href="https://www.techtarget.com/iotagenda/tip/A-comprehensive-view-of-the-4-IoT-architecture-layers">IoT architecture can have up to seven major layers</a>. These layers are like the Open Systems Interconnection networking model in that they can be discussed from bottom to top.</p> <h3>1. Device layer</h3> <p>This layer includes the devices that convert the physical world into digital data and vice versa through actuators. Devices comprise sensors and actuators that can number hundreds of thousands for an IoT deployment. Each device connects to a network using either wired or, more commonly, wireless connections.</p> <h3>2. Network layer</h3> <p>The network layer connects IoT devices and transfers data and commands between devices and computing resources. It includes IoT and network gateways and can also incorporate data aggregation or preprocessing methods, such as edge computing, to minimize the amount of raw data exchanged across the network.</p> <h3>3. Edge processing (preprocessing) layer</h3> <p>Large IoT deployments can strain network capacity, and decision-making is often relevant at the edge. Therefore, edge computing is regularly used to collect and preprocess IoT device data, enabling certain compute and analytics operations to be performed locally for greater efficiency instead of sending all raw data back for centralized processing.</p> <h3>4. Data storage layer</h3> <p>IoT systems routinely generate massive amounts of raw data. Like other business data, this data becomes a business asset and is subject to storage, security and regulatory considerations, such as retention and proper use policies. The data storage layer manages IoT data's storage, protection, organization and access.</p> <h3>5. Computing layer</h3> <p>This layer handles the central processing in IoT deployments. It's where vital IoT data is collected, stored and used for business decisions. Some processing might happen at the edge, where data is first preprocessed, normalized and aggregated. However, more detailed analysis can also occur at the primary data center. Using edge computing to reduce data load enables centralized layers to decrease network traffic and data center resources to focus on more advanced applications.</p> <h3>6. Application layer</h3> <p>At the highest level, an application layer handles user interactions, such as device management or environment control. However, the application layer is mainly where a primary data center ingests data delivered from the computing layer and performs detailed analytics and reporting on the IoT data.</p> <h3>7. Business use layer</h3> <p>This isn't a technology layer but rather a business strategy stage where business leaders can review performance and assess the value of IoT outcomes to the business. This is where <a href="https://www.techtarget.com/iotagenda/tip/Top-8-IoT-design-principles-for-successful-product-creation">IoT system design</a> and use case must align with the larger business strategy.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/iota-iot_system.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/iota-iot_system_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/iota-iot_system_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/iota-iot_system.png 1280w" alt="IoT system diagram." height="374" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>An example of how an IoT system works, from collecting data to taking action. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <p>There are four major architectural issues to consider: infrastructure, security, integration, and analytics and reporting.</p> <h3>1. Infrastructure</h3> <p>The physical layer includes IoT devices, the network and computing resources used to process data. Infrastructure often covers sensor types, quantities, locations, power, network interfaces and configuration and management tools. Networks must account for bandwidth and latency to handle IoT device demands. Computing handles <a href="https://www.techtarget.com/iotagenda/definition/What-is-IoT-data-analytics">IoT data analytics</a> on the back end, and organizations might need to deploy new resources or use on-demand options, such as the public cloud.</p> <p>The infrastructure discussion also involves <a href="https://www.techtarget.com/iotagenda/tip/Top-12-most-commonly-used-IoT-protocols-and-standards">choosing IoT protocols</a> and available connectivity standards such as Bluetooth Low Energy (BLE), 5G, Wi-Fi, Zigbee, long-range WAN, <a href="https://www.techtarget.com/whatis/definition/narrowband-IoT-NB-IoT">narrowband IoT</a> and low-power wireless personal area networks.</p> <h3>2. Security</h3> <p><a href="https://www.techtarget.com/iotagenda/tip/Explore-the-relationship-between-IoT-governance-and-privacy">IoT data can be sensitive and confidential</a>, such as patient medical telemetry data. Transmitting such data over open networks can expose devices and information to snooping, theft and hacking. Organizations planning an IoT project must consider <a href="https://www.techtarget.com/iotagenda/definition/Internet-of-Things-privacy-IoT-privacy">IoT privacy</a> and the best methods to secure IoT devices and data both in transit and at rest. Encryption is a common approach to IoT data security.</p> <p>Additional measures should also be implemented on IoT devices to prevent hacking and malicious modifications to device configurations. Security involves a range of software tools and traditional security devices, such as firewalls and intrusion detection and prevention systems.</p> <h3>3. Integration</h3> <p>This involves making everything work together seamlessly, ensuring that devices, infrastructure and tools added for IoT can interoperate with an organization's existing systems and applications, such as systems management and ERP. Proper <a href="https://www.techtarget.com/iotagenda/definition/IoT-integration">IoT integration</a> requires careful planning, proof-of-principle testing and a well-researched selection of IoT tools and platforms like Apache Kafka or OpenRemote.</p> <h3>4. Analytics and reporting</h3> <p>The highest level of IoT architecture requires a clear understanding of how IoT data will be analyzed and used -- what the business aims to achieve with the IoT system. This is the application layer, which often includes analytical tools, AI and ML modeling and training engines, and data visualization or rendering tools. These tools can be obtained from third-party vendors or accessed through cloud providers where data is stored and processed. Note, though, that <a href="https://www.techtarget.com/iotagenda/tip/IoT-data-visualization-Tips-and-challenges">IoT data visualization comes with its own challenges</a>.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineImages/networking-iot_network_design-f.png"> <img data-src="https://www.techtarget.com/rms/onlineImages/networking-iot_network_design-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineImages/networking-iot_network_design-f_mobile.png 960w,https://www.techtarget.com/rms/onlineImages/networking-iot_network_design-f.png 1280w" alt="Diagram of IoT security architecture components." height="336" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>IoT architecture components include the network, communication bus and an analytics and aggregation platform. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="Business use cases for IoT"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Business use cases for IoT</h2> <p>The wide range of small and capable IoT devices has found significant business applications across most major consumer, industrial, medical and government sectors. <a href="https://www.techtarget.com/iotagenda/tip/Top-8-IoT-applications-and-examples-in-business">Consider some of the growing use cases</a> in six key industries.</p> <h3>1. Smart building automation</h3> <p><a href="https://www.techtarget.com/iotagenda/tip/IoT-in-construction-Use-cases-benefits-and-challenges">IoT devices appear in construction</a> and facilities for energy management, security and even some task automation:</p> <ul class="default-list"> <li>Thermostats and lighting can be scheduled and controlled through internet applications.</li> <li>Motion-activated sensors can trigger video and audio streams to homeowner smartphones.</li> <li>Water sensors can watch basements or equipment-sensitive areas for leaks.</li> <li>Smoke, fire and carbon dioxide detectors can report danger to users and first responders.</li> <li>IoT actuators can lock and unlock doors remotely.</li> </ul> <h3>2. Manufacturing</h3> <p>IoT devices have been broadly <a href="https://www.techtarget.com/iotagenda/tip/Examples-and-use-cases-of-IoT-in-manufacturing">adopted in all manufacturing and industrial settings</a>. Examples of industrial IoT (<a href="https://www.techtarget.com/iotagenda/definition/Industrial-Internet-of-Things-IIoT">IIoT</a>) include the following:</p> <ul class="default-list"> <li>IIoT tags can track, locate and inventory enterprise assets.</li> <li>IIoT devices can help monitor and optimize energy use, such as lowering lighting when human-occupied areas are idle or lowering temperature settings during off-hours.</li> <li>IIoT sensors and actuators can support process automation and optimization.</li> <li>IIoT devices can monitor all machine behaviors and parameters during regular operation, enabling ML algorithms to guide predictive maintenance to optimize process uptime.</li> </ul> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/iota-industry_iot_apps.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/iota-industry_iot_apps_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/iota-industry_iot_apps_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/iota-industry_iot_apps.png 1280w" alt="Diagram showing industrial IoT use cases." height="403" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>IIoT is used in many industries and sectors, including robotics, manufacturing and smart cities. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <h3>3. Public/safety</h3> <p>IoT sensors with cellular-class connectivity can operate collaboratively across metropolitan areas to serve a wide range of purposes:</p> <ul class="default-list"> <li>IoT devices can detect the presence of vehicle traffic, enabling cities to adjust street lighting on idle streets and off-hours.</li> <li>Crime prevention efforts might include camera-based surveillance, while connected audio detection can direct police to areas where gunfire is detected.</li> <li>Cameras can be used to determine and optimize traffic, while transponders and cameras can read license plates or toll boxes to direct toll collection and management.</li> <li>Interconnected parking systems enable cities to track parking spots and alert drivers to available spots through an app.</li> <li>Sensors can watch bridges and other structures for stress and problems, enabling early detection and remediation.</li> <li>Sensors can monitor water quality, enabling early detection of contaminants or pollutants.</li> </ul> <h3>4. Medical/health</h3> <p><a href="https://www.techtarget.com/iotagenda/tip/Top-9-applications-of-IoT-in-healthcare">IoT is present in remote patient telemetry</a> and other medical uses. Examples of the internet of medical things (<a href="https://www.techtarget.com/iotagenda/definition/IoMT-Internet-of-Medical-Things">IoMT</a>) include the following:</p> <ul class="default-list"> <li>IoMT exists in countless wireless, wearable devices, including blood pressure cuffs, heart rate monitors and glucometers. Devices can be tuned to track calorie expenditure against exercise goals and remind patients of appointments or medications.</li> <li>IoMT enables early-warning devices, such as fall detection pendants, that alert health providers and family members and even provide location information for potential issues.</li> <li>With IoMT's remote monitoring capabilities, health providers can track patient health and adherence to treatment plans and better correlate health issues with telemetry data.</li> <li>Hospitals can use IoMT to tag and track the real-time location of medical equipment, including defibrillators, nebulizers, oxygen and wheelchairs.</li> <li>IoMT in staff badges can help locate and direct medical staff more efficiently.</li> <li>IoMT can help control other equipment, such as pharmacy inventory systems, refrigerator temperatures and humidity and temperature control.</li> <li>IoMT hygiene-monitoring equipment can help ensure that medical environments are clean and reduce infection.</li> </ul> <h3>5. Retail</h3> <p>IoT and big data analytics have found extensive use in retail sales and physical store environments:</p> <ul class="default-list"> <li>IoT devices can tag every product, enabling automated inventory control, loss prevention and supply chain management (SCM) so that retailers can place orders based on sales and inventory levels.</li> <li>Cameras and other surveillance technologies can watch shopper activity and preferences, helping retail stores optimize layouts and organize related products to maximize sales.</li> <li>IoT devices can support touchless and scanless checkout and payment, such as near-field communication payment.</li> </ul> <h3>6. Fleet management</h3> <p>Logistics and transportation companies can use IoT to enhance fleet management by optimizing routes, increasing driver safety and lowering operational costs:</p> <ul class="default-list"> <li>GPS trackers can monitor vehicle locations to determine arrival times based on speed and prevailing traffic conditions.</li> <li>Fuel monitoring devices can track fuel usage and calculate efficiency.</li> <li>Vehicle monitoring devices can check for wear and diagnostic issues, helping schedule preventive maintenance and avoid vehicle downtime.</li> <li>Speed monitoring can help drivers comply with speed limits and improve driver safety.</li> </ul> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineImages/iotagenda-industry_iot_use_cases_for_distribution_and_automation-f.png"> <img data-src="https://www.techtarget.com/rms/onlineImages/iotagenda-industry_iot_use_cases_for_distribution_and_automation-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineImages/iotagenda-industry_iot_use_cases_for_distribution_and_automation-f_mobile.png 960w,https://www.techtarget.com/rms/onlineImages/iotagenda-industry_iot_use_cases_for_distribution_and_automation-f.png 1280w" alt="Chart depicting IoT use cases by industry." height="422" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>IoT can add business value to several industries, including construction, manufacturing, retail and transportation. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="What are the business benefits of implementing IoT?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What are the business benefits of implementing IoT?</h2> <p><a href="https://www.techtarget.com/iotagenda/tip/Top-advantages-and-disadvantages-of-IoT-in-business">Benefits of IoT implementation</a> can include the following advantages.</p> <h3>Data-driven decision-making</h3> <p>IoT offers immediate knowledge by measuring and reporting specific real-world conditions. Using modern tools, such as a thermostat in a building that measures current temperatures to control heating or cooling, real-world conditions can be examined and responded to instantly.</p> <p>Suppose a medical heart rate monitor detects an excessive heart rate. In that case, the patient can slow down, relax to lower the heart rate, take appropriate medication, contact their doctor for further guidance or even call for medical help.</p> <p>If a traffic monitoring system detects a backup on a major highway, it can update travel apps with current conditions and help commuters choose alternate routes to avoid congestion.</p> <h3>Long-term analytics</h3> <p>IoT's true power and benefits are the long-term insights it can offer business leaders.</p> <p>Think about the countless IoT sensors that can be placed on equipment, vehicles, buildings, factories, campuses and municipal areas, enabling better long-term insight through advanced analytics: the back-end computing processes capable of analyzing and correlating large amounts of unrelated data to answer business questions and make accurate predictions about future conditions.</p> <p>This can result in significantly improved operational efficiency and better resource management.</p> <h3>Natural relationship with ML and AI</h3> <p>The data collected and analyzed from <a href="https://www.techtarget.com/searchenterpriseai/tip/Integrating-IoT-and-machine-learning-Benefits-and-use-cases">IoT fleets can also be used to train ML models</a>, supporting the development of AI initiatives that gain a deep understanding of the data and its relationships.</p> <p>For example, sensors placed throughout a vehicle or industrial machine can be analyzed to identify operational and condition changes, which might indicate the need for maintenance or even predict a potential failure.</p> <p>Such insights enable a business to order parts, schedule maintenance or make proactive repairs while minimizing the disruption to normal operations.</p> <h3>Cost savings</h3> <p>All the benefits outlined here can potentially lead to cost savings through improved logistics, lower usage of resources such as fuel or electricity, more effective SCM and otherwise-unrecognized business opportunities.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/iota-advantages_and_disadvantages-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/iota-advantages_and_disadvantages-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/iota-advantages_and_disadvantages-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/iota-advantages_and_disadvantages-f.png 1280w" alt="Bullet list graphic comparing IoT pros and cons." height="271" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>IoT can provide valuable business insights, but deploying it can be costly and time-consuming. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="IoT services and business models"> <h2 class="section-title"><i class="icon" data-icon="1"></i>IoT services and business models</h2> <p>Setting up countless individual IoT devices can be overwhelming, but analyzing that data to extract valuable business insights can also pose challenges. As the IoT industry advances, the ecosystem is growing to support new implementations and <a href="https://www.techtarget.com/iotagenda/tip/Top-9-IoT-business-models">enable innovative business models</a>.</p> <p>One of the biggest challenges with IoT is getting it to function correctly. Infrastructure requirements can be extensive, security is often a concern, and network and processing loads can introduce additional complexity.</p> <p>IoT vendors are addressing these issues with a <a href="https://www.techtarget.com/iotagenda/feature/7-IoT-SaaS-platform-providers-help-streamline-adoption">growing number of SaaS platforms</a> designed to simplify IoT adoption and reduce the need for deep investments in gateways, edge computing and other IoT-specific components.</p> <p>IoT SaaS operates between IoT devices and the enterprise, handling many essential functions the enterprise would otherwise need to handle.</p> <p>For example, the SaaS manages routine infrastructure tasks, such as data security and reporting, but often includes advanced processing and computing, like analytics, with added support for ML. This eases the burden on the enterprise data center and IT team, letting the business focus on the generated analyses.</p> <p>IoT SaaS offerings have similar features, so carefully evaluate the pricing to choose the provider best suited to your organization's number of IoT devices, data volumes and analytical needs.</p> <p>Currently, there are dozens of IoT SaaS providers, and an internet search for IoT SaaS services reveals a wealth of specialized providers and tools, including the following:</p> <ul class="default-list"> <li>2Base Technologies IoT Development.</li> <li>AJProTech Solutions for IoT.</li> <li>AllGuard by GuardRFID.</li> <li>Apexon end-to-end IoT development services.</li> <li>Blues Inc.</li> <li>Brightware by Bright Machines.</li> <li>Canopy.</li> <li>Cheesecake Labs.</li> <li>EPAM Systems.</li> <li>Eviden.</li> <li>EY IoT Consulting Services.</li> <li>Fosfor Decision Cloud by LTIMindtree.</li> <li>Fujitsu Hyperconnected Industry Solutions.</li> <li>GE Vernova.</li> <li>Hitachi Digital Services.</li> <li>HPE.</li> <li>Innfini IoT Platform by Innovent.</li> <li>Intellias IoT services.</li> <li>Intersog IoT App Development.</li> <li>Intetics.</li> <li>IoT.nxt by Vodafone.</li> <li>MeShare IoT platform.</li> <li>Mutual Mobile (now Grid Dynamics).</li> <li>Saviant Consulting.</li> <li>ScienceSoft IoT services.</li> <li>Seasia Infotech IoT development services.</li> <li>ThoughtFocus Industry X.</li> <li>Toshiba IoT Solution Pack.</li> <li>UST.</li> <li>Volo custom IoT services.</li> <li>World Wide Technology IoT services.</li> <li>Zoi.</li> </ul> <p>IoT SaaS providers differ in size and capabilities, often serving specific industries, such as healthcare or manufacturing. It's essential to choose a provider that specializes in the target industry and can deliver the necessary services, scalability and reliability.</p> <p>As the IoT industry grows, businesses will discover that IoT tools and software are becoming more accessible in three main areas of the technology stack:</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineImages/iota-iot_saas_arch-f.png"> <img data-src="https://www.techtarget.com/rms/onlineImages/iota-iot_saas_arch-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineImages/iota-iot_saas_arch-f_mobile.png 960w,https://www.techtarget.com/rms/onlineImages/iota-iot_saas_arch-f.png 1280w" alt="IoT SaaS architecture diagram." height="385" width="559"> <figcaption> <i class="icon pictures" data-icon="z"></i>IoT SaaS providers offer platforms that service IoT architecture and processing needs. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <ol class="default-list"> <li><b>Devices and edge.</b> This lowest layer of the IoT stack includes IoT devices, OSes, edge management and security platforms, and data ingestion/preprocessing tools and platforms.</li> <li><b>Middleware. </b>The middle layer of the IoT stack includes a wide range of middleware and platforms, such as databases, message brokers, data ingestion and management tools, and more <a href="https://www.techtarget.com/iotagenda/tip/How-to-choose-the-right-IoT-platform-for-your-business">comprehensive IoT platforms</a> designed to reduce the infrastructure burden for businesses.</li> <li><b>Applications.</b> The highest layer of the IoT stack includes applications such as data access, processing (analysis), reporting and visualization tools that enable businesses to work with the collected IoT data.</li> </ol> <p>IoT is transforming business operations and enabling various new business models that will enable organizations to generate revenue from IoT projects and products. Companies are increasingly exploring ways to monetize and incorporate IoT data as new growth avenues and revenue streams.</p> <p>There are at least four types of business models that IoT can effectively support:</p> <ol class="default-list"> <li><b>Salable data.</b> The raw data gathered by IoT devices can readily be monetized. For example, the data collected by a personal fitness tracker or weight data gathered from IoT home scales might interest health insurance companies seeking to adjust premiums based on consumer fitness activity and physical state.</li> <li><b>B2B and B2C.</b> IoT is all about collecting and analyzing data, and such analytics can be used to identify and optimize brand loyalty or drive additional sales based on business needs or consumer activities identified by IoT devices.</li> <li><b>IoT platforms.</b> The data and analytics IoT yields can form the foundation of platforms that offer AI services -- Amazon's Alexa, for instance. Those platforms continue to learn and improve with a wealth of real-world IoT data, and third-party businesses can integrate the services offered for a fee.</li> <li><b>Pay-per-use.</b> IoT technologies readily facilitate businesses such as bicycle or scooter rentals. GPS can locate equipment, which users with corresponding apps can find, access, use and pay for automatically. IoT data can analyze utilization and maintenance patterns to optimize the business process.</li> </ol> </section> <section class="section main-article-chapter" data-menu-title="What are the requirements for implementing IoT?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What are the requirements for implementing IoT?</h2> <p>There is no universal approach to designing and implementing an IoT infrastructure. Still, a common set of considerations can help organizations ensure they cover all the bases to successfully build and deploy an IoT project. Below are some key implementation considerations.</p> <h3>Network connectivity</h3> <p><a href="https://www.techtarget.com/iotagenda/feature/What-is-IoT-connectivity">IoT devices have several connectivity options</a>, including hard-wired connections, Wi-Fi, Bluetooth, 4G and 5G. Although there's no requirement for all devices to use the same connection type, standardizing one can make device setup and <a href="https://www.techtarget.com/iotagenda/definition/What-is-IoT-monitoring">IoT monitoring</a> easier. Additionally, decide whether sensors (inputs) and actuators (outputs) should share the same network or use separate, segmented or isolated networks.</p> <h3>IoT hub</h3> <p>Simply transmitting all IoT data directly from devices to an analytics platform can result in disparate connections and poor performance. An intermediary platform, such as an IoT hub, can help organize, preprocess and encrypt data from devices across an area before forwarding it for analysis. If a remote facility is IoT-enabled, a hub might collect and preprocess that IoT data at the edge before sending it for further analysis.</p> <h3>Aggregation and analytics</h3> <p>Once the data is collected, it can be used to drive reporting systems and actuators or for deeper analysis, querying and other big data purposes. Choose software tools to process, analyze, visualize and enable ML. For example, <a href="https://www.techtarget.com/iotagenda/tip/How-to-select-the-right-IoT-database-architecture">select appropriate IoT database types</a> and architectures: SQL versus NoSQL, or static versus streaming. These tools might be deployed locally in data centers or accessed through SaaS platforms or cloud providers.</p> <h3>Device management and control</h3> <p>Use a software tool capable of reliably managing all IoT devices throughout the project's lifecycle. Look for high levels of automation and group/asset monitoring and management features to simplify configuration and minimize errors. IoT device patching and updates are becoming challenging, so organizations should focus on effective update and upgrade processes. Use a comprehensive device dashboard to monitor and control IoT device fleets with meaningful metrics.</p> <h3>Security</h3> <p>Every IoT device poses a potential security risk, so an IoT implementation must carefully consider IoT configuration and integration into existing security tools and platforms, such as intrusion detection and prevention systems and antimalware tools. Likewise, the data generated by IoT devices must be managed with data protection, compliance and retention requirements in mind.</p> <h3>Storage and computing infrastructure</h3> <p>Although much of the focus is on IoT devices and support, it's crucial to consider what happens to the massive amount of data generated by the IoT infrastructure. IoT data must be stored and then analyzed using significant computing resources.</p> <p>Sometimes, this involves terabytes, petabytes and even exabytes of data processed across dozens or hundreds of servers dedicated to big data computing. The storage and processing infrastructure can be local, but it is increasingly shifting to public cloud providers.</p> <h3>Iterate and optimize</h3> <p><a href="https://www.techtarget.com/iotagenda/tip/How-to-plan-a-successful-IoT-deployment">IoT deployment is an ongoing process</a>. Regular updates and patches, new devices and issue resolutions drive continuous evaluation and improvements. This can include adding new devices, increasing storage or network bandwidth and refining data management and retention strategies.</p> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading">Learn more about IoT</h3> <p><a href="https://www.techtarget.com/iotagenda/feature/IoT-and-digital-twins-How-they-work-together-with-examples">IoT and digital twins: How they work together, with examples</a><br>Discover how IoT and digital twins create virtual replicas of physical assets to revolutionize operational efficiency and decision-making processes.</p> <p><a href="https://www.techtarget.com/whatis/feature/Top-30-IoT-interview-questions-and-answers">Top IoT interview questions and answers</a><br>Prepare for your next IoT job interview with this guide to the most challenging questions and expert-crafted responses that will set you apart from other candidates.</p> <p><a href="https://www.techtarget.com/whatis/feature/6-best-IoT-conferences-and-events-to-attend">Best IoT conferences and events to attend</a><br>Expand your professional network and stay ahead of emerging IoT trends by attending these industry-leading conferences.</p> <p><a href="https://www.techtarget.com/whatis/feature/Top-18-IoT-blogs-to-follow">Top IoT blogs to follow</a><br>Stay at the cutting edge of IoT developments by following these influential blogs that deliver timely insights, technical deep-dives and industry analysis from recognized thought leaders.</p> <p><a href="https://www.techtarget.com/whatis/feature/11-top-IoT-online-courses-to-boost-your-career-free-and-paid">Top IoT online courses to boost your career (free and paid)</a><br>Accelerate your career growth in the IoT sector with these online courses that range from beginner fundamentals to advanced specializations for every budget.</p> </div> </div> </section> <section class="section main-article-chapter" data-menu-title="4 steps for IoT implementation"> <h2 class="section-title"><i class="icon" data-icon="1"></i>4 steps for IoT implementation</h2> <p>As mentioned above, implementing IoT involves many technical factors, such as choosing and deploying devices, ensuring network connectivity, developing analytical capabilities and computing power and establishing network and data security. However, all these factors pertain to the actual construction and operation of an IoT infrastructure.</p> <p>For many organizations, the initial questions are much simpler: Why take on an IoT project, and how do we begin? Start with these four steps:</p> <ol class="default-list"> <li><b>Begin with a clear strategy.</b> IoT initiatives can vary widely in purpose, capabilities and scope. Like any IT project, an <a href="https://www.techtarget.com/iotagenda/tip/How-to-build-a-successful-IoT-strategy">IoT initiative must start with a well-defined strategy</a> that outlines its purpose and explicitly states its goals. This initial plan should also highlight the project's intended value -- such as increased productivity or reduced costs through predictive maintenance -- to justify the necessary financial and intellectual investment. A <a href="https://www.techtarget.com/whatis/feature/Top-7-must-have-IoT-skills-to-boost-your-career">skills assessment</a> and cross-functional <a href="https://www.techtarget.com/iotagenda/tip/7-IoT-training-certifications-to-take-your-next-career-step">training roadmap</a> should be developed early to identify knowledge gaps and ensure team members have the specialized IoT expertise required for successful implementation.</li> <li><b>Consider the infrastructure. </b>With a strategy in mind, the business typically moves into a research and experimentation phase to identify IoT products, services and software. Project managers then carry out limited proof-of-concept projects to showcase the technology and improve its deployment and management approaches, such as those involving configuration and security. This is where a business can evaluate and address many implementation challenges, including IoT device firmware updates, IoT device and network security and IoT device power management.</li> <li><b>Consider how to use the data.</b> At the same time, analysts evaluate ways to use the resulting data and understand the tools and computing infrastructure needed to derive business intelligence from it. This might involve using limited data center resources for small-scale analytics, with an eye toward public cloud resources and services as the IoT project scales.</li> <li><b>Pick an approach.</b> A business can approach an IoT project in three ways:</li> </ol> <ul class="default-list"> <li><b>Experimental.</b> Assemble a limited or test platform and let business and technology leaders find value, similar to how a business might start its first test projects in a public cloud.</li> <li><b>Comprehensive and formal.</b> Employ a clear project blueprint, including goals and a project timeline.</li> <li><b>A full commitment to IoT across the organization.</b> Such an effort usually requires more expertise and confidence in IoT than others.</li> </ul> <p>Regardless of the specific approach, the key is to remain focused on IoT and its data's value to the business. Ultimately, an IoT implementation must address tangible business needs, and objective metrics can measure its success.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineImages/iota-iot_challenges-f.png"> <img data-src="https://www.techtarget.com/rms/onlineImages/iota-iot_challenges-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineImages/iota-iot_challenges-f_mobile.png 960w,https://www.techtarget.com/rms/onlineImages/iota-iot_challenges-f.png 1280w" alt="Table showing three steps of IoT deployment, connect, scale and innovate, with bulleted lists of the considerations involved in each." height="400" width="559"> <figcaption> <i class="icon pictures" data-icon="z"></i>A comprehensive IoT deployment strategy will help the organization avoid challenges during implementation. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="What are the risks and challenges of implementing IoT?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What are the risks and challenges of implementing IoT?</h2> <p>Although their risks are well understood, IoT devices' sheer volume and diversity require greater attention and control than a business might otherwise exercise. The following encompasses some of the most detrimental risks of IoT environments.</p> <h3>Poor project design</h3> <p>Although IoT devices readily adopt various standards like Wi-Fi or 5G, there are currently no major international standards guiding the design and implementation of IoT architectures, nor is there a widely accepted rulebook for approaching an IoT project. This provides significant flexibility in design but also opens the door to major flaws, vulnerabilities and oversights.</p> <p>IoT projects should be led by IT staff with IoT expertise, but that expertise is continually evolving. There is no substitute for careful, well-planned design and proven performance based on extensive testing and proof-of-concept projects.</p> <h3>Inability to discover all IoT devices</h3> <p>IoT tools and practices must be able to detect and configure all IoT devices in the environment. Undiscovered devices are unmanaged or orphaned, which might not provide valuable data and could serve as attack points for hackers to access the network. Administrators must be able to identify and manage all IoT devices on the network. Incompatible devices can be challenging to manage properly, if at all.</p> <h3>Weak or absent access control</h3> <p><a href="https://www.techtarget.com/iotagenda/definition/IoT-security-Internet-of-Things-security">IoT security</a> relies on robust protection through proper authentication and authorization for each device. Each device's unique identifier enhances this, but it remains crucial to configure each IoT device for least privilege or zero trust, granting access only to necessary network resources for IoT operation and data transfer.</p> <p>Enhance security by using strong passwords and enabling network encryption on all IoT devices. Default passwords must be changed, and all IoT middleware, platforms and applications should implement proper access control.</p> <h3>Lack of storage security</h3> <p>IoT generates vast amounts of raw data, a business asset that must be protected and monitored. Encryption is highly recommended for data in transit, whether from IoT devices or during processing, and at rest -- i.e., when stored on media.</p> <p>Additionally, data storage should follow data retention and appropriate use policies, ensuring only authorized users can access and use it for approved business purposes. Data should also be destroyed when its retention period expires or be stored securely in proper long-term archives.</p> <h3>Ignored or overlooked device updates</h3> <p>IoT devices often need regular software and firmware updates or patches. Ignoring or missing these updates can leave IoT devices vulnerable to hacking or unauthorized access. Therefore, it is essential to plan and implement update strategies when designing an IoT environment.</p> <p>Some devices can be difficult or impossible to update on-site -- often because of low-bandwidth network speeds -- and might even be hard to access or take offline. These factors are a key part of <a href="https://www.techtarget.com/iotagenda/definition/internet-of-things-device-management-IoT-device-management">IoT device management</a> and should be considered during the planning stage of an IoT project.</p> <h3>Poor or weak network security</h3> <p>IoT deployments can add thousands of devices to a LAN, each opening a potential access point for intrusion. Organizations often implement additional network-wide security measures for IoT, including intrusion detection and prevention systems, tightly controlled firewalls, strong data encryption and comprehensive antimalware tools. They might also opt to segment the IoT network from the rest of the IT network.</p> <h3>Lack of security policy or process</h3> <p>Policy and process are vital for proper network security. They represent the combination of tools and practices used to configure, monitor and enforce device security across the network. Adequate documentation, clear configuration guidelines and rapid reporting and response are all part of IoT and everyday network security. Successful IoT policies and processes are often the result of experience, but they should align with existing IT policies and processes.</p> <h3>Weak or inadequate device management</h3> <p>IoT devices aren't just a software issue; each one represents a physical device or endpoint that needs management and maintenance. Every IoT device must be procured, prepared, installed, connected, configured, managed, maintained, replaced or retired.</p> <p>Handling this for a few servers is one thing, but it's entirely different when dealing with hundreds, thousands or even tens of thousands of IoT devices. Issues like device failures, replacements, power support -- including battery replacements -- and the physical integrity of each device's installation require careful planning and staffing.</p> </section> <section class="section main-article-chapter" data-menu-title="IoT security and compliance"> <h2 class="section-title"><i class="icon" data-icon="1"></i>IoT security and compliance</h2> <p><a href="https://www.techtarget.com/iotagenda/tip/Internet-of-Things-IOT-Seven-enterprise-risks-to-consider">IoT deployments face unique security challenges</a> due to their scale and nature:</p> <ul class="default-list"> <li><b>Volume.</b> Tens or hundreds of thousands of devices create an enormous attack surface.</li> <li><b>Weak security features.</b> Many devices have inadequate security standards, including default or easily guessed passwords.</li> <li><b>Limited computing power.</b> Devices are designed for battery efficiency, making firmware updates difficult and time-consuming.</li> <li><b>Management complexity.</b> IoT requires specialized tools to discover, configure and monitor all devices.</li> <li><b>Network vulnerabilities.</b> Shared networks with regular computing devices increase threat exposure.</li> </ul> <p>Effective IoT security revolves around three fundamental issues:</p> <ol type="1" start="1" class="default-list"> <li><b>Design.</b> Select devices with strong security capabilities and plan their implementation from the beginning. Create separate, protected networks specifically for IoT devices.</li> <li><b>Process.</b> Implement tools and practices that properly configure every device, including regular firmware updates. Avoid orphaned devices requiring manual intervention.</li> <li><b>Diligence.</b> Use management tools to monitor configurations and security tools to detect intrusions or malware.</li> </ol> <figure class="main-article-image half-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/iota-iot_security_challenges.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/iota-iot_security_challenges_half_column_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/iota-iot_security_challenges_half_column_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/iota-iot_security_challenges.png 1280w" alt="List of four IoT security tips." height="298" width="279"> <figcaption> <i class="icon pictures" data-icon="z"></i>Major breaches over the years have forced organizations to put more emphasis on IoT security. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <p>Still, <a href="https://www.techtarget.com/iotagenda/tip/5-IoT-security-threats-to-prioritize">IoT devices face numerous security vulnerabilities</a>, including botnet attacks, weak DNS systems susceptible to malware, unauthorized network access and physical tampering. These threats directly affect organizational compliance; stolen patient data or ransomware attacks, for instance, can create regulatory nightmares and operational disruptions.</p> <p>The IoT landscape lacks universal security standards, forcing businesses to document their design decisions and align with existing IT best practices. Although selecting devices that follow established standards -- such as IPv6, BLE and Zigbee -- provides a foundation, these connectivity protocols alone can't ensure comprehensive security.</p> <p>Fortunately, industry organizations are developing more robust frameworks. The IEEE 2413-2019 standard offers a common architectural approach across multiple domains, while IEEE 802.15.4 defines critical physical and media access layers for wireless networks used in many IoT implementations. When properly implemented, these standards can significantly <a href="https://www.techtarget.com/searchcio/tip/IoT-compliance-standards-and-how-to-comply">strengthen compliance efforts</a>.</p> <p>Effective IoT security requires integration with existing IT compliance initiatives. This holistic approach addresses equipment selection, configuration management and personnel training, ensuring IoT devices receive the same security oversight as other enterprise systems.</p> <p>Organizations must update business guidelines to <a href="https://www.techtarget.com/iotagenda/tip/Best-practices-for-IoT-data-management">incorporate IoT data management</a> and security protocols, treating connected devices as full members of the enterprise technology ecosystem, requiring appropriate protection and monitoring.</p> </section> <section class="section main-article-chapter" data-menu-title="What is the future of IoT in the enterprise?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What is the future of IoT in the enterprise?</h2> <p>The future of IoT remains hard to predict because the technology and its applications are still relatively new and have great growth potential. New IoT applications and use cases are continuing to emerge. By about 2030, it's expected that there will be over 25 billion IoT devices in use, with 75% of all devices anticipated to be IoT-connected or IoT-capable by then.</p> <p>When it comes to enterprise IoT, there are several <a href="https://www.techtarget.com/iotagenda/opinion/IoT-trends-to-keep-an-eye-on">important trends to watch</a>.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-1" src="https://www.youtube.com/embed/mLg95dLm-Gs?autoplay=0&amp;modestbranding=1&amp;rel=0&amp;widget_referrer=null&amp;enablejsapi=1&amp;origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0"></iframe> </div> <h3>Advanced connectivity evolution</h3> <p>As IoT devices grow more numerous and sophisticated, the demand for increased network bandwidth will promote widespread adoption of advanced connectivity like 5G and upcoming standards. 5G technologies offer lower latency, network sharing, real-time data processing and dependable coverage across large geographic regions.</p> <h3>Enhanced security frameworks</h3> <p>In the coming years, we will likely see a reevaluation and dramatic increase in IoT security, beginning with initial IoT device design and extending through business selection and implementation. Future devices will include stronger security features enabled by default, not disabled or optional. A combination of new legislation, regulatory pressures and device defaults will reinforce end-to-end IoT data encryption.</p> <h3>AI and IoT convergence</h3> <p>Some aspects of <a href="https://www.techtarget.com/iotagenda/tip/AI-and-IoT-How-do-the-internet-of-things-and-AI-work-together">AI and IoT are merging</a> to create a hybrid <a href="https://www.techtarget.com/iotagenda/definition/Artificial-Intelligence-of-Things-AIoT">artificial intelligence of things</a> technology that aims to combine <a href="https://www.techtarget.com/iotagenda/tip/How-IoT-data-collection-works">IoT data collection</a> with the computing power and continually evolving decision-making skills of ML and AI. AI applications for IoT will continue to grow, from predicting system failures to providing real-time support and improving autonomous operations.</p> <h3>Edge computing expansion</h3> <p><a href="https://www.techtarget.com/iotagenda/tip/IoT-data-storage-Top-technologies-and-challenges-explained">IoT data storage</a> and processing at the edge will become more important as the number of IoT devices and data volumes places even greater pressure on network bandwidth and latency. This will continue to shift more IoT computing work from centralized infrastructures to distributed/edge computing.</p> <h3>Data-driven business opportunities</h3> <p>IoT data volumes will continue to swell and translate into new revenue opportunities for businesses, such as finding purchasing trends or optimizing supply chains. That data will increasingly drive ML and AI initiatives across many industries, from science to transportation to finance to retail.</p> <h3>Market maturation and simplification</h3> <p>The IoT marketplace will continue to grow and mature as vendors seek to offer platforms and services across the IoT stack. Market maturity will help speed the creation of new IoT deployments by removing complexity and making the design and deployment process more turnkey for businesses.</p> <p><i>Stephen J. Bigelow, senior technology editor at TechTarget, has more than 30 years of technical writing experience in the PC and technology industry.</i></p> </section> IoT implementation involves many considerations, including security, network connectivity, data aggregation, and analytics and device management and control. https://cdn.ttgtmedia.com/visuals/digdeeper/6.jpg https://www.techtarget.com/iotagenda/Ultimate-IoT-implementation-guide-for-businesses Thu, 31 Jul 2025 00:00:00 GMT <p>Privacy protection is one of the most critical elements within IoT governance. With <a href="https://www.techtarget.com/iotagenda/definition/IoT-device">IoT devices</a> continuously collecting vast amounts of personal and sensitive data, privacy considerations must be embedded in an organization's governance structures rather than treated as an afterthought. "Privacy first" should be the message to all who engage in business or personal use with IoT devices. Therefore, IoT governance should become the directive to protect privacy.</p> <section class="section main-article-chapter" data-menu-title="IoT governance and privacy are interconnected"> <h2 class="section-title"><i class="icon" data-icon="1"></i>IoT governance and privacy are interconnected</h2> <p>IoT devices provide quick and seamless <a href="https://www.techtarget.com/iotagenda/feature/What-is-IoT-connectivity">connectivity to other IoT devices</a> through the cloud, Wi-Fi or Bluetooth. However, the data transmitted, stored and analyzed by these devices can reveal personally identifiable information -- such as medical, financial and banking data, along with passport, credit card and social security numbers -- that is highly sought after by cybercriminals. <a href="https://www.techtarget.com/iotagenda/definition/Internet-of-Things-privacy-IoT-privacy">IoT privacy</a> protects user data in highly connected IoT environments, enhancing IoT user confidence that the data passing through IoT devices and the networks they use is protected from cybercriminals, as well as from broadcast and manipulation by AI technologies.</p> <p>IoT governance focuses on IoT devices and applications, emphasizing data assets as a crucial element in IoT devices. In addition to <a href="https://www.techtarget.com/iotagenda/tip/Internet-of-Things-IOT-Seven-enterprise-risks-to-consider">managing IoT device security risks</a>, identifying vulnerabilities and stopping potential data breaches, IoT governance establishes the rules, procedures, frameworks, laws and standards for how personal data is handled, and it defines what <a href="https://www.techtarget.com/iotagenda/tip/How-IoT-data-collection-works">data should be collected</a>, how the data should be processed, who has access to this privileged data and why the data is being stored.</p> </section> <section class="section main-article-chapter" data-menu-title="Standards and laws related to IoT governance"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Standards and laws related to IoT governance</h2> <p>According to Statista, the number of IoT devices worldwide is expected to grow from 19.8 billion in 2025 to 40.6 billion by 2034. This proliferation of connected devices has brought about new concerns regarding inadequate data privacy protections when storing or transmitting personal information over IoT devices, as well as security standards, procedures, policies and frameworks that weren't adequately addressed in the development of previous technologies. These concerns have led to the creation of standards and laws that focus on improving IoT cybersecurity resilience and privacy.</p> <h3>ISO/IEC standards</h3> <p>Examples of standards developed by the International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC) include the following:</p> <ul class="default-list"> <li><b>ISO/IEC 27400:2022. </b>The IoT security and privacy standard addresses cybersecurity and privacy of IoT systems.</li> <li><b>ISO/IEC 30141:2024. </b>The IoT reference architecture standard establishes a common framework for IoT systems to define a generic IoT conceptual model and <a href="https://www.techtarget.com/iotagenda/tip/A-comprehensive-view-of-the-4-IoT-architecture-layers">architectural views</a>.</li> <li><b>ISO/IEC 30162:2022. </b>The industrial IoT compatibility standard focuses on device models and requirements used in <a href="https://www.techtarget.com/iotagenda/definition/Industrial-Internet-of-Things-IIoT">industrial IoT</a> systems.</li> </ul> <h3>IEEE standards</h3> <p>Examples of IEEE standards associated with IoT technology include the following:</p> <ul class="default-list"> <li><b>IEEE 2413-2019.</b> This standard describes an architectural framework for IoT sectors and highlights shared characteristics. It also offers a strategy for implementing IEEE standards in IoT.</li> <li><b>IEEE networking protocols.</b> The following <a href="https://www.techtarget.com/iotagenda/tip/Top-12-most-commonly-used-IoT-protocols-and-standards">protocols are applicable to IoT</a>: <ul style="list-style-type: circle;" class="default-list"> <li><b>802.1.</b> The 802.1 Working Group recommends and develops standards in IEEE 802 LAN and metropolitan area network (MAN) architecture; internetworking among LANS, MANs and WANs; security; network management; and protocol layers in the network layer and above.</li> <li><b>802.3.</b> <a href="https://www.techtarget.com/searchnetworking/definition/8023">IEEE 802.3</a> describes the standards for Ethernet wired networking technology used in IoT devices.</li> <li><b>802.11.</b> This standard is the basis for the <a href="https://www.techtarget.com/searchmobilecomputing/definition/Wi-Fi">Wi-Fi</a> technology used by IoT devices.</li> <li><b>802.15.</b> The 802.15 Working Group "focuses on the development of open consensus standards addressing wireless networking for the emerging Internet of Things (IoT), allowing these devices to communicate and interoperate with one another …."</li> </ul> </li> </ul> <h3>NIST and IEC standards</h3> <p>Examples of standards and guidelines offered by NIST, NIST interagency reports (NISTI) and the International Electrotechnical Commission (IEC) regarding security, reliability and interoperability include the following:</p> <ul class="default-list"> <li><b>NIST SP 800-213 series</b>. This NIST set of standards provides guidance regarding the deployment of IoT devices in federal government agency systems.</li> <li><b>NISTIR 8259 series</b>. NISTIR 8259A and NISTIR 8259B offer guidance and recommendations for IoT manufacturers and their third-party providers. NISTIR 8259C, still in draft format, discusses cybersecurity requirements for IoT systems.</li> <li><b>ISA/IEC 62443.</b> This set of standards defines requirements to improve cybersecurity for industrial automation and control systems.</li> <li><b>ISO/IEC TS 30149:2024.</b> This standard describes trustworthiness principles for IoT systems.</li> <li><b>ISO/IEC 27402:2023.</b> This standard specifies device baseline requirements for IoT security and privacy in IoT devices.</li> </ul> <h3>U.S., EU and U.K. IoT laws and regulations</h3> <p>The following laws and regulations from the U.S., EU and U.K. are some examples of the legislation being implemented around the world regarding IoT cybersecurity governance and IoT privacy.</p> <p><b>United States</b></p> <ul class="default-list"> <li><b>IoT Cybersecurity Improvement Act of 2020.</b> Focusing on the appropriate use and management of IoT devices, this bill mandates NIST to create IoT cybersecurity standards for federal agencies and to update them every five years. The Office of Management and Budget (OMB) must align agency policies with NIST guidelines and oversee vulnerability communications.</li> <li><b>U.S. Cyber Trust Mark.</b> Created by the Federal Communications Commission (FCC), this voluntary cybersecurity labeling program for wireless consumer IoT products will help buyers identify trustworthy smart products.</li> <li><b>California's IoT Security Law. </b>Also known as<b> </b><a target="_blank" href="https://leginfo.legislature.ca.gov/faces/billNavClient.xhtml?bill_id=201720180SB327" rel="noopener">SB-327</a>, this law requires manufacturers of connected devices to include reasonable security features to protect against unauthorized access and data breaches.</li> </ul> <p><b>European Union</b></p> <ul class="default-list"> <li><b>Cyber Resilience Act. </b>The CRA makes digital products in the EU more secure by holding manufacturers accountable for software updates and enhancing consumer awareness about cybersecurity before and during their purchases. Full enforcement is slated for December 11, 2027.</li> </ul> <p><b>United Kingdom</b></p> <ul class="default-list"> <li><b>Product Security and Telecommunications Infrastructure Act. </b>The PSTI Act requires manufacturers, importers and distributors of consumer connectable products -- i.e., smart products -- in the U.K. to appoint an authorized representative who will comply with specific duties and ensure relevant products are accompanied by a statement of compliance as outlined in the regulations. Examples of covered duties include regulations around passwords and information on minimum security updates.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="The future of IoT governance"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The future of IoT governance</h2> <p>IoT governance provides the structural foundation to develop a systematic privacy protection program that is integrated with IoT environments and IoT devices. This will necessitate the following:</p> <ul class="default-list"> <li>Greater privacy in IoT devices, data, data storage and analysis.</li> <li>Faster internet connectivity.</li> <li>Better, more encompassing IoT governance.</li> </ul> <p>Successful IoT governance combines privacy requirements with foundational business operations to protect human interactions, user data and operational data when using IoT devices. This includes the following actions:</p> <ul class="default-list"> <li>Identify the need for additional IoT governance regulations, and enforce policies, standards and frameworks for data privacy, data access and data storage.</li> <li>Regulate cybersecurity and privacy technologies for <a href="https://www.techtarget.com/iotagenda/tip/AI-and-IoT-How-do-the-internet-of-things-and-AI-work-together">AI automation and IoT devices</a>.</li> <li>Focus on <a href="https://www.techtarget.com/searchsecurity/feature/How-to-implement-zero-trust-security-from-people-who-did-it">zero trust</a>, zero-trust architecture, AI and edge computing for businesses and governments as a security solution for privacy and access control.</li> <li>Address new AI automation tools, software, as well as <a href="https://www.techtarget.com/searchnetworking/Enterprise-5G-Guide-to-planning-architecture-and-benefits">5G</a> and <a href="https://www.techtarget.com/searchnetworking/definition/6G">6G</a> technologies for data sharing.</li> <li>Develop additional sector-specific IoT governance for privacy.</li> </ul> <p>IoT governance and privacy responsibilities are distributed across multiple stakeholders in an organization, such as the chief strategy officer, chief information security officer, chief privacy officer and the CTO.</p> <p>Noncompliance with IoT governance and privacy regulations can result in financial repercussions such as hefty fines and legal expenses from privacy breaches. In addition, companies might face device inoperability, service interruptions, data loss, increased vulnerability to cyberattacks and damage to their reputation.</p> <p><b>Editor's note:</b> <i>This article was updated in July 2025 to include additional IoT laws and regulations and to improve the reader experience.</i></p> <p><i>Dr. Diane Groth is the owner of Laetare Cybersecurity LLC, based in Baltimore. Her career has been in the field of security, with career assignments including positions as a network security engineer, systems security engineer, cybersecurity scientist and cybersecurity engineer.</i></p> </section> Emerging industry standards and regulations -- coupled with technologies like AI -- will underscore the importance of IoT governance and privacy in the years to come. https://cdn.ttgtmedia.com/rms/onlineimages/iot_g1182604383.jpg https://www.techtarget.com/iotagenda/tip/Explore-the-relationship-between-IoT-governance-and-privacy Wed, 30 Jul 2025 12:20:00 GMT <p>An IoT gateway is a physical device or software program that serves as the connection point between the cloud and <a href="https://www.techtarget.com/iotagenda/definition/Internet-of-Things-IoT">internet of things</a> devices, such as <a href="https://www.techtarget.com/whatis/definition/controller">controllers</a>, sensors and smart devices.</p> <p>IoT is used in enterprises and industries and can be found in consumer products. IoT <a href="https://www.techtarget.com/iotagenda/definition/gateway">gateways</a> act as a central hub, connecting <a href="https://www.techtarget.com/iotagenda/definition/IoT-device">IoT devices</a> to the cloud. Organizations can use gateways to connect IoT devices for data processing and to monitor and manage IoT devices.</p> <p>All data moving between IoT-connected devices and the cloud passes through an IoT gateway, which can be either a dedicated hardware appliance or an application. An IoT gateway might also be referred to as an <i>intelligent gateway</i> or <i>control tier</i>.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/iota-iot_gateway.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/iota-iot_gateway_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/iota-iot_gateway_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/iota-iot_gateway.png 1280w" alt="A diagram showing how IoT gateways facilitate the distribution of data between IoT devices and the cloud."> <figcaption> <i class="icon pictures" data-icon="z"></i>Gateways can be used to create a communication link between an IoT environment and the cloud. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <p>While IoT gateways enable communication between IoT devices and systems, they can also reduce latency and facilitate IoT deployments at scale.</p> <section class="section main-article-chapter" data-menu-title="What does an IoT gateway do?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What does an IoT gateway do?</h2> <p>An IoT gateway acts as a network router, routing data between IoT devices and the cloud. Early on, most gateway devices only sent traffic in one direction: from the IoT device to the cloud. Now, it is common for gateway devices to handle both inbound and outbound traffic. Outbound traffic streams are used to send IoT data to the cloud, while inbound traffic is used for device management tasks, such as updating <a href="https://www.techtarget.com/whatis/definition/firmware">firmware</a>.</p> <p>Some IoT gateways do more than route traffic. They can also preprocess data locally at the edge before sending it to the cloud. In doing so, the device might deduplicate, summarize or aggregate data to reduce the volume of data that is then forwarded to the cloud. This can improve response times and reduce network transmission costs.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/bkq8Te4FnbI?autoplay=0&amp;modestbranding=1&amp;rel=0&amp;widget_referrer=null&amp;enablejsapi=1&amp;origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0"></iframe> </div> <p>IoT gateways include the following potential applications:</p> <ul class="default-list"> <li><b>Improve security.</b> IoT gateways act as a point where security measures, such as device authentication and intrusion detection, can be applied.</li> <li><b>Manage devices.</b> IoT gateways act as touchpoints that enable device management and configurations.</li> <li><b>Support</b><b> edge computing.</b> IoT gateways support the preprocessing of data before it is sent to the cloud.</li> <li><b>Translate protocols.</b> IoT gateways convert different communication protocols used by separate IoT devices.</li> <li><b>Support industry-specific applications. </b>These include the following applications and vertical markets: <ul style="list-style-type: circle;" class="default-list"> <li>Smart homes.</li> <li>Industrial automation.</li> <li>Healthcare.</li> <li>Agriculture.</li> <li>Transportation.</li> </ul> </li> </ul> </section> <section class="section main-article-chapter" data-menu-title="How does an IoT gateway work?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How does an IoT gateway work?</h2> <p>A simple IoT gateway functions like a Wi-Fi router. An IoT system connects to the gateway using a Wi-Fi connection, and the gateway routes the IoT device data to the cloud. More often, though, IoT gateways are far more complex.</p> <p>Still, the simplified process of IoT data traveling across an IoT gateway looks like the following:</p> <ol class="default-list"> <li>The IoT gateway receives data from a network of sensors.</li> <li>It preprocesses the data.</li> <li>That data is then converted from the device-specific format to a standardized communication protocol.</li> <li>The processed and converted data is sent to the cloud platform.</li> </ol> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/whatis-edge_device.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/whatis-edge_device_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/whatis-edge_device_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/whatis-edge_device.png 1280w" alt="How IoT gateways connect devices to the cloud." height="358" width="559"> <figcaption> <i class="icon pictures" data-icon="z"></i>An IoT gateway collects data from multiple IoT devices, such as sensors or actuators; performs preprocessing and protocol translation; and then sends the processed data to the cloud. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <p>IoT architecture is divided into four layers:</p> <ol class="default-list"> <li>The <b>sensor layer</b> is where IoT devices operate.</li> <li>The <b>network or data acquisition layer</b> is where data is aggregated from multiple sources and is securely sent to processing systems.</li> <li>The <b>data preprocessing layer</b> is where basic data analytics are done to reduce data volume.</li> <li>The <b>cloud analysis or application layer</b> is where more in-depth data analytics is performed.</li> </ol> <p>One reason why an IoT gateway tends to be more complex than a Wi-Fi router is that IoT devices use <a href="https://www.techtarget.com/iotagenda/tip/Top-12-most-commonly-used-IoT-protocols-and-standards">several different protocols</a>. These protocols include Z-Wave, BACnet, Bluetooth Low Energy and Zigbee. As such, an IoT gateway might need to support a variety of protocols to service all the IoT devices in an organization.</p> <p>In addition to supporting these protocols, the gateway must be able to route each type of IoT traffic to the appropriate destination. Data from a collection of industrial sensors might need to be sent to a database in the Amazon Web Services cloud, whereas data from building security sensors might need to be <a href="https://www.techtarget.com/iotagenda/feature/7-IoT-SaaS-platform-providers-help-streamline-adoption">directed to a software-as-a-service vendor</a> that operates a cloud-based security portal.</p> <p>Another reason why IoT gateways can be more complex than Wi-Fi routers is that IoT gateways <a href="https://www.techtarget.com/searchstorage/tip/Get-the-most-out-of-cloud-caching-appliances-and-gateways">might need to cache data locally</a> in case internet connectivity fails or the gateway is flooded with more data than it can handle.</p> <p>Additionally, IoT gateways often support <a href="https://www.techtarget.com/searchwindowsserver/definition/failover-cluster">failover clustering</a>, or the ability to scale out to support increasingly large workloads.</p> </section> <section class="section main-article-chapter" data-menu-title="Types of IoT gateways"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Types of IoT gateways</h2> <p>IoT gateways can be used in the following ways, based on their communication technologies, intended use and features:</p> <ul class="default-list"> <li><b>Industrial gateways. </b>These IoT gateways are used in harsh industrial settings for connecting sensors, machines and other devices to data servers or the cloud.</li> <li><b>LoRaWAN.</b> These IoT gateways are used in LoRaWAN networks to transfer long‑range and low-power radio messages from remote sensors to a network server.</li> <li><b>Cellular. </b>These gateways use LTE (Long-Term Evolution), 4G and 5G in wide‑area carrier environments, connecting to two different internet service providers.</li> <li><b>Edge computing.</b> These gateways perform local data processing, which can help organizations reduce latency and <a href="https://www.techtarget.com/searchnetworking/definition/bandwidth">bandwidth</a> usage.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Benefits and challenges of IoT gateways"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Benefits and challenges of IoT gateways</h2> <p>IoT gateways provide the following benefits:</p> <ul class="default-list"> <li><b>Cost.</b> IoT gateways can help reduce operational costs by processing data closer to the edge and reducing requirements for data transmissions.</li> <li><b>Data and device management.</b> Data processed and translated at the edge means less processing needs to be done on it in the cloud, and IoT devices can have data transferred to it, meaning they can be managed and updated as needed.</li> <li><b>Protocol handling.</b> IoT gateways can translate between different communication protocols, enabling devices with different protocols to be used.</li> <li><b>Preprocessing.</b> Data can be processed closer to the edge before it is sent to the cloud.</li> </ul> <p>IoT gateways also come with the following challenges, which can complicate their adoption:</p> <ul class="default-list"> <li><b>Production of large amounts of data by some IoT devices.</b> This can be a problem if an organization has a significant number of devices in its IoT ecosystem and tries to send the data from all those devices to the cloud. The IoT devices could potentially deplete the organization's available internet bandwidth, while also incurring large cloud storage costs.</li> <li><b>Attack surface risks.</b> IoT also comes with some security risks, as it increases an organization's <a href="https://www.techtarget.com/whatis/definition/attack-surface">attack surface</a>.</li> <li><b>Security.</b> Although they are improving, IoT devices can be insecure. According to the "2025 SonicWall Cyber Threat Report," IoT security breaches <a href="https://www.sonicwall.com/threat-report" target="_blank" rel="noopener">increased</a> by 124% in 2024 compared to 2023.</li> <li><b>Compatibility.</b> Organizations should make sure the IoT gateway supports translating the correct protocols used by their IoT devices.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="How to improve IoT gateway security"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How to improve IoT gateway security</h2> <p>One way to avoid the problems associated with the amount of data IoT devices produce is to use edge computing for some of the required data processing. This approach minimizes the volume of data that must be sent to the cloud, thereby reducing both costs and bandwidth consumption.</p> <p>Imagine that an organization has a collection of IP-enabled security cameras, all streaming real-time data. It doesn't make sense to send all the raw security footage to the cloud for data processing, especially if some of the cameras primarily monitor unoccupied areas.</p> <p>Rather than uploading all security footage in real time, it is more efficient to process the video footage at the edge. The edge device can differentiate between security footage that isn't important, such as video of an empty room, and footage that the organization deems worthy of retention. The edge device can take the footage that must be reviewed and send it to a gateway device, which uploads the data to the cloud.</p> <p>Processing IoT data on edge devices -- the same process that reduces the volume of data sent to the cloud -- also means the amount of data sent through the gateway is limited. This helps to reduce attack surfaces, thereby helping to improve security.</p> <p>IoT gateways should sit between IoT devices and the internet and have integrated security functions. These functions, such as tamper detection, <a href="https://www.techtarget.com/searchsecurity/definition/encryption">encryption</a> and hardware random number generation, should protect the IoT devices from being attacked. For example, unidirectional gateways can protect legacy devices that cannot be secured remotely by only allowing data to move in one direction. Likewise, gateway filtering technology can monitor, manage and secure data transfers through authenticated traffic using <a href="https://www.techtarget.com/searchnetworking/definition/packet-filtering">packet filtering</a> or physical network signal filtering.</p> <p>To further improve IoT gateway security, organizations can do the following:</p> <ul class="default-list"> <li>Use only authenticated IoT gateways.</li> <li>Perform security assessments before implementation.</li> <li>Keep gateway software current.</li> <li>Regularly review gateway access.</li> <li>Include gateways in security audits.</li> <li>Use a separate network for IoT gateways and devices.</li> </ul> <p><em>IoT gateways are important for managing and <a href="https://www.techtarget.com/iotagenda/post/How-to-secure-IoT-devices-and-protect-them-from-cyber-attacks">securing IoT devices</a>. They might also help an organization reduce its IoT-related internet bandwidth consumption.</em></p> </section> An IoT gateway is a physical device or software program that serves as the connection point between the cloud and internet of things devices, such as controllers, sensors and smart devices. https://cdn.ttgtmedia.com/visuals/digdeeper/3.jpg https://www.techtarget.com/iotagenda/definition/IoT-gateway Tue, 29 Jul 2025 09:00:00 GMT <p>The world now has twice as many connected devices as humans, and the number of <a href="https://www.techtarget.com/iotagenda/definition/Internet-of-Things-IoT">IoT</a>-enabled endpoints is expected to climb even more exponentially in the years ahead.</p> <p>In a May 2025 report, German data collection and visualization firm Statista put the number of IoT devices worldwide at 19.8 billion in 2025 and predicted it would hit 40.6 billion by 2034.</p> <p>Those IoT connections span the globe and permeate nearly all places: homes, offices, factories, farms, vehicles and even space. The multitude of uses for <a href="https://www.techtarget.com/iotagenda/definition/IoT-device">IoT devices</a> -- and the benefits derived from using the data generated by those devices -- is driving significant investment in the technology.</p> <p>GlobalData, a data and analytics company, predicted in a March 2025 report that the global IoT market would grow at a compound annual growth rate (CAGR) of 13.5% from $959.6 billion in revenue in 2023 to $1.8 trillion in revenue in 2028. "This growth is driven by the rise of enterprise applications, enhanced by new technologies like 5G and AI," researchers wrote.</p> <p>According to GlobalData, enterprise IoT will account for 72% of market revenue by 2028, up from 70% in 2023, while the consumer segment will make up 28% in 2028, down from 30% in 2023.</p> <section class="section main-article-chapter" data-menu-title="Top IoT applications and examples"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Top IoT applications and examples</h2> <p>Here's a detailed look at the top 12 IoT use cases fueling those numbers.</p> <h3>1. Self-driving and connected vehicles</h3> <p>Autonomous vehicles are one of the most notable examples of IoT in action, with longtime automotive companies such as BMW Group, Ford Motor Company and General Motors -- and newer enterprises, such as Tesla -- all working on self-driving vehicles.</p> <p><a href="https://www.techtarget.com/searchenterpriseai/definition/driverless-car">Self-driving cars</a> and trucks use a variety of connected devices to safely navigate roadways in various traffic and weather conditions. These technologies in use include AI-enabled cameras, motion sensors and onboard computers.</p> <p>Although regulatory, safety and technical concerns over the use of self-driving vehicles exist, the market for self-driving cars is expected to grow rapidly in the upcoming years.</p> <p>In a May 2025 report, Precedence Research valued the global autonomous vehicle market size in 2025 at $273.75 billion and estimated it would reach around $4.45 trillion by 2034.</p> <p>IoT connections also exist on conventional vehicles, with manufacturers installing connected devices to monitor performance and manage computerized systems.</p> <p>Commercial fleets, such as municipal buses and corporate delivery trucks, are often fitted with additional IoT technologies -- for example, connected systems to monitor for safety issues. Personal cars and trucks can be equipped with similar technology, which frequently comes from insurance companies, that collects and transmits telemetry data to verify good driving habits.</p> <h3>2. Logistics and fleet management</h3> <p>Companies use <a href="https://www.techtarget.com/iotagenda/definition/smart-sensor">sensors</a>, telematics, GPS and analytics to see where their vehicles are at any given moment, estimate when they'll arrive at their destination and determine whether external conditions warrant updating routes or expected arrival times.</p> <p>This technology ecosystem also enables companies to identify ways to improve operations through predictive maintenance, more driver training and route optimization.</p> <p>Although logistics companies are among the primary users of such technologies, others also use IoT to track their fleets. For example, bike and scooter rental companies -- sometimes known as the <i>micromobility industry</i> -- use IoT to know where their wares are at any point in time.</p> <p>Grand View Research put the value of the IoT fleet management market at $7.03 billion in 2023 and estimated it would grow at a CAGR of 17% from 2024 to 2030.</p> <p>It attributed that dramatic growth rate "to aspects such as the growing inclusion of connected vehicle technology and the rising demand for operational efficiency to meet the changing needs of a competitive industry worldwide."</p> <h3>3. Traffic management</h3> <p>Part of what enables self-driving cars is smart traffic management, which IoT also powers.</p> <p>Like the vehicles themselves, roadway infrastructure has become more connected during the past decade, with cameras, sensors, traffic light controls, parking meters and even smartphone traffic apps transmitting data that's used to help avert traffic jams, prevent accidents and ensure smooth travel.</p> <p>For example, cameras detect and transmit data about traffic volume to central management groups that <a href="https://www.techtarget.com/iotagenda/definition/What-is-IoT-data-analytics">analyze the information</a> to determine whether, what and when mitigation steps must be taken.</p> <p>Sensors on traffic signals can detect varying levels of light in the sky and adjust the brightness of the signals, helping ensure they're always visible to drivers.</p> <p>Connected devices can be used to detect open parking spaces and transmit that information to kiosks or apps to alert drivers.</p> <p>Monitors on bridges <a href="https://www.techtarget.com/iotagenda/tip/How-IoT-data-collection-works">collect and transmit data</a> for analysis about their structural health, alerting authorities to maintenance needs before any issues or failures occur.</p> <p>Juniper Research's May 2025 report put the global smart traffic management market at nearly $15 billion in 2025 and estimated it would grow by 37% over the next two years.</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/4FxU-xpuCww?autoplay=0&amp;modestbranding=1&amp;rel=0&amp;widget_referrer=null&amp;enablejsapi=1&amp;origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0"></iframe> </div> <h3>4. Smart grids, including smart meters</h3> <p>Utilities have been using IoT to improve efficiency and resiliency in their energy grids for years -- upward of two decades, in some cases.</p> <p>Historically, energy flowed one way along the grid: from the generation site to the customer. However, connected devices now enable two-way communication along the entire energy supply chain, from generation through distribution to use, thereby improving the utilities' ability to move and manage it.</p> <p>Utilities can analyze real-time data transmitted by connected devices to detect blackouts, redirect distribution and respond to changes in energy demand and load.</p> <p>Meanwhile, smart meters installed at individual homes and businesses provide information about real-time use and historical usage patterns that customers and the utilities can analyze to identify ways to improve efficiency.</p> <h3>5. Environmental monitoring</h3> <p>Connected devices can collect data indicating the health and quality of air, water and soil, fisheries, forests and other natural habitats. They can also collect weather and other environmental data.</p> <p>As such, IoT delivers the ability to access more real-time data about the environment at any given time and place and enables a range of organizations in various industries to use that data to glean actionable insights.</p> <p>Such information can help government agencies better monitor and even predict natural disasters, such as tornadoes, and better manage and protect land and wildlife populations. Companies can use this data to better limit their carbon footprint, more effectively document <a href="https://www.techtarget.com/searchnetworking/tip/How-to-handle-environmental-regulations-and-green-networking">compliance with environmental regulations</a> and more efficiently plan around weather conditions that affect their business.</p> <h3>6. Connected buildings and building security</h3> <p>Property owners are using the power of IoT to make buildings smarter, meaning they're more energy-efficient, comfortable, convenient, healthier and possibly safer.</p> <p>An IoT ecosystem in a commercial building could include monitoring the HVAC infrastructure, which uses real-time data and automation technologies to constantly measure and adjust the temperature for optimum energy efficiency and comfort. Meanwhile, cameras using AI could aid in crowd management to ensure the smooth flow of foot traffic or support public safety at large-scale events such as sold-out concerts.</p> <p>On the home front, consumers can install smart technologies -- such as door locks, appliances, thermostats and smoke detectors -- that help them with their everyday needs, for example, by coordinating temperature controls to the owners' schedules.</p> <p>Additionally, IoT capabilities power modern security systems in commercial and residential buildings with connected cameras and sensors detecting and registering movement or activity -- i.e., a doorbell ringing. Those cameras and sensors then transmit that information to other systems, which can be programmed to analyze the data and automated to take specific actions based on that data, or to actual humans, such as homeowners who can determine what action to take.</p> <p>This IoT market segment is also seeing remarkable growth: In May 2025, Precedence Research estimated the global smart building market size at $111.51 billion and predicted it will reach $277.92 billion by 2034.</p> <h3>7. Smart cities</h3> <p><a href="https://www.techtarget.com/iotagenda/definition/smart-city">Smart cities</a> are consolidating IoT deployments across many facets to give municipalities a holistic view of what's happening in their jurisdictions.</p> <p>Smart cities incorporate connected traffic management systems and their own smart buildings, as well as private smart buildings. They might also tie into smart grids and use environmental monitoring to create an even larger IoT ecosystem that provides real-time views of the various elements that affect life in their municipalities.</p> <p>Like smaller, more confined IoT deployments, the objective with smart cities is to collect real-time data for analysis that provides insights municipal officials can use for better decision-making and automated controls to yield more efficient, effective, resilient and safer communities. One leader in this area is Singapore, which promotes its tech-forward efforts on its website. The city-state said it's "designing, building and implementing government-wide Internet of Things (IoT) infrastructures for Smart City applications."</p> <h3>8. Supply chain management</h3> <p><a href="https://www.techtarget.com/searcherp/Guide-to-supply-chain-management">Supply chain management has been undergoing modernization</a>, thanks to low-power sensors, GPS and other tracking technologies that pinpoint assets as they move along a supply chain. Such information lets managers more effectively plan and more confidently reassure stakeholders about the location of items shipped or received.</p> <p>That visibility is beneficial, but it's only the start of the value proposition that IoT brings to this discipline. IoT technologies can also monitor and manage delivery requirements -- for example, measuring and maintaining a specified temperature throughout transport to ensure quality and safety controls. Additionally, back-end analytics capabilities can use IoT-generated data to determine supply chain improvements, such as more efficient routes or shipping times.</p> <p>In "IoT Use Case Adoption Report 2024," market research firm IoT Analytics cited numerous ways IoT helps improve the supply chain, including real-time inventory management; supply chain track and trace; track and trace of assets on-site, such as in a warehouse; and product location tracking.</p> <h3>9. Digital payments</h3> <p>IoT also has a role in digital payments, and financial institutions are positioning themselves to use the technology.</p> <p>Take Visa, for example, which promotes the use of IoT. In an online post, the company wrote, "Imagine a future where machines are capable of conducting commerce with other machines. A world in which every internet-connected device can accept and make payments."</p> <p>"This is no longer the stuff of science-fiction," it continued. "Today, a vast, evolving ecosystem of connected devices is already revolutionizing commerce. Known as the Internet of Things, this expanding universe of interoperable devices is making payments possible in everything from connected cars and wearables to smart homes and cities."</p> <h3>10. Health and wellness</h3> <p>As in other areas, IoT devices can gather data -- in this case, biometric data from individuals -- to gain real-time and near-real-time insights into an individual's health and well-being.</p> <p><a href="https://www.techtarget.com/iotagenda/definition/IoMT-Internet-of-Medical-Things">Medical institutions use connected devices</a> throughout their care delivery processes, with many specifically designed to monitor patient vital signs and health conditions. Connected monitors, for example, can monitor, record and transmit a patient's heart rate, glucose levels or blood pressure; some can also determine whether readings are within or outside a predetermined acceptable range and alert the patient or healthcare provider if that happens.</p> <p>Consumers also have access to such devices and more, with smartwatches and other wearables capable of tracking, transmitting and analyzing different wellness markers, from daily steps taken to the amount of quality sleep received.</p> <p>Future Market Insights estimated the global IoT healthcare market's value to be $243.4 billion in 2025 and projected it will grow at a CAGR of 15.3% to surpass $1 trillion by 2035.</p> <h3>11. Predictive maintenance</h3> <p>Another prominent use of IoT, one of the oldest and most widespread examples, is understanding machine health and identifying when a machine needs service.</p> <p>Sensors are placed in various mechanical systems, from airplanes and mining equipment to manufacturing assembly lines and household appliances. These sensors collect, store and transmit data about performance, which, when analyzed, can pinpoint maintenance needs and potential problems before they're required. This enables owners to take preventive action, thereby avoiding degraded performance and equipment failures.</p> <h3>12. Location tracking</h3> <p>In its use case adoption report, IoT Analytics listed location tracking as one of this technology's most prevalent use cases. The report noted that approximately 45% of the surveyed companies use IoT for location tracking. "IoT location can be applied across various environments, including warehouses, factories, and outdoor work sites," IoT Analytics stated.</p> <p>"The location data gathered from the machines or devices help companies locate their equipment and personnel, optimize routing, improve asset utilization, and enhance safety."</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineImages/iotagenda-industry_iot_use_cases_for_distribution_and_automation-f.png"> <img data-src="https://www.techtarget.com/rms/onlineImages/iotagenda-industry_iot_use_cases_for_distribution_and_automation-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineImages/iotagenda-industry_iot_use_cases_for_distribution_and_automation-f_mobile.png 960w,https://www.techtarget.com/rms/onlineImages/iotagenda-industry_iot_use_cases_for_distribution_and_automation-f.png 1280w" alt="Chart depicting IoT use cases by industry." height="422" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>IoT can add business value to several industries, including construction, manufacturing, retail and transportation. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="IoT uses across industries"> <h2 class="section-title"><i class="icon" data-icon="1"></i>IoT uses across industries</h2> <p>IoT has numerous applications in nearly every sector. Aerospace, agriculture, commercial, healthcare, industry, logistics, manufacturing, retail, space, transportation and more have benefited from their IoT deployments, as they have <a href="https://www.techtarget.com/iotagenda/tip/AI-and-IoT-How-do-the-internet-of-things-and-AI-work-together">paired the data those endpoints generate with analytics</a> platforms to gain visibility into and an accurate understanding of their operations. Those insights were impossible to get before the deployment of IoT technology.</p> <p>Consider the following examples:</p> <ul class="default-list"> <li>Manufacturing uses IoT to monitor factory production and provide predictive maintenance on equipment. A manufacturer might use machine-to-machine connected devices to map workloads more accurately as part of an industrial IoT deployment. A factory could track wear and tear on equipment to schedule preventive maintenance at an optimal time. Companies can use employee badges or wearable devices embedded with RFID chips to manage and control physical access to facilities.</li> <li>Farmers can opt for location technologies integrated with environmental monitors and their field equipment to automate and maximize their seed allocations.</li> <li>Transportation and logistics companies, including international shipping companies, use IoT technologies to track their fleets and goods as they're transported. Some also track the conditions in which goods are stored; a transportation company, for example, can monitor and adjust the temperature in a refrigerated truck to ensure it's kept within an optimal temperature range for the items being transported.</li> <li>Retailers use IoT systems to support warehouse automation and robotics capabilities. They're also using IoT for inventory control and, increasingly, for enhancing in-store customer experience and personalized services.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Enterprise benefits of IoT"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Enterprise benefits of IoT</h2> <p>Although some industry-specific IoT use cases exist, many of the most common deployments involving connected technologies transcend any particular vertical. They can be found across a wide range of organizations.</p> <p>The <a href="https://www.techtarget.com/iotagenda/tip/Top-advantages-and-disadvantages-of-IoT-in-business">benefits that come with those deployments</a> are similar across industries. Organizations can see returns on their IoT investments via those benefits, which include the following:</p> <ul class="default-list"> <li>Lower operational costs.</li> <li>Enhanced productivity.</li> <li>Optimized output.</li> <li>Increased security.</li> <li>Improved safety.</li> <li>Enhanced customer experience.</li> <li>Personalized service.</li> <li>Better quality control.</li> <li>Reduction of waste.</li> <li>Increased levels of sustainability.</li> <li>Heightened understanding and visibility into real-world activities.</li> <li>Better data-driven decision-making.</li> </ul> <p><i>Mary K. Pratt is an award-winning freelance journalist with a focus on covering enterprise IT and cybersecurity management.</i></p> </section> IoT applications span both industry-specific and universal use cases, delivering key benefits: reduced operational costs and improved productivity across organizations. https://cdn.ttgtmedia.com/visuals/ComputerWeekly/Hero%20Images/IoT-connected-car-adobe.jpg https://www.techtarget.com/iotagenda/tip/Top-8-IoT-applications-and-examples-in-business Tue, 29 Jul 2025 00:00:00 GMT 60 webmaster@techtarget.com