<p dir="ltr" id="isPasted">Our new report, <strong>AI at the Edge: Technology Accelerated by Wi-Fi Services</strong>, dives deeply into the convergence of Wi-Fi services and Edge AI and explores how a technology model like WaaS can accelerate the adoption of AI at the edge.&nbsp;</p><p dir="ltr">Below is an excerpt from the final chapter of the report. To read the full report, including in-depth case studies, download it now.</p><p dir="ltr"><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzExMTI0MjE4NTYyLVJlbGF5IDIucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib"></p><p dir="ltr"><span contenteditable="false" draggable="true" class="fr-video fr-deletable fr-fvc fr-dvb fr-draggable"><iframe width="540" height="305" src="https://c8056756.sibforms.com/serve/MUIFAIgRr7nh2u88k57MUBWp43e1lkOKIXq3Z9dxFiC8kXdgaxMxkxsZKsum_gd4u7Qq4_1n-e3n6hH4X_Nw12RLp7SUWPiUkUUgLHhq84lH8VfbGGhwuM1Hvkr60WpcS1SyyBLR-7ErbMPEfKrwqo_-_-CHDFwvTGW-swKGBpTKYdEO-rdhIbTFZyt7qA8fH9zg-zqRf6Li7cOQ" frameborder="0" scrolling="auto" allowfullscreen="" style="display: block;margin-left: auto;margin-right: auto;max-width: 100%;" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe></span><br></p><p dir="ltr" id="isPasted">The next years of this decade are going to be extremely exciting for AI, particularly Edge AI. And with Wi-Fi Services like Relay2 revolutionizing the access point market, the future is going to be very promising indeed. The surging demand for AI applications that offer real-time, low-latency, and privacy-conscious capabilities will usher in a wave of Edge AI implementations. These deployments are poised to become increasingly precise and efficient, capitalizing on advancements in communication networks, such as Wi-Fi 6, coupled with innovations in artificial intelligence (such as data-efficient AI) and the Internet of Things (IoT).&nbsp;</p><p dir="ltr">This transformative landscape underscores the pivotal role played by researchers, industry leaders, and open-source communities in steering the trajectory of Edge AI development. The evolution of efficient Edge AI applications relies on the progress of various technologies designed to support edge devices and enhance the computational efficiency of AI functions, including Wi-Fi services.</p><h3 dir="ltr">Increased Adoption &amp; Integration with Edge AI</h3><p dir="ltr">As the demand for real-time processing and low-latency applications continues to surge, the integration of Edge AI with Wi-Fi services will follow suit. The agility and scalability of Wi-Fi seamlessly complement the requirements of edge computing and AI. For instance, the latest generation of Wi-Fi, Wi-Fi 6, promises much faster data transfer speeds that can reach up to five times the speeds of Wi-Fi 5. This is complemented by reduced power usage, increased capacity, and enhanced performance, providing higher connection reliability in environments with multiple connected devices. This is where Relay2 sets a standard with its Wi-Fi services, pushing for innovation that leverages advancements like Wi-Fi 6. With a dynamic system that ensures flexibility and security, Relay2 offers virtual access control and simultaneous HD video sessions that can support up to 128 sessions. This is further supported by high performance and management of heavy traffic, capitalizing on an average throughput DL that exceeds 2 Gbps and handles 1,024 clients concurrently.</p><p dir="ltr">This is bound to grow and enhance the adoption and integration with Edge AI in order to enrich the user experience. By implementing AI at the edge for efficient data processing and leveraging Relay2’s proactive real-time analysis and natural language adaptability, businesses and organizations can elevate their user experience beyond merely improving connection reliability. This synergy allows for efficient processing closer to data sources, reducing latency and enhancing overall system responsiveness.</p><p dir="ltr">With Wi-Fi 7 being the next generation of Wi-Fi, we could see an even more seamless and immersive user experience and an advanced Edge AI performance, building on its new features such as multi-link operation (MLO), 320 MHz superwide channels, and a 4k quadrature amplitude modulation (QAM). This convergence of state-of-the-art communications and information technologies, such as cloud-native Wi-Fi services, edge computing, IoT, and AI, is driving a massive leap in management efficiency and social productivity. The hybrid edge-cloud architectures and applications are likely to surge in the very near future, ensuring not only high speed and efficiency but also the ability to run multi-modal generative AI and language models at the edge . In the second half of this decade, we will arguably witness an unprecedented increase in the adoption of Edge AI across numerous applications, rendering the technology mainstream.</p><h3 dir="ltr">Computer Vision &amp; the Impact of Edge AI and Wi-Fi</h3><p dir="ltr">One area where the convergence of Edge AI and Wi-Fi services is poised to have a high impact is computer vision applications. With the capability to process data locally, Wi-Fi-empowered edge devices can execute intricate computer vision tasks with unparalleled speed and efficiency. This transformative shift not only minimizes reliance on centralized cloud servers but also allows positioning systems to optimize energy and costs, enabling applications such as facial recognition, object detection, and automated surveillance to operate seamlessly in real time.</p><p dir="ltr">With localization techniques such as Wi-Fi-based positioning systems (WPS) and the advent of convolutional neural networks (CNNs), we can detect and extract spatial patterns from visual data in a remarkable manner. This has the potential to transform industries, including healthcare, retail, automotive, and traffic management. Combining the high-processing capabilities of cloud computing with the real-time features of edge computing and the connectivity enhancements brought about by Wi-Fi technologies can enable AI to lift computer vision to a different level. Consider industrial automation in large factories and warehouses, smart cities with optimized traffic control, retail centers and shopping complexes with enhanced services and store layouts based on monitored customer behavior, and even remote medical services and patient monitoring that enable accurate diagnosis in real time. All these developments can take place by leveraging computer vision that is powered by AI at the edge.</p><p dir="ltr">While there are still challenges standing before computer vision today, such as high processing power and high-quality data, the potential that Edge AI brings, supported by Wi-Fi capabilities that ensure fast and seamless data transfer - even in remote areas where accessibility would otherwise be difficult - will propel computer vision and enable it to be a much more potent and ubiquitous technology.&nbsp;</p><p dir="ltr">With on-device inference capabilities and functionalities that enable computer vision within edge and mobile devices, image and pattern recognition can improve significantly, taking advantage of edge computing’s reduced latency, enhanced security, and minimized costs. Integrating AI into the mix enables even low-cost cameras to act as smart cameras, with deep learning methods enabling better identification and interpretation of data patterns. This is further enhanced by leveraging data from multiple devices connected via Wi-Fi, which provides AI with more comprehensive data, reinforcing its precision and understanding.</p><h2 dir="ltr">Conclusion: Wi-Fi-Powered Edge AI - A Technology for the Future</h2><p dir="ltr">Wi-Fi and Edge AI represent a technological paradigm shift with far-reaching implications. The convergence of Wi-Fi with Edge AI is not just a technological evolution but a fundamental reshaping of the digital landscape. As this symbiotic relationship matures, it propels us towards a future where Edge AI is not just a technology but an integral and indispensable part of our interconnected world. The potential for transformative applications is immense, urging both developers and sellers to explore the uncharted territories of innovation and contribute to the unfolding narrative of Edge AI's promising future.</p><p dir="ltr">This not only addresses the computational needs of Edge AI but also aligns with the growing trend of connected devices in smart buildings, industrial settings, healthcare, retail, and smart cities. The integration of Edge AI with Wi-Fi services brings forth a boost in performance, user experience, and security measures, ensuring that sensitive data is processed locally. This transformation leads to the development of robust, always-on systems capable of meeting the stringent privacy requirements of contemporary applications and the ever-growing need for better performance, flexibility, scalability, and reliability.</p><p dir="ltr">Throughout this report, we explored the capabilities and impact of Edge AI, especially when coupled with Wi-Fi services. We highlighted the valuable insights provided by Relay2, the leading Wi-Fi technology provider for the Edge AI market. Relay2's Service Points technology is designed to deliver exceptional application performance while enhancing security, privacy, and scalability at the edge.&nbsp;</p><p dir="ltr">The Relay2 ServiceEdge Platform harnesses the power of Wi-Fi Services with Edge Computing to create a digital world where application performance and user experience not only remain uncompromised but are also enhanced. We also dove into particular applications and reviewed some use cases of Wi-Fi services edge computing. And finally, we took a look at the future of these technologies and how they will impact our businesses and way of living in the coming years. All this could not have been done without the support of Relay2 in developing this report.&nbsp;</p><p dir="ltr">Relay2 is committed to empowering its partners by providing comprehensive, innovative solutions to ensure mutual success leveraging Wi-Fi Services with Edge Computing and the Relay2 ServiceEdge Platform. Therefore, developers and sellers are encouraged to partner with Relay2 to unlock the full potential of technology and shape a seamless digital future. The convergence of Wi-Fi with Edge computing can reshape the digital technology and business landscape, and Relay2 is at the forefront of this transformation.</p><h2 dir="ltr">Acknowledgments</h2><p dir="ltr">This report is the result of collaborative efforts between Wevolver and Relay2. Initial input was graciously provided by Relay2’s Eric Chen and Daniel Kwong, sharing their insights, expertise, and case studies, creating a robust technical substructure for the report. Then, the author further expanded upon this information to develop a comprehensive and insightful text, supported by the content and design team at Wevolver. Thank you to all contributors and supporters, and special thanks to Relay2.</p><p dir="ltr">Download the full report with custom images, case studies and more, below.&nbsp;</p><p dir="ltr"><span contenteditable="false" draggable="true" class="fr-video fr-deletable fr-fvc fr-dvb fr-draggable"><iframe width="540" height="305" src="https://c8056756.sibforms.com/serve/MUIFAIgRr7nh2u88k57MUBWp43e1lkOKIXq3Z9dxFiC8kXdgaxMxkxsZKsum_gd4u7Qq4_1n-e3n6hH4X_Nw12RLp7SUWPiUkUUgLHhq84lH8VfbGGhwuM1Hvkr60WpcS1SyyBLR-7ErbMPEfKrwqo_-_-CHDFwvTGW-swKGBpTKYdEO-rdhIbTFZyt7qA8fH9zg-zqRf6Li7cOQ" frameborder="0" scrolling="auto" allowfullscreen="" style="display: block;margin-left: auto;margin-right: auto;max-width: 100%;" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe></span><br></p>

The coming years will see a surge in Edge AI advancements, driven by real-time, efficient, and privacy-focused AI applications, alongside innovations in Wi-Fi and IoT, marking a promising future shaped by researchers, industry leaders, and open-source contributions.

AI at the Edge Report. Chapter 4: Future of Edge AI with Wi-Fi Technology

<p dir="ltr" id="isPasted">Our new report, <strong>AI at the Edge: Technology Accelerated by Wi-Fi Services</strong>, dives deeply into the convergence of Wi-Fi services and Edge AI and explores how a technology model like WaaS can accelerate the adoption of AI at the edge.&nbsp;</p><p dir="ltr">Below is an excerpt from Chapter 3 of the report. To read the full report, including in-depth case studies, download it now.</p><p dir="ltr"><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1710514655459-Relay+2.png" style="width: 100%px;" class="fr-fic fr-dib"></p><p dir="ltr"><span contenteditable="false" draggable="true" class="fr-video fr-deletable fr-fvc fr-dvb fr-draggable"><iframe width="540" height="305" src="https://c8056756.sibforms.com/serve/MUIFAIgRr7nh2u88k57MUBWp43e1lkOKIXq3Z9dxFiC8kXdgaxMxkxsZKsum_gd4u7Qq4_1n-e3n6hH4X_Nw12RLp7SUWPiUkUUgLHhq84lH8VfbGGhwuM1Hvkr60WpcS1SyyBLR-7ErbMPEfKrwqo_-_-CHDFwvTGW-swKGBpTKYdEO-rdhIbTFZyt7qA8fH9zg-zqRf6Li7cOQ" frameborder="0" scrolling="auto" allowfullscreen="" style="display: block;margin-left: auto;margin-right: auto;max-width: 100%;" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe></span><br></p><p id="isPasted">The applicability of Wi-Fi Edge AI is fairly expansive and is growing by the day, spanning various industries and application areas. The most central aspects of this intersection of technologies are the real-time insights they provide, how these insights impact the speed and type of response, and how they are communicated across the network. Whether it is in smart healthcare, education, retail, or other application areas, Wi-Fi-enabled Edge AI is redefining how technology is leveraged in real time. Relay2 utilizes several Edge AI platforms to enhance the functionality of AI applications on the edge. In this chapter, we will take a look at some interesting use cases of Wi-Fi Edge AI, and we will see the impact of this technology convergence and the new opportunities it is opening in new and emergent technological spaces.</p><h2>Education / Smart Campus</h2><p>Wi-Fi Edge AI plays an important role in education-related applications, among which is remote learning integration, facilitating seamless and interactive remote education and bridging the gap between on-site and remote learning experiences. With localized content engagement pattern analysis and personalized experiences for students, Wi-Fi services and edge computing can help enhance and refine education content delivery.&nbsp;</p><p>Campus facilities can also benefit significantly from integrating such technologies, especially in terms of security and surveillance, where Wi-Fi Edge AI can help analyze surveillance videos locally and in real time to recommend timely actions for security staff. It also powers use cases like attendance automation and traffic patterns, streamlining attendance tracking for educators and student flow analysis for operation enhancement.&nbsp;</p><p>Another use case of Wi-Fi and edge computing can be seen in revenue generation, in which they enable intelligent, location-based advertising through audience behavior analysis for commercial partners. By leveraging these technologies, educational institutions can help promote campus services better, boost product marketing across campus premises and beyond, and enable efficient digital transactions.</p><p>One example of applying Wi-Fi and edge computing in education is by WENet, an OEM partner of Relay2 in Vietnam. In order to support the University of Transport Technology in Vietnam in developing a digital technology infrastructure platform, WENet deployed Relay2’s Wi-Fi-enabled edge computing solution, making use of the advantages provided by Relay2 ServiceEdge Platform compared to conventional Wi-Fi networks. From stable bandwidth to fast processing speed, short deployment time, minimal service interruption time, and optimal operating costs, the features brought about by Relay2’s ServiceEdge Platform were highly effective. As a result, over 17 thousand students across three campuses were able to benefit from this platform, especially in terms of the following three key functions:</p><ul><li>Digital signage interacting with mobile devices to support two-way communication (university-to-student communication and student responses to university requests)</li><li>Students’ access to digital education materials from Relay2’s Service Points</li><li>Students’ ability to order food digitally from the cafeteria</li></ul><p>Such functions have not only enabled students to benefit from a Wi-Fi-powered edge computing platform but also helped collect analytic data for future AI processing at the edge. Read more about the WENet use case on the Relay2 website.</p><h2>Smart Healthcare</h2><p>Undoubtedly, one of the most important aspects of healthcare is real-time monitoring and real-time decision-making. However, as we have seen over the recent years with pandemic-caused crises, healthcare workers are more often than not overworked, and hospitals are resource-limited, which can limit their abilities to provide timely care. In order to ensure patient safety and health within hospital spaces and elsewhere, it is crucial to track, monitor, analyze, and act in real-time. All this can be made available by incorporating Edge AI and Wi-Fi. Whether it is remote monitoring and management, patient activity tracking, patient care, or even assistance during healthcare crises, hospitals, and medical personnel can benefit significantly from integrating Wi-Fi Edge AI into their processes.</p><p>Smart healthcare comes in the form of connected healthcare, where AI-based smart devices, healthcare management software, and digital instruments are integrated into a “connected” healthcare system using a network protocol like Wi-Fi. As such, medical personnel would have access to all the medical-related information they need to provide the patients with the necessary medical treatment in the most effective and convenient way possible. This has been made possible by utilizing Edge AI and Wi-Fi technologies to empower the Internet of Medical Things (IoMT). In other words, healthcare personnel can leverage the low-latency capabilities of Edge AI processing and the ubiquity of Wi-Fi connectivity to access real-time data from diverse medical sensors, enabling timely decision-making and interventions and fostering a proactive approach to patient care.</p><p>Consider intensive care units (ICUs), operating rooms, or other healthcare spaces, the use of Edge AI and Wi-Fi can augment the work of doctors, nurses, and clinicians by minimizing limitations, redundancies, and time allocated to activities away from direct patient care (such as documentation). As a result, medical workers can benefit from an emerging ambient intelligence , powered by edge computing, AI capabilities, and Wi-Fi. This can even be expanded to daily living spaces, which would support independent living, chronic disease management, mental health, and physical rehabilitation, particularly of elderly individuals.</p><h2>Smart Retail</h2><p>Global retail is almost always in flux, and both retailers and suppliers are grappling with the complexities of ever-changing consumer demand, behavior, and expectations. The continuous shifts in these dynamics create uncertainties in predicting future trends and exert significant stress on international supply chains and store operations. Navigating these challenges necessitates real-time adaptability to stay ahead in the retail industry.</p><p>Edge AI emerges as a potent solution, offering retailers the capability to swiftly and precisely forecast daily demand while automating crucial aspects of supply chain logistics, customer engagement, and operational agility. This not only addresses challenges related to in-store supply management but also tackles issues in last-mile delivery costs, aligning with consumer expectations regarding timely deliveries.</p><p>Within physical stores, retailers leverage Edge AI to combat issues such as shrinkage and stockouts, optimizing inventory management. Simultaneously, the application of Edge AI and Wi-Fi contributes to the creation of frictionless in-store experiences while prioritizing the health and safety of both employees and shoppers. The integration of AI in retail is thus transforming operations, offering a multifaceted approach to address the intricate challenges posed by the dynamic retail landscape.</p><p>D.Phone, one of the largest cell phone retailers out of China, has deployed in-store Wi-Fi to enhance its customer experience and promote engagement as a way to offer a differentiated experience that would distinguish its &nbsp;D.Phone stores from competitors. They opted for Relay2’s wireless broadband solution, taking advantage of its unified native-cloud wireless networking and edge-service delivery.</p><p>By leveraging Relay2 access points, D.Phone was able to offer high-quality customer experiences and deliver value-added services in-store. With its fast and reliable coverage in demanding environments like customer-dense spaces, including shopping centers and large venues, Relay2 access points enabled D.Phone to meet its customers' expectations and offer them the high-speed connectivity they desire. Moreover, with Relay2’s Edge services, D.Phone was able to run sales-generating applications and computation-intensive services locally and place content right at its &nbsp;D.Phone customers’ fingertips, thus reducing content download time to just seconds. This helped streamline the customer purchasing experience and circumvent bandwidth bottlenecks. It even enabled D.Phone to deliver new services to its customers, including app delivery and couponing. This has displayed an accelerated go-to-market process for D.Phone’s digital merchandise and a reinforced branding strategy. Read more about the D.Phone use case on Relay2’s website.</p><blockquote><p>“Relay2’s plug-and-play access points and cloud-based platform [have] given us a solution that lowers the cost of deployment and management.” - Wu Huan, CIO, D.Phone</p></blockquote><h2>Smart Buildings</h2><p>With the recent growth in smart homes and building automation systems, edge computing, AI, and Wi-Fi have become increasingly popular in this space. The integration of Edge AI with sustainable architecture and smart buildings has been rapidly gaining momentum and transforming the manner in which we construct and interact with our built spaces. With advantages like enhanced energy efficiency, optimized systems, personalized occupant comfort, and streamlined building maintenance, smart buildings are leveraging the real-time analysis capabilities of Edge AI and its integration with IoT and developing potential for more sustainable architecture and digital integration.</p><p>Acting as a centralized intelligence hub, AI processes and interprets data obtained from an array of edge devices (IoT devices) such as sensors and actuators scattered throughout the building. This network of devices forms a comprehensive information system, providing valuable insights into various aspects of the building's operations. Through the implementation of AI algorithms, smart buildings gain the ability to efficiently monitor and regulate crucial functions like lighting, heating, ventilation, air conditioning, security, and energy consumption. Such an integration results in an environment that is not only responsive but also adaptive, catering to the dynamic needs and preferences of the building occupants.</p><p>This can be further supported by Wi-Fi connectivity and cloud-based Wi-Fi services, in particular. Cloud-based Wi-Fi services enable centralized management and control of Wi-Fi networks. This centralized approach simplifies the deployment and maintenance of Wi-Fi connectivity across the building, ensuring a more streamlined and scalable infrastructure. Furthermore, the cloud facilitates the storage and analysis of the vast amounts of data generated by IoT devices in Smart Buildings. AI algorithms require substantial data inputs to make informed decisions, and cloud-based services offer the computational resources needed for processing and interpreting this data. It enables more sophisticated analytics, allowing for better insights into building operations, occupant behaviors, and energy consumption patterns.&nbsp;</p><p>Similarly, the cloud's scalability can easily accommodate the dynamic nature of Smart Buildings, especially when the number of connected devices grows or changes. Just as importantly, cloud-based services enable remote monitoring, management, and updates of Wi-Fi networks and connected devices. This remote accessibility is invaluable for building administrators, allowing them to troubleshoot issues, implement updates, and optimize network performance without physically being on-site. In this regard, smart buildings can benefit meaningfully from Relay2’s innovative solutions. With advanced networking capabilities, Wi-Fi Edge Computing power, and intelligent analytics, users of Relay2’s ServiceEdge platform can ensure seamless connectivity and optimized operational efficiency.</p><h2>Smart Agriculture</h2><p>The Internet of Things (IoT) and edge computing have influenced the agricultural and farming industries quite extensively over the past decade, especially with the rapid rise of low-power wide-area networks (LPWAN) . Wireless communication protocols are, in fact, a vital part of smart agriculture systems, especially since the fields cover large areas that necessitate system components to be placed at remote locations. The integration of Wi-Fi and edge computing has been key to expanding the digital functionalities in agriculture, especially with the advent of AI at the edge, thus increasing the possibilities of smart agriculture over large areas.</p><p>One type of smart agriculture that has been propelled by Edge AI and Wi-Fi services is precision farming. By deploying sensors and cameras in fields, farmers can gather real-time data on crucial factors such as weather patterns, soil conditions, crop growth, and pest infestations. This localized data processing enables farmers to modify and regulate their irrigation, fertilization, and pest control without delay, leading to an increase in crop yields and resource efficiency. The implementation of edge devices equipped with sensors extends beyond crop monitoring to include livestock health and behavior. Wearable devices on animals, such as cattle, provide early indications of illness or oestrus, empowering farmers to take timely actions, resulting in improved animal well-being, reduced rates of mortality, and higher farm productivity all around.&nbsp;</p><p>Furthermore, the incorporation of Edge AI has paved the way for autonomous farming machinery, where tractors and drones equipped with edge devices can analyze field data in real time. This enables them to refine their routes, control planting depths, and identify and eliminate weeds in an autonomous manner. Not only does autonomous farming machinery reduce labor costs, but it also minimizes the use of chemicals, aligning agriculture with more eco-friendly practices. This is further empowered with the integration of Wi-Fi Services, allowing for centralized, remote monitoring and seamless connectivity between edge devices across large fields and in remote areas. The seamless integration of Edge AI and Wi-Fi technologies is proving transformative in making agriculture smarter, more efficient, and more sustainable over expansive agricultural landscapes.</p><p>Relay2 offers smart farms state-of-the-art solutions that can help transform crop production, efficiency, and sustainability. These solutions seamlessly connect and monitor agricultural devices, collect real-time data, and leverage advanced analytics for informed decision-making. By optimizing resources, automating processes, and implementing precision farming, Relay2 empowers farmers to maximize yield and sustainability.</p><hr><p>This was an excerpt from Chapter 3 of the <strong>AI at the Edge: Technology Accelerated by Wi-Fi Services</strong> report. If you would like to read the full report, including in-depth case studies, you can download it below. &nbsp;</p><p><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1710514806917-Relay+2.png" style="width: 100%px;" class="fr-fic fr-dib"></p><p><span contenteditable="false" draggable="true" class="fr-video fr-deletable fr-fvc fr-dvb fr-draggable"><iframe width="540" height="305" src="https://c8056756.sibforms.com/serve/MUIFAIgRr7nh2u88k57MUBWp43e1lkOKIXq3Z9dxFiC8kXdgaxMxkxsZKsum_gd4u7Qq4_1n-e3n6hH4X_Nw12RLp7SUWPiUkUUgLHhq84lH8VfbGGhwuM1Hvkr60WpcS1SyyBLR-7ErbMPEfKrwqo_-_-CHDFwvTGW-swKGBpTKYdEO-rdhIbTFZyt7qA8fH9zg-zqRf6Li7cOQ" frameborder="0" scrolling="auto" allowfullscreen="" style="display: block;margin-left: auto;margin-right: auto;max-width: 100%;" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe></span><br></p>

Wi-Fi-enabled Edge AI is redefining how technology is leveraged in real time.

AI at the Edge Report. Chapter 3: Applications & Case Studies

<p dir="ltr" id="isPasted">Our new report, <strong>AI at the Edge: Technology Accelerated by Wi-Fi Services</strong>, dives deeply into the convergence of Wi-Fi services and Edge AI and explores how a technology model like WaaS can accelerate the adoption of AI at the edge.&nbsp;</p><p dir="ltr">Below is an excerpt from Chapter 2 of the report. To read the full report, including in-depth case studies, download it now.</p><p dir="ltr"><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1709548103162-Relay+2.png" style="width: 100%px;" class="fr-fic fr-dib"></p><p><span contenteditable="false" draggable="true" class="fr-video fr-deletable fr-fvc fr-dvb fr-draggable"><iframe width="540" height="305" src="https://c8056756.sibforms.com/serve/MUIFAIgRr7nh2u88k57MUBWp43e1lkOKIXq3Z9dxFiC8kXdgaxMxkxsZKsum_gd4u7Qq4_1n-e3n6hH4X_Nw12RLp7SUWPiUkUUgLHhq84lH8VfbGGhwuM1Hvkr60WpcS1SyyBLR-7ErbMPEfKrwqo_-_-CHDFwvTGW-swKGBpTKYdEO-rdhIbTFZyt7qA8fH9zg-zqRf6Li7cOQ" frameborder="0" scrolling="auto" allowfullscreen="" style="display: block;margin-left: auto;margin-right: auto;max-width: 100%;" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"><span class="fr-mk" style="display: none;">&nbsp;</span></iframe></span></p><p dir="ltr" id="isPasted">The convergence of Wi-Fi and edge computing stands as a formidable force driving the ongoing shift to digital today. This convergence presents a pioneering paradigm for connectivity. It empowers enterprises with the capabilities of both managed Wi-Fi services and on-device data processing at the edge, enabling them to stay in step with, if not one step ahead of, the evolving digital landscape.&nbsp;</p><p dir="ltr">Wi-Fi analytics services, in essence, revolutionize Wi-Fi deployment through a cloud-based service model, offering a complete package of managed Wi-Fi infrastructure and services. This strategic approach spares organizations from the significant capital investments typically associated with Wi-Fi infrastructure, affording them the opportunity to harness the expertise of service providers for broad network management. As a result, businesses can concentrate on their primary operations without having to worry about the intricacies of network maintenance. Simultaneously, the advent of edge computing ushers in a paradigm shift by migrating computational processes to the data source, thereby reducing latency and enabling real-time analytics and decision-making. This strategic switch from centralized computing models results in a notable enhancement of response time and operational efficiency, thanks to reduced bandwidth requirements and lower latency.</p><p dir="ltr">At the heart of this technological transformation are the edge applications, which play a pivotal role within the Wi-Fi-edge-computing space. These applications harness the potential of edge computing for localized data processing and analytics, giving rise to real-time insights, seamless integration of artificial intelligence, advancements in IoT, and immersive user experiences. AI applications at the edge can accelerate innovation and enable organizations from various sectors to upgrade their services and maximize their operational efficiency.</p><ol id="isPasted"><li dir="ltr"><p dir="ltr">Empowering Organizational Agility:&nbsp;The convergence of Wi-Fi and Edge Computing offers a dynamic solution that equips organizations with the ability to scale their Wi-Fi infrastructure in response to ever-evolving demands. By executing localized data processing and applications at the edge reinforced with Wi-Fi Analytics Services, businesses can seamlessly expand their network infrastructure and minimize their reliance on centralized data processing, thus optimizing bandwidth utilization and curtailing expenses.</p></li><li dir="ltr"><p dir="ltr">Improving Cost-Efficiency and Streamlining Infrastructure Management:&nbsp;With Wi-Fi Networking and Edge Computing convergence, organizations can delegate the management and upkeep of Wi-Fi networks to service providers, hence alleviating the complexities of network infrastructure management while reaping the benefits of trustworthy and proficient Wi-Fi services. This also minimizes the initial financial burdens associated with building and maintaining Wi-Fi infrastructure. This integration yields the merits of both a cloud-managed Wi-Fi framework and local data processing, delivering immediate data insights and facilitating real-time decision-making.</p></li><li dir="ltr"><p dir="ltr">Enhancing Performance and Reducing Latency:&nbsp;Leveraging local data processing at the network edge significantly mitigates latency in comparison to transmitting data across long distances to the cloud. This, in turn, results in prompt response times, enriched user experiences, and substantial improvements in application performance.</p></li></ol><p><br></p><p dir="ltr">In other words, Wi-Fi Services with Edge Computing emerges as a pivotal catalyst for digital transformation. Through its localized data processing capabilities, it delivers faster (low latency), more efficient (less bandwidth usage), and highly secure (enhanced security) data handling to enable real-time decision-making, which is a central factor of many applications, including autonomous driving, healthcare, and smart factories.</p><h3 dir="ltr">Relay2 ServiceEdge Platform: Reshaping Wi-Fi Access Point Technology</h3><p dir="ltr">In a recent study by Gartner, analysts estimated that by 2025, 75% of all enterprise-generated data will be created and processed outside of the cloud or traditional centralized data centers . These predictions highlight the significance of edge computing and its growth in enabling AI applications at the edge. This is where Relay2’s Service Point technology emerges, providing a state-of-the-art, all-in-one solution that combines Wi-Fi services with edge computing.</p><p dir="ltr" id="isPasted">Relay2's Service Point technology marks a substantial advancement in the field of Wi-Fi access point technology, pushing the boundaries of what conventional access points can achieve. Traditional access points may offer fundamental connectivity, yet they frequently fall short in providing the essential features required to fully exploit the potential of edge computing. The Relay2 Wi-Fi Service Point is a high-caliber Wi-Fi access point that incorporates inherent edge computing capabilities. It offers the capacity to host and execute local edge applications, which are either native software applications or equivalent counterparts of cloud-based applications. This convergence of edge computing at the Wi-Fi access point results in enhanced application and service performance, real-time interaction and response, and secure data processing, ensuring privacy and confidentiality.</p><p dir="ltr">Using Relay2’s Service Point, businesses can leverage Wi-Fi services with edge computing to reap the following benefits:</p><ol><li dir="ltr"><p dir="ltr">Efficient use of extra computing resources:&nbsp;By delegating computational duties from centralized servers to the Service Point devices, enterprises can enhance their network's overall performance and diminish latency. These devices have powerful processors and extensive memory, which enable streamlined handling of complex computing tasks at the edge of the network.</p></li><li dir="ltr"><p dir="ltr">Enhanced performance, reliability, and security:&nbsp;Service Point devices have built-in security features and advanced encryption protocols that support organizations’ privacy and integrity of their data. Furthermore, these devices are engineered to manage substantial data workloads and sustain unwavering performance, even in challenging operational settings.</p></li><li dir="ltr"><p dir="ltr">Streamlining infrastructure and achieving sustainable cost efficiency:&nbsp;Businesses can significantly benefit from an all-in-one device that integrates switches, routers, and computer servers, enabling them to optimize their network infrastructure and minimize long-term operational and maintenance costs. This comprehensive approach simplifies deployment and management processes, granting organizations the ability to allocate their resources with increased efficiency.</p></li></ol><p dir="ltr">Relay2 has taken one step further and has developed a cutting-edge platform called the ServiceEdge Platform. This platform is purpose-built to coordinate and oversee Relay2 Service Points and the edge-based applications they host, all orchestrated seamlessly from the cloud. The Relay2 ServiceEdge Platform comprises a network edge device (the Relay2 Wi-Fi Service Point), combined with a cloud portal service that allows for the management and coordination of Wi-Fi networking, Service Point, and edge computing. This platform enables the distribution, hosting, provisioning, and automation of custom-built or open-source edge applications via the Edge Apps Orchestrator. The overarching goal of the Relay2 ServiceEdge Platform is to offer a more efficient solution for WaaS providers to overcome the challenges of increasing operating costs and diminished ROI. By incorporating edge computing for advanced value-added services, this platform seeks to enhance the competitiveness of WaaS providers in the marketplace.</p><p dir="ltr" id="isPasted">Going beyond the conventional Wi-Fi access points focused on network connectivity, Relay2 Service Points introduce advanced edge-computing capabilities. These capabilities enable the hosting of edge applications within the Wi-Fi network in closest proximity to users and data sources. Relay2 expands the reach of edge computing, providing an opportunity for cloud computing applications to leverage the deployment of their edge-computing equivalents.&nbsp;</p><p dir="ltr">The Relay2 Edge Apps Orchestrator stands out in the market due to a set of unique and compelling features. It introduces hierarchical, tiered-account cloud management services tailored to distributors, service providers, and end customers, facilitating Cloud Wi-Fi network management for Managed Service Providers (MSPs) while reducing operational expenses. Notably, the Edge Application Store within the Relay2 Wi-Fi Cloud Manager presents a distinct advantage, allowing MSPs to swiftly download and install prequalified applications for Service Points, expediting proof-of-concept for value-added services. Furthermore, Relay2 offers a cloud portal for provisioning, management, and automation of application hosting and settings on Service Points, enhancing user convenience through centralized configuration and administration. The platform also seamlessly orchestrates docker containers with its patented edge container system, streamlining the dynamic deployment of containerized edge applications while optimizing resource utilization and simplifying application management.</p><p dir="ltr">Leveraging docker containers for the development of edge applications on Service Points, Relay2 fosters a developer-friendly, open-source environment, enabling IT technicians to create and deploy applications efficiently, thereby reducing time-to-market. Lastly, the Relay2 Cloud Manager provides feature-rich graphics, user interfaces, and monitoring capabilities, offering comprehensive insights into edge-computing applications and network performance for organizations.</p><p dir="ltr">With Relay2 ServiceEdge Platform, businesses and developers can take part in the digital transformation and benefit from Relay2’s store of ready-made edge-computing applications to reduce their time to market and enhance their infrastructure’s scalability and flexibility with unparalleled automation and orchestration. They can also boost their operational efficiency with streamlined IT operations enabled by a centralized cloud-based management portal, all the while future-proofing their digital network infrastructure and unlocking new opportunities in emerging technologies like AI and IoT.</p><p dir="ltr">This was an excerpt from Chapter 2 of the AI at the Edge: Technology Accelerated by Wi-Fi Services report. If you would like to read the full report, including in-depth case studies, you can download it below. &nbsp;</p><p dir="ltr"><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1709548158975-Relay+2.png" style="width: 100%px;" class="fr-fic fr-dib"></p><p><span contenteditable="false" draggable="true" class="fr-video fr-deletable fr-fvc fr-dvb fr-draggable"><iframe width="540" height="305" src="https://c8056756.sibforms.com/serve/MUIFAIgRr7nh2u88k57MUBWp43e1lkOKIXq3Z9dxFiC8kXdgaxMxkxsZKsum_gd4u7Qq4_1n-e3n6hH4X_Nw12RLp7SUWPiUkUUgLHhq84lH8VfbGGhwuM1Hvkr60WpcS1SyyBLR-7ErbMPEfKrwqo_-_-CHDFwvTGW-swKGBpTKYdEO-rdhIbTFZyt7qA8fH9zg-zqRf6Li7cOQ" frameborder="0" scrolling="auto" allowfullscreen="" style="display: block;margin-left: auto;margin-right: auto;max-width: 100%;" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe></span><br></p>

Wi-Fi and Edge Computing: Transforming AI Applications


AI at the Edge Report. Chapter 2: Relay2 and Edge AI

<p dir="ltr" id="isPasted">Our new report, <strong>AI at the Edge: Technology Accelerated by Wi-Fi Services</strong>, dives deeply into the convergence of Wi-Fi services and Edge AI and explores how a technology model like WaaS can accelerate the adoption of AI at the edge.&nbsp;</p><p dir="ltr">Below is an excerpt from Chapter 1 of the report. To read the full report, including in-depth case studies, download it now.</p><p dir="ltr"><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzA5MTI3Njg4OTg0LVJlbGF5IDIucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib"></p><p dir="ltr"><span contenteditable="false" draggable="true" class="fr-video fr-deletable fr-fvc fr-dvb fr-draggable"><iframe width="540" height="305" src="https://c8056756.sibforms.com/serve/MUIFAIgRr7nh2u88k57MUBWp43e1lkOKIXq3Z9dxFiC8kXdgaxMxkxsZKsum_gd4u7Qq4_1n-e3n6hH4X_Nw12RLp7SUWPiUkUUgLHhq84lH8VfbGGhwuM1Hvkr60WpcS1SyyBLR-7ErbMPEfKrwqo_-_-CHDFwvTGW-swKGBpTKYdEO-rdhIbTFZyt7qA8fH9zg-zqRf6Li7cOQ" frameborder="0" scrolling="auto" allowfullscreen="" style="display: block;margin-left: auto;margin-right: auto;max-width: 100%;" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"><span class="fr-mk" style="display: none;">&nbsp;</span><span class="fr-mk" style="display: none;">&nbsp;</span><span class="fr-mk" style="display: none;">&nbsp;</span><span class="fr-mk" style="display: none;">&nbsp;</span><span class="fr-mk" style="display: none;">&nbsp;</span></iframe></span></p><p dir="ltr" id="isPasted">Typically, artificial intelligence has been powered by cloud computing, given AI’s need for computing power and data-intensive processing. However, with the advent of edge computing, the AI landscape has been shifting, allowing for the rise of Edge AI. Edge AI is a revolutionary approach to how we deploy AI in various application areas, as it enables local computing and processing of data. That means the computing power is brought closer to the source of data, facilitating on-device data processing. With Edge AI, the system can make decisions in real time and with full contextual awareness by enabling AI features and capabilities directly on devices. Such a process would benefit from significant advantages brought about by Edge AI, including quick response, high bandwidth efficiency, and cost-effectiveness, to name a few.</p><p dir="ltr">Unlike Cloud AI, which relies on remote servers for data processing and analysis, Edge AI is applied locally among a spectrum of devices spanning from data centers to IoT endpoints. The nature and location of the data being processed determine whether Cloud AI or Edge AI is more suitable for a particular application. For processing-intensive applications where latency can be compromised for the sake of in-depth data analysis and powerful computation, Cloud AI would be the ideal option. However, many applications are time-sensitive and require real-time data processing and prompt responses. This is where Edge AI takes center stage, minimizing the need to send data back and forth to a cloud server. This can take place at any location denoted as the edge, such as retail stores, hospitals, traffic lights, autonomous vehicles, and educational facilities.</p><p dir="ltr" id="isPasted">The following table explains the benefits and applicability of Edge AI and Cloud AI and how they differ from one another. Keep in mind that Edge AI and Cloud AI are not interchangeable technologies but rather applicable in different applications and scenarios. In fact, Edge AI and Cloud AI can even be complementary for systems that include both time-dependent and processing-intensive applications, which can benefit from a hybrid approach to data processing that integrates both technologies, as we’ll discuss later in this report.</p><p dir="ltr"><em>Table 1: Applicability and Benefits of Edge AI and Cloud AI</em></p><p dir="ltr"><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzA4NTg0MTM3NjM2LXRhYmxlIHJlbGF5LnBuZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 100%px;" class="fr-fic fr-dib"></p><h3 dir="ltr" id="isPasted">The Evolution and Adoption of Edge AI</h3><p dir="ltr">A 2023 report by Gartner on innovations in and around AI has highlighted the AI hype cycle for this year, showcasing the various advancements in AI and where they are today in terms of the public’s expectations . Among these innovations, we can see Cloud AI slowly navigating the so-called “Slope of Enlightenment” stage, where it is gradually transitioning toward mainstream adoption. In fact, Gartner expects Cloud AI to become mainstream in two to five years. Meanwhile, one of the fastest-growing innovations we can pinpoint on the cycle graph is Edge AI, showing a fast adoption rate to reach mainstream productivity in less than two years. This validates the potential that Edge AI has demonstrated in the past 2-3 years and shows that both edge and cloud computing can support AI applications in a symbiotic manner in the very near future.</p><p dir="ltr"><span contenteditable="false" class="fr-img-caption    fr-fic fr-dib fr-draggable" style="width: 768px;" draggable="false"><span class="fr-img-wrap"><a href="https://www.gartner.com/en/articles/what-s-new-in-artificial-intelligence-from-the-2023-gartner-hype-cycle" target="_blank" rel="noopener noreferrer"><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzA4NTg0MjE0MDU5LTAzXzExLmpwZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 768px;" class="fr-fic fr-dib"><span class="fr-inner" contenteditable="true">The hype cycle for AI in 2023 showed the rapid adoption rate of Edge AI. Credit: Gartner.</span></a></span></span></p><p dir="ltr" id="isPasted">The recent developments in Edge AI have opened up new opportunities for devices to operate with human-like intelligence, regardless of their location. The successful deployment of AI models at the edge can be attributed to innovations that have significantly contributed to today’s digital transformation. For instance, neural networks and AI infrastructure have reached a level of maturity enough to pave the way for generalized machine learning. Organizations are now able to train AI models and deploy them in production at the edge. Besides, the recent advanced Edge AI accelerator chipset development, such as Axelera Metis, with high performance and low power budget, has made it possible to integrate these AI capabilities at a low power budget and with very high inference speed. Relay2 is pioneering this embedded integration with Wi-Fi Access Point, the edge of the Wi-Fi network. &nbsp;This is further strengthened by the widespread adoption of IoT devices, which is arguably the key reason behind the blowup of big data. Businesses can now collect every type of data from various sources. This availability of data and corresponding devices has made it possible to deploy AI models successfully at the edge.</p><p dir="ltr" id="isPasted">Given their remarkable ability to process and comprehend a range of unstructured data, including visuals, audio, temperature, language, faces, and more, AI algorithms have emerged as effective solutions for problems that end users face in real-time. Yet, deploying these AI applications primarily in centralized data centers like the cloud may prove impractical, especially with concerns about latency, bandwidth, and privacy. This is where the benefits of edge applications can facilitate AI deployment with their localized nature and decentralization, enabling real-time insights, high availability, and enhanced privacy.&nbsp;</p><p dir="ltr">Nonetheless, Edge AI is not free of limitations, either. It still faces challenges, especially in data management, integration, security, miniaturization, and scalability. To overcome these challenges, a harmonious and purposeful co-design of hardware and software is necessary, and coordination with other technologies can prove quite fruitful. In fact, one of the most promising solutions for Edge Intelligence comes in the form of the convergence of Edge AI with cloud-based Wi-Fi Services, as we’ll see in the following section. Achieving miniaturization, model accuracy, energy efficiency, and cost-effectiveness simultaneously is a complex challenge. However, with proper coordination, optimization, and communication, we can facilitate the emergence of the next set of AI advancements at the edge.</p><h3 dir="ltr" id="isPasted">Next-Level Intelligence: Reinforcing Edge AI with Wi-Fi Services</h3><p dir="ltr">Since its inception about two and a half decades ago, Wi-Fi has shown significant development and adoption, with connection speeds skyrocketing from a few megabits to multi-gigabits per second. With this increase in speed, we have also seen an exponential rise in Wi-Fi-enabled devices, with almost every mobile device and computer now including Wi-Fi by default. In order to support the growing usage, demands, and throughputs of Wi-Fi, the network architecture has played a crucial role. Initially, Wi-Fi deployments were based on standalone access point architectures but later shifted to centralized hardware-based controller architectures. However, along with Wi-Fi functionalities like network optimization and mobility came some challenges, including scalability, reliability, manageability, and bottlenecks in performance, especially with increasing Wi-Fi traffic and link speeds. To tackle these challenges, service providers like Relay2 have been harnessing the power of the cloud and enabling vendors to shift from on-premise hardware controllers to cloud-native wireless controllers. Such a cloud-native system can provide the same benefits of centralized management without the constraints of physical hardware or associated adaptations. This not only enables greater flexibility but also offers more efficient and cost-effective management and coordinated control. As a result, this space has allowed for the rise of Wi-Fi-as-a-Service (WaaS), a subscription-based service that integrates software, infrastructure, and managed services to enable centralized management and coordinated control across different access points and automation of network monitoring and troubleshooting.</p><p dir="ltr">Bringing Wi-Fi services and Edge AI into the same picture, we can see how their benefits align, where Wi-Fi enhances Edge AI’s scalability and integration capabilities, and Edge AI furthers the user experience of Wi-Fi solutions with data-driven insights and real-time analysis. For instance, looking at Edge AI’s integration challenges, we can still see cases of incompatibility stemming from differences in hardware, software, and communication protocols, which result from the unique architecture, specifications, and interface of every edge device. Employing Wi-Fi at this level enables secure, wide-coverage wireless communications, which further promotes interoperability and minimizes compatibility issues. Similarly, scalability challenges in terms of how Edge AI systems are handling increasing amounts of data and devices may compromise efficiency. The adaptability and scalability brought about by Wi-Fi services can help overcome these hurdles by enlarging a business’s network infrastructure and enabling effortless infrastructure management to meet the growing demand and shifting requirements.</p><p dir="ltr">In other words, tying wireless and edge computing together can empower AI applications and reshape the business landscape to drive the digital transformation we are experiencing today. This convergence of Wi-Fi and edge computing presents a promising frontier for innovation, efficiency, and growth. As companies continue to recognize the value of this convergence, we can anticipate a marked increase in its adoption. As a result, edge computing would bring about a new wave of intelligent AI applications by integrating more computing power, which would allow adaptive learning and real-time responsiveness. This would be a significant step towards a more resilient system as the demand for always-on services continues to grow across various industries and application areas, including education, smart buildings, intelligent traffic management, smart agriculture, and smart retail. As more companies embrace the convergence of Wi-Fi and edge computing, we can expect to see a new era of technological innovation and efficiency.&nbsp;</p><p dir="ltr">Right at the center of this technological fusion is Relay2, a leading Wi-Fi service provider that is on a mission to challenge the status quo of today’s Wi-Fi access point market. Relay2 is at the vanguard of the Wi-Fi edge-computing revolution, powered by their innovative ServiceEdge Platform, a Service Points technology that provides unparalleled performance, scalability, security, and privacy across a wide range of edge applications. In the next chapter, we will dive deeper into Relay2’s Wi-Fi services and explore how Relay2 is poised to reshape the Wi-Fi industry and how its patented platform is enabling more AI applications and capabilities within the edge-computing framework.</p><p dir="ltr">This was an exceprt of Chapter 1 of the AI at the Edge: Technology Accelerated by Wi-Fi Services report. To read the full report, including in-depth case studies, download it below. &nbsp;</p><p dir="ltr"><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzA5MTI3ODU2MTAyLVJlbGF5IDIucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib"></p><p dir="ltr"><span contenteditable="false" draggable="true" class="fr-video fr-deletable fr-fvc fr-dvb fr-draggable"><iframe width="540" height="305" src="https://c8056756.sibforms.com/serve/MUIFAIgRr7nh2u88k57MUBWp43e1lkOKIXq3Z9dxFiC8kXdgaxMxkxsZKsum_gd4u7Qq4_1n-e3n6hH4X_Nw12RLp7SUWPiUkUUgLHhq84lH8VfbGGhwuM1Hvkr60WpcS1SyyBLR-7ErbMPEfKrwqo_-_-CHDFwvTGW-swKGBpTKYdEO-rdhIbTFZyt7qA8fH9zg-zqRf6Li7cOQ" frameborder="0" scrolling="auto" allowfullscreen="" style="display: block;margin-left: auto;margin-right: auto;max-width: 100%;" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe></span><br></p>

Intelligence at the Edge: Bringing AI Closer to You

AI at the Edge Report. Chapter 1: Wi-Fi Analytics Services Enabling Edge AI

<p id="isPasted">Condition Monitoring, the backbone of smart industrial maintenance, is a proactive approach that leverages advanced technologies for real-time monitoring of machine conditions. This innovative strategy is pivotal in transitioning from time-based to condition-based maintenance in industrial environments.</p><h2>Condition Monitoring</h2><p>At its core, Condition Monitoring focuses on the real-time assessment of machinery by tracking key parameters such as temperature, vibration, pressure, and other vital indicators.&nbsp;</p><p>This method stands out from traditional reactive or preventive maintenance strategies, which are either failure-induced or schedule-based. Condition Monitoring uses data analytics to identify patterns, trends, and anomalies in machine performance, thereby allowing for timely and precise maintenance interventions. This optimizes machine performance and significantly reduces the likelihood of unexpected breakdowns and associated downtime.</p><h3>Transitioning to Condition-Based Maintenance</h3><p>The shift from time-based to condition-based maintenance represents a significant advancement in industrial maintenance practices. Traditional time-based maintenance often leads to unnecessary downtime, as maintenance is performed at predetermined intervals, which may only sometimes be required.&nbsp;</p><p>In contrast, Condition Monitoring enables maintenance to be scheduled based on the actual condition of the equipment. This data-driven approach leads to more efficient resource allocation, cost savings, and improved machine longevity. It's a smarter strategy emphasizing predictive maintenance, where actions are determined by the machine's condition rather than fixed schedules.</p><h3>Advantages of Condition Monitoring</h3><ul><li><strong>Increased Equipment Reliability</strong>: Early detection of potential issues allows for proactive maintenance, minimizing unexpected failures and downtime.</li><li><strong>Optimized Maintenance Planning</strong>: Maintenance activities are more data-driven, avoiding unnecessary interventions and focusing resources where needed most.</li><li><strong>Cost Reduction</strong>: Early detection and intervention prevent minor issues from escalating into major failures, reducing overall maintenance costs.</li><li><strong>Improved Safety</strong>: Continuous monitoring of critical machine parameters helps identify potential safety hazards, ensuring a safer working environment.</li><li><strong>Enhanced Overall Equipment Efficiency</strong>: By maintaining machines in optimal condition, Condition Monitoring ensures efficient performance, reducing energy consumption and enhancing productivity.</li></ul><h3>The Process of Condition Monitoring</h3><h4>Monitoring Key Parameters</h4><p>Condition Monitoring depends on the continuous tracking of crucial machine parameters. These parameters vary across different types of machinery and industries. For instance, a manufacturing plant might focus on temperature and vibration, whereas a transportation system might monitor speed and fuel efficiency. Selecting these parameters requires a deep understanding of the machine's design, operating conditions, and potential failure modes.</p><h4>Data Collection and Analysis</h4><p>This process involves using advanced sensors and data collection systems that capture vital data points from machines. The collected data is then transmitted to a centralized system for processing and analysis. Sophisticated analytics are applied to the data to detect deviations from normal operation, enabling early intervention.</p><h2>Challenges in Condition Monitoring</h2><p>The below points outline the key challenges in implementing condition monitoring:</p><p><strong>Complex Data Collection and Integration</strong></p><ul><li>Managing data from a diverse range of sensors and machines.</li><li>Standardizing data formats across different equipment and sensors.</li><li>Integrating data from multiple sources for comprehensive analysis.</li></ul><p><strong>Scalability Issues</strong></p><ul><li>Expanding the condition monitoring system to include more machines and sensors.</li><li>Ensuring the system can handle increasing data volumes without performance degradation.</li></ul><p><strong>Infrastructure Limitations</strong></p><ul><li>Establishing robust networking capabilities to support extensive data transmission.</li><li>Implementing sufficient data storage and processing capabilities.</li><li>Providing adequate computing resources for real-time data analysis.</li></ul><p><strong>Maintenance and Operational Challenges</strong></p><ul><li>Training personnel to effectively use and interpret condition monitoring data.</li><li>Implementing effective maintenance strategies based on condition monitoring insights.</li><li>Balancing predictive maintenance with traditional maintenance approaches.</li></ul><p><strong>Cost Considerations</strong></p><ul><li>Balancing the initial investment in condition monitoring technology against long-term benefits.</li><li>Managing ongoing costs associated with system upgrades and maintenance.</li></ul><p><strong>Data Security and Privacy</strong></p><ul><li>Ensuring the security of data collected from sensors and machines.</li><li>Addressing privacy concerns, especially in sensitive industrial environments.</li></ul><p><strong>Data Analysis and Interpretation</strong></p><ul><li>Developing sophisticated analytics to accurately interpret condition monitoring data.</li><li>Turning vast amounts of data into actionable insights for maintenance decision-making.</li></ul><p>These challenges highlight the need for a strategic approach in implementing condition monitoring systems to effectively leverage their benefits for predictive maintenance and operational efficiency.</p><h2>Moving Condition Monitoring Online</h2><h3>Transition from "Walk-around" to Online Maintenance</h3><p>The traditional "walk-around" method of condition-based maintenance, where technicians manually check equipment conditions, is evolving into a more efficient, online system. This change is particularly significant in industrial settings where manual inspections can be tedious and hazardous, especially for hard-to-reach devices.&nbsp;</p><p>Online condition monitoring systems utilize permanent transducers connected to a multi-channel module for data acquisition, which then feeds into a PC-based processor station for data analysis and processing.&nbsp;</p><p>This setup enables real-time monitoring and provides high-integrity data from otherwise inaccessible machine locations. The system is designed to automatically check sensor inputs against predefined alarm levels to determine the operating status of machines. Such systems are particularly valuable for machinery considered critical to operations, located in hard-to-access or unsafe areas, or in processes requiring frequent data assessment.</p><h3>Advantages and Applications of Online Systems</h3><p>Online systems offer numerous benefits over manual inspections. They reduce the time staff need to collect data, enhance the capacity for detailed machinery analysis, and provide frequent data sampling for faster diagnostics of problems. These systems are not only more efficient but also cost-effective, as they reduce the need for portable instruments and extensive labor.&nbsp;</p><p>Online condition monitoring is ideal for processes that are event-driven or conditional, require immediate alarm notification, and where collaboration between operations and maintenance personnel is crucial.&nbsp;</p><p>The integration of online monitoring with route-based tools allows for a comprehensive maintenance strategy, combining the strengths of both methods. For instance, online systems can immediately alert technicians when a machine parameter, like vibration in a gearbox, exceeds its threshold, while handheld devices provide flexibility in data collection and analysis.</p><h3>Implementing Online Condition Monitoring</h3><p>When implementing online condition monitoring, it is essential to understand which assets and failure modes should be monitored. Decisions should be based on the number of assets and types of measurements needed. The choice of a condition monitoring solution should consider factors like scalability, openness to new analysis techniques, interoperability with existing systems, and the overall cost-effectiveness of the solution.&nbsp;</p><p>A successful online condition monitoring system involves data management, analytics, and the ability to detect reliably early indicators of potential issues. The system should balance minimizing false positives and negatives, providing actionable insights for predictive maintenance. This approach allows maintenance managers to schedule and plan maintenance only when necessary, leading to increased revenue, reduced costs, and enhanced safety.</p><p>Transitioning to online condition monitoring in smart industrial environments offers significant advantages over traditional methods. It improves efficiency, safety, and reliability while reducing costs and downtime. The integration of such systems with existing maintenance strategies is key to achieving optimal asset performance and longevity.</p><p><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzA4MzU2MzgxNzM0LWxvd3Jhb25lIDEucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 300px;" class="fr-fic fr-dib"></p><h2 id="isPasted">LoRaWAN in Condition Monitoring</h2><h3>Wired vs Wireless Condition Monitoring</h3><p>The transition from wired to wireless condition monitoring systems introduces a marked change in setup complexity and cost. Wired sensor installations typically involve intricate cabling, which can be labor-intensive and expensive. In contrast, wireless systems offer a streamlined and cost-effective solution for deploying sensors across various locations, particularly in complex industrial settings.</p><h3>LoRaWAN in the Wireless Landscape</h3><p>LoRaWAN emerges as a formidable option in the wireless technology arena, especially when compared to other wireless protocols like Wi-Fi, Bluetooth/Bluetooth Low Energy (BLE), and LTE (Long-Term Evolution). Each of these technologies has its strengths and limitations, influenced by their inherent design to balance range, power consumption, and bandwidth.</p><ul><li><strong>Wi-Fi</strong>: While Wi-Fi excels in high bandwidth, it is limited by shorter range (often not extending beyond 15 meters) and higher power consumption, making it less suitable for scattered IoT devices.</li><li><strong>Bluetooth/BLE</strong>: Similar to Wi-Fi, Bluetooth and BLE are more focused on short-range communication. They are ideal for small-scale consumer IoT applications but may not be the best fit for industrial IoT due to their limited range.</li><li><strong>LTE</strong>: Cellular technologies like LTE offer broader coverage and support for both low and high transmission bandwidths. However, they may involve higher power consumption compared to LPWAN (Low Power Wide Area Network) technologies like LoRaWAN.</li></ul><p>&nbsp;<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzA4MzU2NDIxNTAyLWxvd3Jhb25lIDIucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 300px;" class="fr-fic fr-dib"></p><p id="isPasted">LoRaWAN, with its long-range capability (several kilometers) and low power consumption, is uniquely positioned for condition monitoring applications. This technology is particularly efficient in sending small packets of data, such as those required for monitoring temperature, humidity, and other environmental variables. Devices on a LoRaWAN network can operate for years on a single battery charge, thanks to its low power design. Additionally, LoRaWAN's star network topology, where each device node communicates with a specific gateway, makes it a robust choice for IoT deployments in varied and challenging environments.&nbsp;<iframe id="65ba23f2cb56854ce719756b" width="250" class="specs-iframe" height="440" src="https://wevolver.com/iframe/specs/advantech-wise-2410sk-na-starter-kit?iframe=true" frameborder="0" scrolling="no" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe></p><p>In the context of IoT, LoRaWAN's advantages are evident when considering the requirements of different use cases. For instance, its ability to efficiently handle small data packets over long distances makes it an excellent choice for applications like asset tracking, environmental monitoring, and smart agriculture.&nbsp;</p><p>On the other hand, technologies like Wi-Fi and BLE might be more suitable for scenarios requiring higher data throughput over shorter distances, such as in smart homes or retail settings.</p><h2>Conclusion</h2><p>LoRaWAN Wireless Condition Monitoring represents a significant leap forward in industrial maintenance. By transitioning from time-based to condition-based maintenance, it offers a more efficient, cost-effective, and data-driven approach. This technology stands out in its ability to facilitate real-time tracking of key machine parameters like temperature, vibration, and pressure, thus enabling predictive maintenance.</p><p>LoRaWAN, with its long-range, low power capabilities, is particularly suited for this task, overcoming the limitations of traditional wired systems and other wireless technologies like Wi-Fi, Bluetooth, and LTE.&nbsp;</p><p>Despite facing challenges such as data integration, scalability, and infrastructure demands, the benefits—increased equipment reliability, optimized maintenance planning, cost reduction, improved safety, and enhanced overall efficiency—make it an invaluable tool in modern industrial environments.&nbsp;</p><p>As industries increasingly adopt smart technologies, LoRaWAN Wireless Condition Monitoring emerges as a pivotal solution for advancing operational excellence and sustainability in the ever-evolving landscape of industrial maintenance.</p><h2>&nbsp;References</h2><ol start="1" type="1"><li><a href="https://sensemore.io/condition-monitoring-smarter-future-in-industrial-maintenance/" target="_blank">https://sensemore.io/condition-monitoring-smarter-future-in-industrial-maintenance/</a></li><li><a href="https://www.iotforall.com/condition-monitoring-via-lorawan" target="_blank">https://www.iotforall.com/condition-monitoring-via-lorawan</a></li><li><a href="https://www.mokolora.com/lora-and-wireless-technologies/" target="_blank">https://www.mokolora.com/lora-and-wireless-technologies/</a></li><li><a href="https://blog.pruftechnik.com/the-advantages-of-online-and-route-based-condition-monitoring-tools/" target="_blank">https://blog.pruftechnik.com/the-advantages-of-online-and-route-based-condition-monitoring-tools/</a></li><li><a href="https://www.plantservices.com/monitoring/condition-monitoring/article/11292115/addressing-challenges-of-online-condition-monitoring" target="_blank">https://www.plantservices.com/monitoring/condition-monitoring/article/11292115/addressing-challenges-of-online-condition-monitoring</a></li><li><a href="https://reliabilityweb.com/articles/entry/transitions" target="_blank">https://reliabilityweb.com/articles/entry/transitions</a></li><li><a href="https://www.flir.com/discover/professional-tools/what-is-condition-monitoring-guide/" target="_blank">https://www.flir.com/discover/professional-tools/what-is-condition-monitoring-guide/</a></li></ol>

Condition Monitoring with LoRaWAN: A guide to its effectiveness in industrial maintenance, the transition from traditional methods, and overcoming implementation challenges

LoRaWAN Wireless Condition Monitoring

<h2 dir="ltr">Introduction</h2><p dir="ltr">To successfully deploy Edge AI applications with real-time capabilities and low latency, it is crucial to have access to high bandwidth connectivity that operates at ultra-fast speeds. This is where Wi-Fi comes into play. Deploying Wi-Fi technologies enhances Edge AI’s real-time analysis and reinforces its ability to proactively respond to diverse scenarios with minimal latency and higher bandwidth efficiency. Wi-Fi deployment is further streamlined by an advanced Wi-Fi-as-a-service (WaaS) business model.&nbsp;</p><p dir="ltr">Our new report, <strong>AI at the Edge: Technology Accelerated by Wi-Fi Services</strong>, dives deeply into the convergence of Wi-Fi services and Edge AI and explores how a technology model like WaaS can accelerate the adoption of AI at the edge.&nbsp;</p><p dir="ltr">Download the full 40-page report below.&nbsp;</p><p dir="ltr">&lt;image&gt;</p><p dir="ltr">Form.</p><h3 dir="ltr" id="isPasted">Leading the Digital Transformation with Edge AI and Wi-Fi-as-a-Service</h3><p dir="ltr">The report explore's how Relay2 is serving the global market and learn about its ServiceEdge Platform and PartnerConnect Program. We will also take a good look at some notable use cases of these technologies, including education, healthcare, and retail, and finally peek into the future of Edge AI and Wi-Fi.&nbsp;</p><p dir="ltr">This report aims to provide a comprehensive, in-depth analysis of how marrying Edge AI with cloud-managed Wi-Fi services will drive the growth of smart and lightweight infrastructure markets and create a smarter connected world with unified wireless access and an application computing platform.</p><blockquote><p dir="ltr">“Relay2 is pioneering the convergence of Wi-Fi and Edge Computing, fortifying industries to provide smarter and better-connected services, enhanced security, safety, and privacy, along with operational efficiency and cost optimization.” - Eric Chen, Founder &amp; CEO at Relay2</p></blockquote><p dir="ltr">Don't miss out on this comprehensive guide and detailed case studies. Download your copy now.&nbsp;</p><p dir="ltr" id="isPasted">&lt;image&gt;</p><p dir="ltr">Form.</p><h3 dir="ltr">Read excerpts of the report chapters here:</h3><p dir="ltr" id="isPasted">Chapter 1: Wi-Fi Services Enabling Edge AI</p><p dir="ltr" id="isPasted">Chapter 2: Relay2 and Edge AI</p><p>Chapter 3: Applications &amp; Case Studies</p><p dir="ltr" id="isPasted">Chapter 4: Future of Edge AI with Wi-Fi Technology</p><p>Conclusion: Wi-Fi-Powered Edge AI - A Technology for the Future</p>

<h2 dir="ltr">Introduction</h2><p dir="ltr">To successfully deploy Edge AI applications with real-time capabilities and low latency, it is crucial to have access to high bandwidth connectivity that operates at ultra-fast speeds. This is where Wi-Fi comes into play. Deploying Wi-Fi technologies enhances Edge AI’s real-time analysis and reinforces its ability to proactively respond to diverse scenarios with minimal latency and higher bandwidth efficiency. Wi-Fi deployment is further streamlined by an advanced Wi-Fi-as-a-service (WaaS) business model.&nbsp;</p><p dir="ltr">Our new report, <strong>AI at the Edge: Technology Accelerated by Wi-Fi Services</strong>, dives deeply into the convergence of Wi-Fi services and Edge AI and explores how a technology model like WaaS can accelerate the adoption of AI at the edge.&nbsp;</p><p dir="ltr">Download the full 40-page report below.&nbsp;</p><p dir="ltr"><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1708692972720-Relay+final+%281%29.png" style="width: 300px;" class="fr-fic fr-dib"></p><p dir="ltr"><span contenteditable="false" draggable="true" class="fr-video fr-deletable fr-fvc fr-dvb fr-draggable fr-active"><iframe src="https://c8056756.sibforms.com/serve/MUIFAHQ1RzmRq2C4LLaGIyc0SIbhplZVhzapUbUp7RqKP5Lt2roTAWGSz62uJMz4fNFeLGuhZI97irHq9J_4pLu2XbIx9FlrN9A8Gsmo11v03ozf6Qw83e4mk2E2ZWFuzWXMvR6NTo85ClJnyc7jmTIUWK4mQh9GbC-v_4SSumcw_XE_GIVo3OrFmb2b8rsyUNlGSVHQ7quSTDwC" frameborder="0" scrolling="auto" allowfullscreen="" style="display: block; margin-left: auto; margin-right: auto; max-width: 100%; width: 540px; height: 455px;" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe></span><br></p><h3 dir="ltr" id="isPasted">Leading the Digital Transformation with Edge AI and Wi-Fi-as-a-Service</h3><p dir="ltr">The report explores how Relay2 is serving the global market and learns about its ServiceEdge Platform and PartnerConnect Program. We will also take a good look at some notable use cases of these technologies, including education, healthcare, and retail, and finally peek into the future of Edge AI and Wi-Fi.&nbsp;</p><p dir="ltr">This report aims to provide a comprehensive, in-depth analysis of how marrying Edge AI with cloud-managed Wi-Fi services will drive the growth of smart and lightweight infrastructure markets and create a smarter connected world with unified wireless access and an application computing platform.</p><blockquote><p dir="ltr">“Relay2 is pioneering the convergence of Wi-Fi and Edge Computing, fortifying industries to provide smarter and better-connected services, enhanced security, safety, and privacy, along with operational efficiency and cost optimization.” - Eric Chen, Founder &amp; CEO at Relay2</p></blockquote><p dir="ltr">Don't miss out on this comprehensive report with detailed case studies. Download your copy now.&nbsp;</p><p dir="ltr" id="isPasted"><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1708693065073-relay+final+3+%281%29.png" style="width: 300px;" class="fr-fic fr-dib"></p><p dir="ltr"><span contenteditable="false" draggable="true" class="fr-video fr-deletable fr-fvc fr-dvb fr-draggable"><iframe src="https://c8056756.sibforms.com/serve/MUIFAHQ1RzmRq2C4LLaGIyc0SIbhplZVhzapUbUp7RqKP5Lt2roTAWGSz62uJMz4fNFeLGuhZI97irHq9J_4pLu2XbIx9FlrN9A8Gsmo11v03ozf6Qw83e4mk2E2ZWFuzWXMvR6NTo85ClJnyc7jmTIUWK4mQh9GbC-v_4SSumcw_XE_GIVo3OrFmb2b8rsyUNlGSVHQ7quSTDwC" frameborder="0" scrolling="auto" allowfullscreen="" style="display: block; margin-left: auto; margin-right: auto; max-width: 100%; width: 540px; height: 455px;" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true"></iframe></span><br></p><h3 dir="ltr">Read excerpts of the report chapters as they are released:</h3><p dir="ltr" id="isPasted">Chapter 1: Wi-Fi Services Enabling Edge AI (Coming soon)</p><p dir="ltr" id="isPasted">Chapter 2: Relay2 and Edge AI (Coming soon)</p><p>Chapter 3: Applications &amp; Case Studies (Coming soon)</p><p dir="ltr" id="isPasted">Chapter 4: Future of Edge AI with Wi-Fi Technology (Coming soon)</p><p>Conclusion: Wi-Fi-Powered Edge AI - A Technology for the Future (Coming soon)</p>

Introduction

Leading the Digital Transformation with Edge AI and Wi-Fi Networking

AI at the Edge: Technology Accelerated by Wi-Fi Services

<p id="isPasted"><span data-contrast="auto" lang="EN-US">Bluetooth&nbsp;LE, Wi-Fi&nbsp;6,</span><span data-contrast="auto" lang="EN-US">&nbsp;and cellular IoT bring connectivity to low power IoT devices. The Nordic SoCs, companion ICs, and SiPs running these protocols are among the most power efficient wireless solutions on the market, extending devices’ battery life.</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span></p><p><span data-contrast="auto" lang="EN-US">But there’s more to managing power than just efficient chips; power from a battery or a mains source must be regulated and distributed, and if the device is powered by a rechargeable battery, it will occasionally need to be charged. That means no matter how efficient the processor, radio, and memory are in the wireless chip, a less-than-optimized power management system will compromise battery life.&nbsp;</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span></p><h2><span data-contrast="auto" lang="EN-US">Building a compact power management system&nbsp;Into&nbsp;one small package</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span></h2><p><span data-contrast="auto">Building an efficient power management system is one problem, designing it to be compact makes things even more challenging. Many IoT products are space constrained, yet conventional power management solutions typically comprise multiple chips—for example, voltage regulator, battery charger, fuel gauge, external watchdog, and hard reset—which take up precious space.</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span></p><p><span data-contrast="auto">Nordic has addressed both the efficiency and space challenges of power management with its nPM Family of&nbsp;</span><a href="https://www.nordicsemi.com/Products/Supplementary/Power-Management" target="_blank"><span data-contrast="none">Power Management ICs</span></a><span data-contrast="auto">&nbsp;(PMICs). The family comprises the nPM6001 (which features six independently controlled power rails), nPM1100 (a dual-mode configurable buck regulator and integrated battery charger) and the latest introduction, the nPM1300. This PMIC is optimized for maximum efficiency and compact size and simplifies system design by integrating the essential functions required for reliable operation into one small package.</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span></p><h2><span data-contrast="auto" lang="EN-US">Intelligent power management from the nPM1300</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span></h2><p><span data-contrast="auto">Within its 5 by 5 mm (QFN32) or 3.1 by 2.4 mm (WLCSP) compact form factor, the nPM1300 incorporates two buck converters, two load switches, a battery charger, USB-C compatible input, ship mode, and fuel gauge. This simplifies power management from as many as eight chips plus associated passives to one chip plus a few passives.</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span></p><p><span data-contrast="auto">In addition to the high level of integration, the PMIC provides key system management features that typically must be individually added to conventional power management circuits. These features include key items such as failed boot recovery, hard reset, a power saving ‘hibernate’ mode, watchdog timer, and a power loss warning.</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span></p><h2><span data-contrast="auto" lang="EN-US">Precise fuel gauging without the power drain</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span></h2><p><span data-contrast="auto">It’s very useful for a consumer to have an accurate idea of the remaining battery life of their IoT device. Engineers typically achieve this by measuring the battery voltage—which is a proxy for remaining energy—or, for a more precise result, a coulomb counter, a device that continuously measures the current flowing into or out of a battery to determine the total cell charge.&nbsp;</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span></p><p><span data-contrast="auto">The battery voltage measurement is simple to implement and uses little power, but is not very accurate, particularly if the battery is subject to temperature variances. The coulomb counter is more precise but requires additional components and drains more power. In comparison, the nPM1300 features a highly accurate fuel gauge that combines the simplicity and modest power consumption of a battery voltage measurement with the precision of a coulomb counter.&nbsp;</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span></p><p><span data-contrast="auto">Nordic conducted experiments that compared a coulomb counter, battery voltage measurement, and the nPM1300’s fuel gauge. Compared to the coulomb counter, the battery voltage calculation peaked at nearly 20 percent error. In comparison, the nPM1300’s fuel gauge showed a maximum of two percent error at worst compared with the coulomb counter but was mostly within one percent.&nbsp;</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span></p><h2><span data-contrast="auto" lang="EN-US">Fuel gauge powered by software</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span></h2><p><span data-contrast="auto">The key to Nordic’s fuel gauge’s accuracy over a wide temperature range is the software algorithm powered by the host processor. The processor uses information such as the current flowing out of the battery, the battery terminal voltage, the system voltage, and a battery temperature thermistor reading.</span><span data-contrast="none">&nbsp;</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span></p><p><span data-contrast="none">For the algorithm to produce accurate results it must first be ‘taught’ the battery characteristics (which only has to happen once if the end product continues to use the same type of battery). The teaching is done using the Nordic&nbsp;</span><a href="https://www.nordicsemi.com/Products/Development-hardware/nPM1300-EK" target="_blank"><span data-contrast="none">Evaluation Kit</span></a><span data-contrast="none">&nbsp;(EK) equipped with a fuel gauge board to provide the right resistive load and the Nordic nPM PowerUP App.</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span></p><p><span data-contrast="none">After calibration and with the current, voltage, and temperature inputs, the host processor uses the Nordic-developed algorithm to accurately determine the battery’s state of charge for the life of the device. Power consumption for a one-second measurement frequency adds about four microamps to the typical host processor overhead.</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span></p><h2><span data-contrast="none" lang="EN-US">Managing power from&nbsp;battery to antenna</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span></h2><p><span data-contrast="auto">Maximizing battery life demands taking responsibility for how each part of the wireless product’s system affects the overall power consumption. The developer needs to optimize each element—from the battery all the way to Cloud connectivity, including radio operation, processing, and power management—to get the most from the power source. &nbsp;</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span><span data-contrast="auto">&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</span></p><p><span data-contrast="auto">Basing a design on a Nordic SoC or SiP—among the lowest power wireless chips on the market—together with a Nordic nPM6001, nPM1100, or nPM1300 is an excellent foundation for keeping the energy consumption of wireless products as low as possible.&nbsp;</span></p>

Bluetooth LE, Wi-Fi 6, and cellular IoT bring connectivity to low power IoT devices. The Nordic SoCs, companion ICs, and SiPs running these protocols are among the most power efficient wireless solutions on the market, extending devices’ battery life. 

Inside the next generation of efficient and compact power management

<p id="isPasted"><span data-contrast="auto" lang="EN-US"><strong>Every&nbsp;day, the average</strong></span><span data-contrast="auto" lang="EN-US"><strong>&nbsp;person inhales a staggering 11,000 liters of air</strong></span><span data-contrast="none" lang="EN-US"><strong>,&nbsp;</strong></span><span data-contrast="auto" lang="EN-US"><strong>amounting to more than 300 million liters over a lifetime (as reported by&nbsp;</strong></span><strong><em><span data-contrast="auto" lang="EN-US">TheWorldCounts</span></em></strong><span data-contrast="auto" lang="EN-US"><strong>).</strong></span></p><p><span data-contrast="auto">This remarkable intake underscores the importance of ensuring the air we breathe is fresh and clean, especially since</span><span data-contrast="none">, a</span><span data-contrast="auto">ccording to the World Health Organization, there are over 6.7 million premature deaths annually due to air pollution, with more than 3.2 million of these stemming from indoor environments. &nbsp;</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span></p><p><span data-contrast="auto">Despite the common focus on outdoor air pollution, significant health risks also originate from the air indoors. With people spending increasing amounts of time inside homes, offices, shops, gyms and restaurants</span><span data-contrast="none">&nbsp;</span><span data-contrast="auto">it has become even more important to monitor the air quality of these environments.</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span></p><h2><span data-contrast="auto" lang="EN-US">The next phase of air quality monitoring&nbsp;</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span></h2><p><span data-contrast="auto" lang="EN-US">Carbon monoxide alarms have been around for&nbsp;almost a&nbsp;century,&nbsp;while&nbsp;traditional&nbsp;smoke detectors&nbsp;have been around for over seventy years</span><span data-contrast="none" lang="EN-US">. But wireless technology represents a new level of air quality measurement. For example,&nbsp;</span><span data-contrast="auto" lang="EN-US">whereas&nbsp;previously conventional&nbsp;alarms&nbsp;only&nbsp;issued warnings when dangerous levels&nbsp;of carbon monoxide or smoke&nbsp;were detected, the advent of wireless technology&nbsp;allows&nbsp;for&nbsp;a more nuanced and&nbsp;timely&nbsp;response&nbsp;to potential hazards, especially in cases of long-term, low-level exposure.</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span></p><p><span data-contrast="auto">The effects of such exposure shouldn’t be taken lightly. According to an article by Julie Connolly, Senior Lecturer in Health and Social Care at Liverpool John Moores University, the symptoms of low-level carbon monoxide exposure can be difficult to spot</span><span data-contrast="none">. And yet,&nbsp;</span><span data-contrast="auto">they have been linked to such serious symptoms as musculoskeletal injury, fatigue, and memory loss.&nbsp;</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span></p><p><span data-contrast="auto">Beyond concerns like natural gas leaks, or carbon monoxide, carbon dioxide, and smoke build-up, humans present risks to fellow humans through viruses (such as COVID-19 or influenza). And certain strains of bacteria and mold spores also pose a threat to air quality.</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span></p><p><span data-contrast="auto">One of the most serious threats, however, is from Volatile Organic Compounds (VOCs). These can lead to serious health issues, including eye, nose, and throat irritation, headaches, loss of coordination, nausea, and potential damage to the liver, kidneys, and central nervous system (according to the U.S. Environmental Protection Agency). Worse still, some VOCs have even been linked to cancer.</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span></p><h2><span data-contrast="auto" lang="EN-US">Creating smart&nbsp;IoT&nbsp;systems&nbsp;for air&nbsp;quality monitoring</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span></h2><p><span data-contrast="auto">Now the IoT can be used to alert building occupants of these hazards, in near real-time. This allows individuals and companies to proactively implement changes to help ensure healthy indoor environments and prevent health problems.</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span></p><p><span data-contrast="auto">Moreover, smart air purification and filtration systems can be integrated into smart home systems or an intelligent HVAC (Heating, Ventilation, and Air Conditioning) unit in a commercial building. A feedback loop can then be formed between the sensor network and the air purification system. When sensors detect the air quality dropping the system can automatically boost purification.&nbsp;</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span></p><h2><span data-contrast="auto" lang="EN-US">The advantages of Bluetooth LE and Wi-Fi&nbsp;</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span></h2><p><span data-contrast="auto">There are many advantages of employing wireless technology in these applications. Technology such as&nbsp;</span><a href="https://www.nordicsemi.com/Products/Wireless/Bluetooth-Low-Energy" target="_blank"><span data-contrast="none">Bluetooth LE</span></a><span data-contrast="auto">&nbsp;suits compact, low-power sensors working over hundreds of meters while low-power&nbsp;</span><a href="https://www.nordicsemi.com/Products/Wireless/WiFi" target="_blank"><span data-contrast="none">Wi-Fi</span></a><span data-contrast="auto">&nbsp;technology such as Nordic’s nRF70 Series suits sensors that need a bit more bandwidth. Bluetooth LE and Wi-Fi can also work together in gateways, with the Bluetooth LE signal coming from a network of sensors, while the Wi-Fi part of the gateway sends the data to the Cloud. &nbsp;</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span></p><p><span data-contrast="auto">Because these solutions need no wiring, they are simple to integrate into new builds or retrofit existing buildings. Compact, battery-powered sensors (such as carbon monoxide detectors) can easily be strategically installed near fossil-fuel heaters, in rooms with poor ventilation, and in other areas of concern.</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span></p><p><span data-contrast="auto">Once these sensors have been set up, they continuously gather data. Edge computing enables the device to only forward information to a gateway or central device when significant to trigger further decisions such as increasing ventilation. Alternatively, the data can be sent directly to the user’s smartphone via Bluetooth LE for instant notifications. Multiple types of sensors and wireless tech enable users to build the optimum solution for the application. &nbsp;</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span></p><h2><span data-contrast="auto" lang="EN-US">Nordic Bluetooth LE SoCs power multisensory air quality monitor &nbsp;</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span></h2><p><span data-contrast="auto">For example, the&nbsp;</span><a href="https://www.nordicsemi.com/Nordic-news/2023/10/The-AirSuite-Glance-environment-monitor-employs-the-nRF9160-SiP-and-nRF52840-SoC" target="_blank"><span data-contrast="none">AirSuite Glance</span></a><span data-contrast="auto">, created by New Zealand company AirSuite, employs a range of sensors to monitor carbon dioxide (CO</span><span data-contrast="auto">2</span><span data-contrast="auto">), temperature, humidity, sound, lighting, air pressure, and volatile organic compounds (VOCs). It uses the Bluetooth LE connectivity provided by Nordic Semiconductor’s&nbsp;</span><a href="https://www.nordicsemi.com/products/nrf52840" target="_blank"><span data-contrast="none">nRF52840</span></a><span data-contrast="auto">&nbsp;SoC to transmit the data directly to the user’s smartphone every minute, and the LTE-M or NB-IoT connectivity of the&nbsp;</span><a href="https://www.nordicsemi.com/products/nrf9160" target="_blank"><span data-contrast="none">nRF9160</span></a><span data-contrast="auto">&nbsp;SiP to send it to the Cloud at least every fifteen minutes.</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span></p><p><span data-contrast="auto">Through the dedicated app and web platform, users can oversee and receive notifications when environmental metrics surpass or fall below predetermined thresholds. Additionally, the AirSuite Monitor Web Portal offers access to historical data, allowing users to analyze trends and compare values across various rooms or sites.</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span></p><h2><span data-contrast="auto" lang="EN-US">Intelligent adjustment with machine learning &nbsp;</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span></h2><p><span data-contrast="auto">There are many innovations currently shaping the landscape of indoor air quality monitoring. Notably, the development of more advanced wireless sensors—low power devices that can run for years between battery replacements—and the advancement of Machine Learning (ML)-driven analytics.&nbsp;</span><span data-ccp-props='{"201341983":0,"335559739":160,"335559740":259}'>&nbsp;</span></p><p><span data-contrast="auto">ML, with its pattern recognition capabilities, can identify trends, and intelligently adjust settings to optimize occupant health and comfort. The system can autonomously adjust settings in response to</span><span data-contrast="none">&nbsp;certain stimuli—</span><span data-contrast="auto">such as switching on an air purifier in anticipation of the increased building occupancy expected at certain times of the day. This reduces power consumption by avoiding unnecessary equipment use and helps create indoor environments that can be continually optimized for the occupants’ wellbeing.</span></p>

Every day, the average person inhales a staggering 11,000 liters of air, amounting to more than 300 million liters over a lifetime (as reported by TheWorldCounts).

Smart wireless IoT systems for air quality monitoring

<h2 dir="ltr" id="isPasted">Getting Started with Matter</h2><p dir="ltr" id="isPasted">This episode focuses on Matter, a universal smart home standard, and delves into various aspects crucial for engineers and companies looking to adopt this technology. <a href="https://www.wevolver.com/article/the-tech-between-us-podcast-exploring-the-matter-protocol-for-a-smarter-home/draft" target="_blank" rel="noopener noreferrer">Listen to the first part here.&nbsp;</a></p><p dir="ltr">A significant part of the discussion revolves around the practical steps for engineers and companies to begin working with Matter. Chris LaPré emphasizes the accessibility of the Matter Software Development Kit (SDK), available on GitHub. He notes that this tool makes it easier to build simpler devices like light bulbs and smart plugs. Additionally, the CSA team is developing videos and documentation to assist engineers in creating more complex devices, highlighting the supportive resources available.</p><h3 dir="ltr">Understanding the Matter Specification</h3><p dir="ltr">An interesting point Chris makes is that while Matter uses the ZigBee cluster library for its device data model, in-depth knowledge of ZigBee isn’t a prerequisite for designing Matter-compatible devices. This aspect significantly lowers the barrier to entry for engineers and developers looking to implement Matter in their designs.</p><p>The conversation also covers technical aspects, like the OSI model layers, explaining that Matter operates above UDP and relies on transport protocols such as Wi-Fi and Thread. This technical discussion provides listeners with a deeper understanding of how Matter fits into the broader context of network communication.</p><p><a href="https://www.wevolver.com/article/matter-the-future-of-smart-home-connectivity-and-its-impact-on-product-development" target="_blank" rel="noopener noreferrer">Explore more on Matter here. </a></p><h3>CSA Working Groups: From ZigBee to Data Privacy</h3><p>Raymond and Chris highlight the different working groups within the CSA, including those focused on ZigBee, the data model group, product security, and data privacy. These groups play a pivotal role in the ongoing development and refinement of Matter and related standards.</p><p>One of the episode's key takeaways is the CSA's commitment to developing a robust product security standard, informed by external standards, and a data privacy framework. These initiatives aim to offer clearer comparisons and transparency regarding how companies handle user data. The ultimate goal, as Chris elucidates, is to bolster consumer confidence in IoT devices by ensuring interoperability, robust product security, and stringent data privacy measures.</p><p>Overall, this episode of "The Tech Between Us" provides valuable insights into the evolving world of smart home technology, particularly focusing on the Matter standard. It offers a blend of practical advice for professionals in the field and a deeper understanding of the technological underpinnings for enthusiasts and consumers interested in the future of IoT and smart home devices.</p>

In a fascinating follow-up episode of "The Tech Between Us," host Raymond Yin continues his engaging conversation with Chris LaPré, Chief Technical Officer at the Connectivity Standards Alliance (CSA). 

The Tech Between Us Podcast: Exploring the Matter Protocol for a Smarter Home. Part II

<p dir="ltr" id="isPasted"><iframe id="652e6bda405966a620c0bedf" width="250" class="specs-iframe" height="440" src="https://wevolver.com/iframe/specs/nordic-semiconductor-nrf7002-dk-wi-fi-6-development-kit?iframe=true" frameborder="0" scrolling="no"></iframe>In this episode of <a href="https://www.youtube.com/playlist?list=PLBFFfxVbvpNTzubC_bkcurRZ5bUWCfwSu" target="_blank" rel="noopener noreferrer">The Tech Between Us</a>, podcast guest host Mark Patrick, Technical Content Director for EMEA at Mouser Electronics, joins Bruno Tomas, CTO of the Wireless Broadband Alliance (WBA), to discuss the future of communications with WiFi7.&nbsp;</p><p dir="ltr">The podcast delves into WiFi7, the latest connectivity standard, exploring its potential to drastically improve latency, speed, and jitter. This advancement is set to enhance a range of applications, from immersive AR/VR experiences to smoother video streaming and cloud gaming, marking a significant transformation in the wireless communication landscape.&nbsp;</p><p dir="ltr">Listen to the informative interview above or read more about <a href="https://www.wevolver.com/article/a-short-guide-to-the-next-generation-of-wireless-connectivity-wi-fi-7" target="_blank" rel="noopener noreferrer">WiFI 7 here.</a></p><p dir="ltr"><a href="https://www.wevolver.com/article/a-short-guide-to-the-next-generation-of-wireless-connectivity-wi-fi-7" target="_blank" rel="noopener noreferrer"></a></p><h3 dir="ltr">About the &nbsp;"The Tech Between Us" Podcast:</h3><p dir="ltr">"The Tech Between Us" is a podcast series focused on exploring the latest trends and innovations in technology. Each episode features insightful discussions with industry experts, thought leaders, and technology professionals hosted by Raymond Yin. The podcast covers a wide range of topics, from advancements in connectivity, like WiFi7, to emerging technologies in smart homes and beyond. It aims to provide listeners with a deeper understanding of how technology is evolving and impacting our world, both in everyday life and in complex industrial applications. The show is known for its engaging conversations, expert insights, and ability to break down complex technical concepts into understandable and relatable content for its audience.</p><p dir="ltr"><a href="https://www.youtube.com/playlist?list=PLBFFfxVbvpNTzubC_bkcurRZ5bUWCfwSu" target="_blank" rel="noopener noreferrer">Listen to more episodes here.</a></p>

Discover the technical and application details of the latest WiFi standard.


The Tech Between Us Podcast: Exploring WiFi 7 with Bruno Tomas

<p id="isPasted">In the modern era it’s reasonable to assume that expensive items moving around the world are carefully tracked and protected and therefore never go astray. But no, there are still a disturbing number of mishaps resulting in key assets disappearing – sometimes forever. For instance, Popular Mechanics magazine reports over one million spare parts needed to keep F-35 fighter aircrafts in the air have gone missing, with an estimated total value of at least $85 million.</p><p>Fighter aircraft are one thing, but the challenge of knowing where everything is becomes vastly more complex when scaled up to myriad items being transported across vast distances. For example, some 68 million containers are used to move cargo around the world (according to statista) and any one could contain millions of dollars of manufactured goods or materials. Keeping track of these assets is a logistical nightmare for companies. Wireless tech is providing the answers.&nbsp;</p><h2>Navigation and tracking using GPS</h2><p>One tech solution is the Global Positioning System (GPS) - the principal component of Global Navigation Satellite System (GNSS). Billions of people already rely on GNSS daily to help them find their way around, and it’s now also providing a foundation for many IoT applications to help keep track of valuable assets that might otherwise go missing.</p><p>Made up of 24 satellites positioned around 20,000 kilometers above the Earth, the GPS constellation is arranged to ensure four satellites can be observed at any point on the planet. These satellites transmit their locations, status, and the precise time from onboard atomic clocks to an earthbound GPS receiver. The receiver notes the arrival time of the signal and then calculates the distance to each satellite (using the time difference between signal transmission and reception, and then multiplying by the speed of light). Information from four satellites can then be used to pinpoint the receiver’s position on the surface of the planet. Attach the receiver to the valuable cargo and you’ll always know where it is.&nbsp;</p><h2>The challenges of GNSS</h2><p>Well, perhaps not quite always. Despite its sophisticated design, GNSS is still subject to several issues. For instance, inaccuracies with the onboard clocks can cause timing errors. To combat these issues, GNSS systems compare multiple satellites and use algorithms to determine which clocks are in error and then reset them.<br>Other problems occur because the relatively weak signal between satellites and earthbound receivers can easily be disrupted. With an average GPS signal strength at Earth’s surface of just -130 dBm (as reported by gps-repeaters.com), obstructions such as rows of tall buildings—known as ‘urban canyons’—can block the transmission.</p><p>And even in instances when the data is successfully transmitted, so-called multipath errors can occur. These involve the signal reflecting off buildings before reaching the receiver, causing timing errors and leading to incorrect positional information. Other errors can occur because of density variations in the Earth’s atmosphere, which can delay or distort the GNSS signal.</p><p>Electromagnetic interference (EMI) from other radio sources can also cause timing errors. To mitigate these problems, techniques such as filtering, correlation, and signal power measurement, as well as ionosphere and troposphere modeling, are employed. But despite all this technology there are times when GNSS just doesn’t work and logistics companies need alternatives to keep track of everything.</p><h2>Maximizing battery life with Wi-Fi SSID scanning</h2><p>Another downside of GNSS is that it can take several minutes to determine the initial location of a tracked item - taking a heavy toll on batteries. Some relief for the power source can come from using technologies such as Assisted- and Predicted-GPS (A-GPS and P-GPS). These methods, supported by Nordic’s <a href="https://www.nordicsemi.com/Products/Cloud-services" rel="noopener" target="_blank">nRF Cloud Location Services</a> in conjunction with the company’s <a href="https://www.nordicsemi.com/Products/nRF9160" rel="noopener" target="_blank">nRF9160 SiP</a>, a multimode cellular IoT solution, use satellite assistance data stored in a database. This information is transmitted to the nRF9160 via the LTE-M or NB-IoT network, speeding up the first satellite fix and saving power.</p><p>But even with A-GPS and P-GPS, the battery requirements for GNSS remain significant. This becomes important consideration for certain applications, such asset trackers that are typically equipped with smaller batteries while still requiring long lifetimes. If you need precision down to few meters, only GNSS will do, but if accuracy of tens of meters is acceptable, there are alternatives that can lead to reduced power requirements.&nbsp;</p><p>One such locationing technique, which provides a reasonably precise alternative to GNSS while also consuming less power, is Wi-Fi Service Set Identifier (SSID) scanning. Every Wi-Fi access point (AP) network is identified with an SSID - a technical reference for the AP’s name. With knowledge of the network’s SSID, it’s possible to cross reference against databases that will detail its location.&nbsp;</p><p>Wi-Fi chips such as Nordic’s <a href="https://www.nordicsemi.com/Products/WiFi/Products#infotabs" rel="noopener" target="_blank">nRF70 Series</a> of companion ICs devices can use the technique to determine location by scanning any nearby Wi-Fi AP for its SSID. In the Nordic case, a partner nRF9160 SiP can then forward the SSID (and other useful information) to nRF Cloud using cellular connectivity. nRF Cloud then checks one or more Wi-Fi SSID databases and returns the tracked item’s location based on the position of nearby APs, plus a degree of uncertainty for that location, either to the nRF9160 or elsewhere as directed.&nbsp;</p><h2>Striking the right balance between precision and battery life with Wi-Fi locationing</h2><p>While it’s hard to beat the accuracy of GNSS, when a slightly lower precision is acceptable and battery life is critical, or in asset tracking applications where the GNSS signal is likely to be interrupted, Wi-Fi SSID locationing is an excellent alternative.&nbsp;</p><p>With Nordic’s nRF91 and nRF70 Series, and nRF Cloud, it’s simple to switch seamlessly between GNSS and Wi-Fi locationing methods in an asset tracker to trade-off location precision against battery life to best suit the situation. There is now no excuse for the loss of expensive aircraft parts or any other valuable assets.</p><hr id="isPasted"><p>This article was first published on Nordic's <a href="https://blog.nordicsemi.com/getconnected" target="_blank" rel="nofollow"></a><a href="https://blog.nordicsemi.com/getconnected?utm_campaign=2021%20wevolver" target="_blank" rel="nofollow">Get Connected Blog</a>. &nbsp;</p>

In the modern era it’s reasonable to assume that expensive items moving around the world are carefully tracked and protected and therefore never go astray. But no, there are still a disturbing number of mishaps resulting in key assets disappearing – sometimes forever.

How to optimize asset tracking with Wi-Fi locationing

<p dir="ltr" id="isPasted">As technology continues to advance, Wi-Fi has remained a key component in research and industrial manufacturing. With the introduction of Wi-Fi 7, organizations now have the opportunity to improve their value propositions and provide customers with an enhanced experience. This new wireless communication technology offers substantial benefits for those looking to stay ahead in the game.</p><h2 dir="ltr">The Journey to Wi-Fi 7</h2><p dir="ltr">Wi-Fi, which stands for wireless fidelity, was developed by an organization called the Institute of Electrical and Electronics Engineers (IEEE), who sets standards for the Wi-Fi standard. IEEE 802.11be, dubbed Extremely High Throughput (EHT), is the next amendment of the IEEE 802.11 standard, which will be designated Wi-Fi 7. IEEE 802.11be is still in the development stage, and it is expected that the specifications will be officially released in late 2024 or early 2025.&nbsp;</p><p dir="ltr">The IEEE 802.11be aims to define Media Access Control (MAC) and Physical Layer (PHY) features that are customized to meet the demanding requirements of high-throughput and low-latency applications. The PHY component of IEEE 802.11 is expected to be similar to the one outlined in IEEE 802.11ax standard. For instance, the IEEE 802.11be will incorporate support for technologies like multi-user multiple-input and multiple-output (MU-MIMO), orthogonal frequency division multiple access (OFDMA), and longer symbol durations with smaller subcarrier spacing.&nbsp;</p><h2 dir="ltr">Technical Specifications</h2><p dir="ltr">Recent reports indicate that Wi-Fi 7 has achieved a remarkable increase in wireless data link performance, nearly quadrupling the capabilities of its previous generation, offering a throughput exceeding 36 Gbps. To attain this impressive transfer rate, the IEEE 802.11be standard introduces a range of technological advancements, such as wider channels and higher quadrature amplitude modulation (QAM), that exhibit substantial improvements over its predecessor.&nbsp;</p><p dir="ltr">In Wi-Fi 6, the utilization of OFDMA involved breaking down radio channels into smaller frequency allocations known as Resource Units (RUs). This approach enabled Wi-Fi devices to send smaller data packets to multiple users concurrently, enhancing both throughput and reducing latency. Wi-Fi 7 builds upon this foundational OFDMA concept but introduces the notion of Multiple RUs (MRU), which allows for combinations of different RU sizes.</p><p dir="ltr">The enhancements introduced through MRU have led to a significant reduction in latency, especially when multiple users are attempting to transmit data simultaneously. This improvement is achieved by allocating RUs more efficiently, taking into account the varying data lengths of different users. For example, in a scenario where four users with different data lengths are transmitting data, a Wi-Fi 7 access point (AP) equipped with MRU can achieve the shortest end-to-end latency compared to previous-generation APs, resulting in a 33 percent reduction in latency compared to Wi-Fi 5 and a 25 percent reduction compared to Wi-Fi 6.&nbsp;<iframe id="652e6bda405966a620c0bedf" width="250" class="specs-iframe" height="440" src="https://wevolver.com/iframe/specs/nordic-semiconductor-nrf7002-dk-wi-fi-6-development-kit?iframe=true" frameborder="0" scrolling="false" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe></p><h2 dir="ltr">How Does Wi-Fi 7 Achieve High Throughput?</h2><p dir="ltr">Wi-Fi 6 operated across two frequency bands—2.4 GHz and 5 GHz. In practical usage, only a portion of the available frequencies within each band were utilized, such as 80 MHz in the 2.4 GHz band and 600 MHz in the 5 GHz band. These specific sets of frequencies are referred to as the spectrum, and their actual size can <a href="https://www.lairdconnect.com/support/faqs/what-channels-are-supported-both-24-ghz-and-5ghz-band-most-countries" target="_blank">vary</a> between different countries.</p><h3 dir="ltr">Wider Channels</h3><p dir="ltr">While the previous generation of Wi-Fi could simultaneously handle 160 MHz channels, Wi-Fi 7 introduces a substantial improvement with ultra-wide 320 MHz channels. This advancement translates to a doubled data transmission capacity compared to the previous Wi-Fi 6 and 6E technologies. The broader channel not only minimizes latency but also enhances the overall transmission rate. These 320 MHz channels are situated in the relatively open 6 GHz band, steering clear of the frequently congested wireless transmission protocol bands. Consequently, this configuration reduces interference and ensures a more stable signal.</p><h3 dir="ltr">4K QAM for Higher Data Rate</h3><p dir="ltr">To leverage frequencies for faster computer speeds, Wi-Fi 6 uses a technique called quadrature amplitude modulation (QAM), supporting 1024 QAM. This means it can extract 1024 signals from these frequencies. The greater the number of signals, the more data bits it can carry, resulting in increased throughput. However, a choice must be made regarding the Wi-Fi channel within one of the frequency bands. For instance, in the 2.4 GHz band, a channel width of 20 MHz is typically used, and a broader channel width leads to higher throughput.</p><p dir="ltr">Comparing Wi-Fi 7 to its predecessors reveals significant advancements. Wi-Fi 7 boasts a data rate of 9.6 Gbps, a 39 percent increase compared to the previous generation, primarily due to the jump in QAM from 1024 QAM in Wi-Fi 6. Now, with the advent of Wi-Fi 7, even more enhancements have been introduced. The channel width has doubled, moving from 160 MHz to 320 MHz, effectively doubling the data rate. Additionally, the QAM has seen an improvement, increasing from 1024 QAM in Wi-Fi 6 to 4096 QAM, contributing an additional 20 percent to the data rate.</p><h3 dir="ltr">Improvements in MIMO</h3><p dir="ltr">Wi-Fi achieves data transmission between devices through specific Wi-Fi channels. To further enhance throughput, it utilizes a technique known as spatial streams, also referred to as MIMO. The Wi-Fi 7 standard expands the count of multi-user MIMO streams to 16. This increase in available MIMO streams, coupled with the capability to automatically select the most suitable stream for any given task, will result in a reduction in latency.&nbsp;</p><h3 dir="ltr">MLO for Wider Channels</h3><p dir="ltr">Wi-Fi 7 introduces enhancements to Multi-Link Operation (MLO). MLO enables the simultaneous utilization of multiple bands or channels by Multi-Link Devices. Embracing MLO provides advantages such as load balancing, data aggregation, and reduced latency. When employing the same modulation and coding scheme rate, Wi-Fi 7 with MLO delivers up to three times the effective throughput compared to Wi-Fi 6 with a single link. Furthermore, Wi-Fi 7 featuring MLO brings about an impressive 80 percent reduction in latency compared to the previous generation using a single link.</p><h2 dir="ltr">Why Use Wi-Fi 7 for Next-Gen Applications?</h2><h3 dir="ltr">Speed and Efficiency</h3><p dir="ltr">Wi-Fi 7 can leverage the capabilities of MLO to prioritize efficient data transmission, effectively managing network congestion and interference while optimizing the flow of data. With Wi-Fi 7 routers, dynamic channel selection becomes a key strategy to bypass congestion or interference, ensuring the smooth and reliable movement of data throughout the network.</p><h3 dir="ltr">Reliability</h3><p dir="ltr">In terms of reliability, Wi-Fi 7 elevates the&nbsp;dependability of wireless connections by maintaining a steady connection and mitigating interference, resulting in fewer disruptions and dropouts for users. This technology also addresses limitations associated with the coverage range of specific frequency bands. By intelligently selecting channels and optimizing transmission, it ensures that even in areas with limited signal coverage, connections remain resilient.</p><h3 dir="ltr">Adaptability</h3><p dir="ltr">One important feature of Wi-Fi 7 is its adaptability. By dynamically selecting the most appropriate channel according to current network conditions, it guarantees that the network can adapt to evolving environments and sustain peak performance. This adaptability inherent in Wi-Fi 7 not only ensures resilience but also future-proofs networks. As new devices and technologies come into play, Wi-Fi 7 can accommodate them by adeptly allocating resources and enhancing performance.</p><h2 dir="ltr">Potential Use Cases for Wi-Fi 7</h2><h3 dir="ltr">Real-Time Applications</h3><h4 dir="ltr">4K and 8K Streaming&nbsp;</h4><p dir="ltr">Recognizing Wi-Fi as the cornerstone of advancing digital technologies like edge computing and industrial automation, the introduction of Wi-Fi 7 marks a significant expansion of real-time applications, including the handling of 4K and 8K video streams.</p><h4 dir="ltr">AR and VR&nbsp;</h4><p dir="ltr">Wi-Fi 7 equips users to immerse themselves in technologies like augmented reality (AR) and virtual reality (VR) that offer experiences remarkably close to reality. Thanks to its rapid data transfer speeds and minimal latency, Wi-Fi 7 enhances user experiences by facilitating uninterrupted, real-time interactions within virtual environments.</p><h4 dir="ltr">Cloud Gaming</h4><p dir="ltr">Leveraging MLO technology plays a crucial role in diminishing latency and enhancing stability, a vital factor for cloud gaming enthusiasts. The increased throughput capabilities of Wi-Fi 7 enable real-time communication with latency levels consistently below 5 milliseconds, ensuring a top-tier gaming experience. This translates to high-quality video streaming, elevating the overall quality of the cloud gaming experience.</p><h2 dir="ltr">Industrial Applications</h2><h3 dir="ltr">IoT in Manufacturing</h3><p dir="ltr">Wi-Fi 7 offers the capacity to connect an extensive array of sensors and edge devices essential in the context of industrial automation applications. This capability enables manufacturing companies to automate their operations, resulting in operational efficiency. These sensors can monitor equipment conditions, detect anomalies, and optimize production workflows, resulting in reduced downtime, minimized errors, and enhanced overall productivity.</p><h3 dir="ltr">Automated Systems</h3><p dir="ltr">Manufacturers implementing wireless sensing and control technologies in their factory automation systems gain operational and financial benefits through the adoption of Wi-Fi 7 technology. Wi-Fi 7 enhances the reliability and speed of wireless communication within factory automation systems. This translates into quicker response times, more precise control, and the ability to manage larger volumes of data efficiently.</p><h3 dir="ltr">Public and Business Environments&nbsp;</h3><h3 dir="ltr">Smart Cities</h3><p dir="ltr">Smart cities have an increasing need for high-speed internet connectivity, and Wi-Fi 7 stands out as a solution that significantly enhances connectivity, efficiency, performance, and security for a wide array of smart city applications. These applications include real-time traffic and public transportation system monitoring, as well as the delivery of high-definition video surveillance. By implementing Wi-Fi 7, smart cities can improve their infrastructure, enabling efficient real-time data transfer for critical functions like traffic management and public safety.</p><h3 dir="ltr">Large Venues Like Airports and Stadiums</h3><p dir="ltr">In locations requiring high-density wireless connectivity, such as airports and stadiums, Wi-Fi 7 emerges as a compelling solution due to its advanced features, including the wide 320 MHz channels and enhanced multi-link operation. Wi-Fi 7 has the capacity to accommodate numerous simultaneous connections, allowing travelers and sports enthusiasts to stay connected to the internet without interruptions.</p><h2 dir="ltr">Conclusion</h2><p dir="ltr">Over the past few years, emerging applications with heightened requirements for both high throughput and low latency have fueled the evolution of the IEEE 802.11 standard. Wi-Fi 7, as part of this ongoing development, introduces significant enhancements, primarily centered around the design of high-performance PHY and MAC protocols.</p><p dir="ltr">Furthermore, Wi-Fi 7 incorporates a range of advanced techniques, including Multiple RU utilization, 4096 QAM modulation, multi-link aggregation and operations, MIMO improvements, and coordination techniques across multiple APs. These collective innovations within the standard protocol are geared toward supporting applications such as cloud gaming, IoT in manufacturing, automated systems, and high-quality video streaming.&nbsp;</p><p dir="ltr"><a href="https://www.mouser.com/empowering-innovation/wifi7" target="_blank" rel="noopener noreferrer">Learn more at Mouser.com</a></p><h2 dir="ltr">References</h2><p dir="ltr">[1] Nokia. Wi-Fi 7: a quantum leap in throughput and features. Laszlo Gyalog. July 05, 2023. <a href="https://www.nokia.com/blog/wi-fi-7-a-quantum-leap-in-throughput-and-features/" target="_blank">https://www.nokia.com/blog/wi-fi-7-a-quantum-leap-in-throughput-and-features/</a>. Accessed on September 23, 2023.</p><p dir="ltr">[2] Mediatek. Key Advantages of Wi-Fi 7: Performance, MRU and MLU. White Paper. February 24, 2022. <a href="https://www.mediatek.com/blog/mediatek-wifi-7-whitepaper-detailing-key-advantages-performance-mru-and-mlo" target="_blank">https://www.mediatek.com/blog/mediatek-wifi-7-whitepaper-detailing-key-advantages-performance-mru-and-mlo</a>. Accessed on September 23, 2023.</p><p dir="ltr">[3] Wired. What is Wi-Fi 7? Everything You Need to Know. Simon Hill. December 29, 2022. <a href="https://www.wired.com/story/what-is-wi-fi-7/" target="_blank">https://www.wired.com/story/what-is-wi-fi-7/</a>. Accessed on September 23, 2023.</p><p dir="ltr">[4] Senza Fili. Wi-Fi 7: The next generation in the evolution of Wi-Fi. Monica Paolini. Tech Brief. <a href="https://6ghz.info/wp-content/uploads/2022/07/SenzaFili-IntelTB-Wi-Fi7-The-next-generation-in-the-evolution-of-Wi-Fi.pdf" target="_blank" data-lf-fd-inspected-kn9eq4roawkarlvp="true">https://6ghz.info/wp-content/uploads/2022/07/SenzaFili-IntelTB-Wi-Fi7-The-next-generation-in-the-evolution-of-Wi-Fi.pdf</a>. Accessed on September 23, 2023.</p><p dir="ltr">[5] Intel Corporation. Next-generation Wi-Fi: Wi-Fi 7 and beyond. Carlos Cordeiro. July 2020. <a href="https://www.intel.com/content/dam/www/public/us/en/documents/pdf/wi-fi-7-and-beyond.pdf" target="_blank" data-lf-fd-inspected-kn9eq4roawkarlvp="true">https://www.intel.com/content/dam/www/public/us/en/documents/pdf/wi-fi-7-and-beyond.pdf</a>. Accessed on September 23, 2023.</p><p dir="ltr">[6] Rohde &amp; Schwarz. IEEE 802.11be: Technology Introduction. Lisa Ward and Jörg Köpp. White Paper. <a href="https://scdn.rohde-schwarz.com/ur/pws/dl_downloads/premiumdownloads/premium_dl_brochures_and_datasheets/premium_dl_whitepaper/IEEE-802-11be-technology-introduction_wp_en_3683-4026-52_v0100.pdf" target="_blank" data-lf-fd-inspected-kn9eq4roawkarlvp="true">https://scdn.rohde-schwarz.com/ur/pws/dl_downloads/premiumdownloads/premium_dl_brochures_and_datasheets/premium_dl_whitepaper/IEEE-802-11be-technology-introduction_wp_en_3683-4026-52_v0100.pdf</a>. Accessed on September 23, 2023.</p>

The article discusses the Wi-Fi 7– with improved speed, low latency, and better reliability for your wireless connections.


A short guide to the next generation of wireless connectivity-Wi-Fi 7

In this episode, we explore the dynamic landscape of retail transformation in the digital age. Learn how the integration of cutting-edge technology is reshaping shopping experiences and customer engagement. From real-time supply monitoring to digital shelves enabling dynamic pricing based on demand, discover how retailers adapt to changing consumer behaviors and preferences.

Podcast: Retail Fights Back With Connected Tech

<p id="isPasted">Experts say 2021 was the year of ransomware, but things changed in 2022 as criminals realized an estimated 17 billion IoT devices represented an easier target. While IT hardware and software security has dramatically improved, the IoT has lagged.</p><p>Many IoT products need to be adequately secured and, as such, represent vulnerable entry points for attacks on critical infrastructure. Or the IoT device itself can be the specific target due to the data it hosts &ndash; for example, video from security cameras and patient information from medical wearables.</p><p>There is a steady stream of news items about cyberattacks affecting everyday businesses and well-known brands. These can result in financial losses, privacy breaches, or individuals being blocked from accessing critical services. But now key infrastructure is also proving a major target, posing a danger to health, energy, food, water, and communications.</p><h2><strong>IoT as a growing attack surface for cybercrime</strong></h2><p>This is a problem that&rsquo;s not going away. Inexpensive wireless components are proving a boon to connectivity. The price of turning a dumb device into a smart device can be as low as 10 cents, says security expert Mikko Hypp&ouml;nen. That&rsquo;s encouraging vendors to add wireless connectivity to many devices, even if the benefits might be minor. And Hypp&ouml;nen explains that whenever an appliance is connected, that also makes it vulnerable.</p><p>According to analyst firm IDC, there will be almost 42 billion IoT devices by 2025. The vulnerable products among that network will contribute to a cost of cybercrime that&rsquo;s set to grow to $10.5 trillion by the same year, according to research firm Cybersecurity Ventures. The growing number of connected devices creates a larger &lsquo;attack surface&rsquo;&mdash;the number of potentially unprotected targets a miscreant can seek to exploit. In addition, the large volumes of data gathered and transmitted by billions of connected IoT devices create a bigger target for interception.</p><h2><strong>Addressing the vulnerability of connected devices</strong></h2><p>Enhancing the <a href="https://www.nordicsemi.com/Support/Security" target="_blank">security</a> of the IoT is challenging. Cyber attackers benefit from the complexity of the network, as the more companies, equipment, devices, and software are involved, the more opportunities there are for exploitation. Such complexity emphasizes the importance of security being considered at all stages of a product&rsquo;s lifecycle - not just when it&rsquo;s in the field.</p><p>Even simple IoT products, smart thermostats, for example, should be endowed with a degree of protection. It&rsquo;s not expensive to build-in simple protection such as secure-boot and secure-update with anti-rollback. Secure boot ensures the device verifies that its original software, and any subsequent update, is authorized and is safe to run. Anti-rollback prevents an older (and potentially vulnerable) version of the firmware being reinstated.</p><p>Even greater security can be achieved by isolation. Isolation provides a barrier between the firmware responsible for potentially vulnerable interfaces and the security critical code. Non-critical information can still be extracted from the isolated area for general operation of the IoT device, but no security critical information is accessible beyond the isolated area. The device might also feature secure storage for security critical data and assets.</p><h2><strong>Changing IoT-customers&#39; expectations of security</strong></h2><p>In the wake of heightened awareness of cyber-attacks, public expectations of IoT devices have shifted. A survey by the U.K. government in 2020 found nine out of ten people now expect smart devices to have basic embedded features to protect user privacy and security.</p><p>In response, <a href="https://www.psacertified.org/" rel="noopener" target="_blank">PSA Certified</a>, a framework for securing connected devices, has brought together major stakeholders to consolidate a range of security approaches into a standardized approach for the IoT. It developed a <a href="https://www.psacertified.org/what-is-psa-certified/using-psa-certified/" rel="noopener" target="_blank">four-stage framework</a> that guides developers through the steps necessary to implement the right level of security for a product. Nordic itself has aligned with the framework.</p><p>Regulators in several countries are also outlining expectations and establishing minimum security standards for IoT products. In the EU, lawmakers recently introduced security standards that require internet-connected products to have &ldquo;appropriate levels of cybersecurity&rdquo;. In the U.S., recent Executive Orders on cybersecurity have led to the development of IoT security standards by The National Institute of Standards and Technology (NIST).</p><h2><strong>Unlocking the value of the IoT</strong></h2><p>Improved security can help developers of IoT solutions unlock stronger customer relationships, especially in contexts where reliability is critical. A prime example is the <a href="https://www.psacertified.org/products/fluence-wireless-flex-dimming-receiver/" rel="noopener" target="_blank">Wireless Flex Dimming Receiver</a> lighting solution from illumination company Fluence, which is built using Nordic&rsquo;s nRF52840 SoC and is PSA Certified.</p><p>The product is targeted at the agriculture sector and enables growers to increase the amount and quality of produce by optimizing lighting conditions. Its built-in security features make it resistant to disruption increasing industry&rsquo;s trust in connected commercial solutions. This trust must now extend to key smart infrastructure such as smart electricity distribution grids, education, and healthcare.</p><p>As wireless IoT suppliers like Nordic, industry consortiums like PSA Certified, and regulators around the globe work to prioritize digital security, we may finally see inherent high levels of protection that will unlock the full potential of the IoT.</p><hr><p>This article was first published on Nordic&#39;s&nbsp;<a href="https://blog.nordicsemi.com/getconnected" target="_blank" rel="nofollow" id="isPasted"></a><a href="https://blog.nordicsemi.com/getconnected?utm_campaign=2021%20wevolver" target="_blank" rel="noopener noreferrer">Get Connected Blog</a>. &nbsp;</p>

Many IoT products need to be adequately secured and, as such, represent vulnerable entry points for attacks on critical infrastructure. Or the IoT device itself can be the specific target due to the data it hosts – for example, video from security cameras and patient information from medical wearables.

Why cybercrime is an increasing threat to the IoT

<p id="isPasted">The McKinsey Global Institute, an economics research firm, has estimated that by 2030 the IoT could enable $5.5 trillion to $12.6 trillion in value globally, including the value captured by consumers and customers of IoT products and services.</p><p>However, from where we are today to the IoT of 2030 is not a straightforward path. The wireless tech underpinning the IoT is complex to build, deploy, and maintain. But with the introduction of a new end-to-end solution, Nordic is making it easier and quicker to bring a <a href="https://www.nordicsemi.com/Products/Low-power-cellular-IoT?utm_campaign=2021%20wevolver" rel="noopener noreferrer" target="_blank">cellular IoT</a> end-product to market and support its implementation.</p><h2><strong>Dealing with cellular IoT and a fragmented supply chain</strong></h2><p>Such support is needed because, previously, many companies struggled to adopt cellular IoT due to the engineering difficulties presented by chipsets based on stripped-down mobile handset technology. Because these chipsets weren&rsquo;t designed specifically for cellular IoT, they were clunky and offered poor battery life, and less-than-robust connectivity.</p><p>The problem was made worse when the hardware was packaged into modules from a second vendor and used firmware from a third. The customer became confused as to where to turn for engineering tools and technical support for their cellular IoT development. And if that wasn&rsquo;t enough, things were made more complicated by the requirement to engage a cloud services provider to look after IoT products in the field.</p><p>At each step of the chain, the developer potentially had to deal with a different company that often had little or no interest in making sure its technology worked well with other parts of the system. That left it down to the designer to spend time solving gritty technical issues instead of focusing on enhancing their application.</p><h2><strong>A different approach</strong></h2><p>Nordic&rsquo;s approach to wireless has always been to abstract the complexity away from the underlying technology so the developer is freed to use the connectivity to build novel applications. By making wireless tech easier to design with, developers are relieved of the tricky RF engineering and software protocol challenges. That enables them to focus on the application and its associated software, accelerating time-to-market, and generally making for a better end-product.</p><p>With product families such as Nordic&rsquo;s <a href="https://www.nordicsemi.com/Products/Bluetooth-Low-Energy?utm_campaign=2021%20wevolver" rel="noopener noreferrer" target="_blank">Bluetooth LE</a> SoCs (the nRF52, nRF53 and nRF54 Series) the strategy of simplifying design and deployment extends to offering an end-to-end solution. Customers can access silicon, firmware, development tools, and modules (through Nordic solution partners) from a single supplier, safe in the knowledge that everything will work in harmony. And if engineering challenges do arise with the end-product, Nordic is on hand to offer comprehensive and expert technical support.</p><h2><strong>Extending the end-to-end approach to cellular IoT</strong></h2><p>Cellular IoT is the market leading LPWAN for secure and reliable long range connectivity. According to analyst Statista, the cellular IoT technologies, NB-IoT and LTE-M, make up 47 percent of the LPWAN market, with LoRa contributing 41 percent. Nordic has now extended its pioneering end-to-end approach to cellular IoT and <a href="https://www.nordicsemi.com/Products/DECT-NR?utm_campaign=2021%20wevolver" rel="noopener noreferrer" target="_blank">DECT NR+</a> (&ldquo;NR+&rdquo;).</p><p>That makes the company the first to offer a fully inclusive, world-class, massive IoT solution. Nordic&rsquo;s offering brings simplicity, stability, and cost efficiency to cellular IoT design, manufacture, and deployment. Developers can access SiPs, software, and services designed and supplied by a single company. That will help them save considerable time, money, engineering resources, and frustration from dealing with traditional fragmented supply chains.</p><h2><strong>Cellular IoT &ndash; from prototyping to the market and beyond</strong></h2><p>The cellular IoT solution hardware is based on two new nRF91 Series products, the <a href="https://www.nordicsemi.com/Products/nRF9161?utm_campaign=2021%20wevolver" rel="noopener noreferrer" target="_blank">nRF9161</a> and the <a href="https://www.nordicsemi.com/Products/nRF9131?utm_campaign=2021%20wevolver" rel="noopener noreferrer" target="_blank">nRF9131</a>. The plan is for the nRF9161&nbsp;to be a globally precertified SiP. That will make it possible to use a single device to select either cellular IoT, or NR+ for massive, ultra-reliable private 5G networking. The nRF9131 SiP is a feature-compatible alternative to the nRF9161, measuring half the size and offering greater flexibility in design and sourcing for high-volume businesses.</p><p>New SiPs are developed through Nordic&#39;s unified and scalable <a href="https://www.nordicsemi.com/Products/Development-software/nRF-Connect-SDK?utm_campaign=2021%20wevolver" rel="noopener noreferrer" target="_blank">nRF Connect SDK</a>. The nRF Connect for Desktop software also offers unique cellular IoT tools for optimizing power consumption and evaluating, monitoring, and debugging network connectivity.</p><p>Deployed customer end-devices based on the new SiPs can optionally be supported by Nordic&rsquo;s<a href="https://www.nordicsemi.com/Products/Cloud-services?utm_campaign=2021%20wevolver" rel="noopener noreferrer" target="_blank"> nRF Cloud</a>, which brings lower power, higher security, and flexibility to IoT device management. nRF Cloud offers a connectivity platform and cloud services solution from onboarding to decommissioning. Two new sets of services, nRF Cloud Security Services and nRF Cloud Device Management offer secure remote provisioning, cryptographic identity authentication, device state monitoring, and protocol-agnostic connectivity options. Nordic&rsquo;s SiPs also combine well with other Cloud management services.</p><h2><strong>Building the cellular IoT foundation</strong></h2><p>Designing and implementing cellular IoT applications is never likely to be trivial. But by offering an end-to-end solution, Nordic has made things easier. And with the company&rsquo;s nRF9161 and nRF9131, customers can take advantage of high-performance, low-power consumption cellular IoT solutions certified for global use.</p><p>If the IoT is to reach the potential forecast by McKinsey, it will need a comprehensively engineered foundation. By introducing end-to-end support for cellular IoT, Nordic is among the leaders in helping its customers build strong IoT foundations that will last.</p><hr><p>This article was first published on Nordic&#39;s <a href="https://blog.nordicsemi.com/getconnected" target="_blank" rel="nofollow" id="isPasted"></a><a href="https://blog.nordicsemi.com/getconnected?utm_campaign=2021%20wevolver" target="_blank" rel="nofollow">Get Connected Blog</a>. &nbsp;</p>

The wireless tech underpinning the IoT is complex to build, deploy, and maintain. But with the introduction of a new end-to-end solution, Nordic is making it easier and quicker to bring a cellular IoT end-product to market and support its implementation.

Wi-Fi

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