<p id="isPasted">I&#39;ve argued before that the IoT is more than hype. In fact, there is no question today that the IoT has gone mainstream.</p><p>A few application examples include asset tracking, advanced medical and sports wearables, both consumer and professional, and smart home. And the functionality and intelligence, in other words the usefulness, of all IoT applications are being further enhanced by machine learning (ML) and edge processing powered by AI in the cloud. There is no question that the IoT has finally arrived and is here to stay. The question is now: where is it going next?</p><h2><strong>The future of IoT is massive</strong></h2><p>I regard the IoT as like a luxury that if you&#39;ve never had you don&#39;t miss. But if you&#39;ve ever experienced its benefits, you can&rsquo;t forget them. Achieving 10 times more with 10 times less by doing it 10x smarter is very compelling. And that means like other successful platform technologies&mdash;for example, cellular&mdash;demand for what the IoT does best will boom massively in the years and decades ahead.</p><p>That requires the network to expand. And this scaling will be important to the point of existential need if both public and commercial organizations are to reach sustainability by delivering more with less.</p><p>Because the truth is we&rsquo;re not going to save the planet and conserve and protect vital scarce resources, or combat climate change, or feed the world, without the IoT. That means the IoT at the massive scale cannot arrive soon enough.</p><h2><strong>What&#39;s been holding massive IoT back?</strong></h2><p>The only reason massive IoT hasn&#39;t truly arrived yet is that it wasn&#39;t technologically or commercially viable before now for massive&nbsp;machine-to-machine (M2M)&nbsp;type communication.</p><p>This scale isn&#39;t thousands of devices. It&#39;s millions. It&#39;s billions. And it&#39;s going to one day be trillions of connected IoT sensors and device &#39;things&#39; at installation densities of a million devices per square kilometer.</p><p>This presents a massive wireless engineering challenge. Especially given that the typical IoT &#39;thing&#39; will be battery-powered and so have relatively limited power and computing capabilities. Moreover, the physical wireless network and its operational optimization must be &lsquo;off-the-scale&rsquo; better compared to anything that has gone before.</p><p>Although there have been admirable proprietary attempts to solve this problem, I can&#39;t see a long-term future for these. If a business or government organization is going to invest millions if not billions of dollars in any technology, they will need to know that technology is going to be viable not just years but decades from now.</p><p>Historically, the only way the tech and wireless communication sector has managed to deliver such longevity is via standards that encourage large mutivendor ecosystems. It&rsquo;s simply too risky to the point of reckless to rely only on only one vendor to supply and support a technology upon which you are vitally reliant.</p><p>This is why I believe the future of massive IoT is now in the hands of two complementary 5G standard wireless IoT technologies that were built from day one to support massive IoT low power wide area (LPWA) networks: cellular IoT and DECT NR+.</p><h2><strong>Cellular IoT</strong></h2><p><a href="https://www.nordicsemi.com/Products/Low-power-cellular-IoT" target="_blank">Cellular IoT</a> is the IoT-targeted LPWAN version of cellular wireless technology. From 4G, and now in 5G, this comes in two flavors: LTE for Machine-Type Communications (LTE-M) and Narrowband Internet of Things (NB-IoT).</p><p>Both LTE-M and NB-IoT offer the same legendary reliability and security benefits of cellular worldwide. But with power consumption levels that support multi-year operation from small, lightweight batteries that make traditional mobile and smartphone batteries look huge in energy capacity comparison terms. Cellular IoT offers global geographical coverage in or near to every population center and was designed for massive IoT scaling from the ground up.</p><p>This means almost any &lsquo;thing&rsquo; can now be connected to the world&rsquo;s cellular networks without a gateway. In industrial IoT, for example, this might mean the ability to monitor the location and contents of shipping containers and key industrial assets, or how well plant machinery is operating and the probability of failure (from maybe tell-tale changes in vibration, for example).</p><p>However, having access to a ubiquitous, secure, reliable, global network that already exists doesn&rsquo;t come free. And nor would you want it to be free for it to support a commercially viable and self-sustaining free market in the long-term.</p><p>What underpins the security and reliability is that your device must be certified for operation on the network. And the data you send will have to be sent via an established carrier. All that means cost and a certain degree of complexity, although both are falling all the time. This is why I believe cellular IoT will become a mainstay of massive IoT in the future whenever an application requires global connectivity.</p><h2><strong>DECT NR+</strong></h2><p>While 4G provided a platform for cellular IoT, 5G is the first radio standard defined with truly massive IoT in mind. <a href="https://www.nordicsemi.com/Products/DECT-NR" rel="noopener" target="_blank">DECT New Radio (NR)+</a> (originally called &#39;DECT-2020 NR&#39;) is the world&#39;s first non-cellular wireless technology to become a full 5G standard.</p><p>In my opinion, DECT NR+ fills the gap in the LPWAN market that proprietary alternatives have previously been the only ones to address. Namely: if you don&#39;t require global operation and instead only need to operate within a geographically-defined area, then enterprise IoT and public customers can now build their own &lsquo;private&rsquo; network that supports low-cost data. Example use cases include asset tracking, smart city, and smart energy.</p><p>DECT NR+&rsquo;s 1.9 GHz operating frequency is a global, license-free spectrum allocation (with the current exception of Japan, India, and China). It forms a single, secure, and reliable radio standard that is future-proofed and scalable. Moreover, because it is license free, DECT NR+ incurs no data charges, making it cheaper to run than its licensed equivalents.</p><p>With DECT NR+ users can deploy their own private networks. Private networks that use some of the proven technology that underpins the highly secure and ultra reliable global cellular infrastructure. As such, the technology promises to democratize 5G wireless by allowing massive IoT deployments with all the benefits of cellular, but at a much lower cost.</p><h2><strong>Managing the massive</strong></h2><p>I predict that over the next decade hundred-million-unit-plus IoT deployments will become routine across the globe. Every commercial and public organization in the world will need to deliver to this 10 times more with 10 times less for them and the planet to survive. Preventable waste and inefficiency will have to become fragments of a pre-massive IoT past.</p><p>To me that means massive IoT will become an almost &lsquo;no choice&rsquo; option in countless applications in hundreds if not thousands of industries and markets over the coming decade.</p><p>Massive IoT is going to completely transform how we live, work, and play in ways unimaginable to us today. And in doing so make the world a safer, greener, healthier, and ultimately better place to live.</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="nofollow">Get Connected Blog</a>. &nbsp;</p>

I've argued before that the IoT is more than hype. In fact, there is no question today that the IoT has gone mainstream.

Massive hype to massive IoT

<div data-id="be109c3" data-element_type="widget" data-widget_type="theme-post-content.default" id="isPasted"><p>Technology has a tendency to move from hardware to software, as physical components give way to virtual features. That trend certainly holds in IoT connectivity. For example, see the growth of eSIM, a market that&rsquo;s expected to nearly quadruple in size, reaching&nbsp;<a href="https://www.statista.com/statistics/1344336/e-sim-market-size-worldwide/" data-wpel-link="external" target="_blank" rel="external noopener noreferrer">over $16 billion</a>, by 2027.&nbsp;</p><p>This embedded subscriber identity module (hence &ldquo;eSIM&rdquo;) replaces the manual swapping of hardware SIM cards with remote provisioning. In other words, it replaces hardware with software&mdash;but so far, the benefits of this shift have fallen more heavily on consumer mobile devices than IoT deployments. &nbsp; &nbsp;</p><p>This difference comes from the technical specifications that govern mobile communication. Specifically, until recently, the standardization authority GSMA offered different technical specifications for remote provisioning in consumer devices and massive IoT deployments: &nbsp;</p><ul><li>For consumer devices, this is&nbsp;<a href="https://www.gsma.com/esim/resources/sgp-22-v2-2-2/" data-wpel-link="external" target="_blank" rel="external noopener noreferrer">SGP .22 &ndash; Remote SIM Provisioning Architecture for Consumer Devices</a>.</li><li>For IoT systems, it&rsquo;s&nbsp;<a href="https://www.gsma.com/esim/resources/sgp-02-v4-1-pdf/" data-wpel-link="external" target="_blank" rel="external noopener noreferrer">SGP .02 &ndash; Remote Provisioning Architecture for Embedded UICC Technical Specification</a></li></ul><p>With the 2023 release of&nbsp;<a href="https://www.gsma.com/esim/resources/sgp-32-v1-0/" data-wpel-link="external" target="_blank" rel="external noopener noreferrer">SGP .32 &ndash; eSIM IoT Technical Specification</a>, however, the difference between remote provisioning for IoT devices and consumer devices is starting to align a lot more closely. Simply put, SGP .32 allows massive IoT systems to access cellular networks more like eSIM-enabled consumer devices. It&rsquo;s a simpler process, so IoT product designers are watching the rollout of SGP .32 closely.</p><p>But does that mean every IoT product line should incorporate SGP .32 standards immediately? Not necessarily. Here&rsquo;s why:</p><p>&nbsp;</p><h2><strong>How SGP .32 Is Meant to Change Cellular IoT Connectivity&nbsp;</strong></h2><p>Before we get to our recommendations for IoT producers, we should explain the significance of GSMA&rsquo;s SGP .32 eSIM standard.&nbsp;</p><p>The key capability described by this standard concerns how IoT devices access the profiles that tell cellular networks they are, indeed, authorized for access. (This process is called&nbsp;<em>provisioning.</em>)</p><p>With a physical SIM, the profile is hard-wired onto the SIM card. With eSIM, you can store multiple profiles on a single chip, and you can access new profiles remotely&mdash;without having to swap out hardware, in other words. That provides access to a broader range of cellular networks, an essential feature for global IoT deployments. &nbsp;&nbsp;</p><h3>Remote eSIM Provisioning for IoT Systems (Prior to SGP .32)</h3><p>Under the old GSMA remote SIM provisioning (RSP) standard for IoT systems, remote access to user profiles required SMS (text messaging) capabilities. The device required bootstrap profiles to send SMS requests to networks, which would then deliver appropriate access credentials.&nbsp;</p><p>This sometimes clunky process is known as the&nbsp;<strong>push model of provisioning</strong>, because network systems have to actively send profiles out to devices. It&rsquo;s a complicated backend setup for a cellular IoT system, &nbsp;</p><h3>Remote eSIM Provisioning&nbsp;</h3><p>The consumer RSP specification, on the other hand, follows a&nbsp;<strong>pull model of SIM provisioning</strong>. The eSIM uses a type of application called a local profile assistant (LPA) to access network profile packages from the networks. &nbsp;</p><p>With SGP .32, LPA use&mdash;the simpler &ldquo;pull&rdquo; model of provisioning&mdash;becomes standard for massive IoT deployments. At least, that&rsquo;s the plan&mdash;but, unfortunately, the hardware ecosystem isn&rsquo;t quite mature enough for immediate deployment of SGP .32.</p><p>&nbsp;</p><h2><strong>The Role of IoT Modules in Remote Provisioning &nbsp;</strong> &nbsp;</h2><p>To connect to any cellular network, an IoT device needs an IoT module. This hardware includes a few features that control connectivity:&nbsp;</p><ul><li>The chipset controls the electromagnetic radio waves that communicate with cellular towers.&nbsp;</li><li>Computing hardware like a processor and memory storage units.</li><li>Antennas to send and receive radio waves (or at least an antenna port).&nbsp;</li><li>eSIM chips, integrated SIM circuitry, and/or SIM card slots.</li></ul><p>In other words, the module is where the cellular connection takes place.&nbsp;<em>The hardware, firmware, and software standards built into the module control remote provisioning.</em> As we publish, the current generation of IoT modules doesn&rsquo;t incorporate the SGP .32 specifications.</p><p>If you&rsquo;re building IoT products, you&rsquo;re probably buying your IoT modules from producers. Until those producers start shipping modules that use the SGP .32 specifications, there&rsquo;s not much you can do. It will probably take about&nbsp;<strong>5 years&nbsp;</strong>for these new capabilities to become widely available in IoT modules. While you can plan for the arrival of SGP .32, a product you release today probably won&rsquo;t be able to take advantage of the new specification. Here&rsquo;s what that means for IoT product designers.</p><p>&nbsp;</p><h2><strong>Getting Ready for the Rollout of the SGP .32 RSP Specification</strong></h2><p>If you need to ship your IoT product soon, you&rsquo;re probably stuck with eSIM remote provisioning via the SGP .02 specification, complete with an SMS bootstrap. If you&rsquo;re not in a hurry, you could keep your eye on the module market and see when this hardware starts incorporating SGP .32.&nbsp;</p><p>With either approach, however, the best way to prepare for SGP .32 is the same: Partner with a cellular connectivity provider that can handle technical upgrades for you. An IoT connectivity provider links your devices to a network or networks, freeing you from vendor-lock with a single mobile network operator (MNO).&nbsp;</p><p>That offers a single entryway into global connectivity. It creates redundancy to prevent downtime for your devices. And, with the right partner, it future-proofs your IoT system, as the connectivity experts can incorporate new technologies as they arise.&nbsp;</p><p>Look for a connectivity partner that works with module manufacturers; they&rsquo;ll be the first to incorporate new features like LPA provisioning with eSIM, according to the SGP .32 specification.&nbsp;</p><p>In general, if a connectivity-as-a-service provider has a strong track record of technical versatility&mdash;offering not just 4G or 5G networks, but private LTE/5G, satellite, and low-power network choices, too&mdash;they&rsquo;re likely to handle the heavy lifting on new GSMA specifications for you. That will get you ready for SGP .32 and whatever comes next, too.&nbsp;</p></div><div data-id="1fd13d7" data-element_type="widget" data-widget_type="author-box.default">Maor Efrati</div>

Technology has a tendency to move from hardware to software, as physical components give way to virtual features. That trend certainly holds in IoT connectivity. 

Is Your IoT Product Ready for the SGP .32 eSIM Specification?

<h2>Why You&#39;ll Love This Article</h2><p>Urban planning, the art of designing and shaping the cities we live in, is undergoing a quiet revolution. Researchers have harnessed the power of Artificial Intelligence (AI) to optimize community layouts, making cities more efficient, accessible, and sustainable. In this article, we&#39;ll delve into the world of AI-driven urban planning, exploring the challenges it addresses, the ingenious solution it offers, and the tangible impact it promises.&nbsp;</p><p>This research was conducted by researchers at Tsinghua University, Beijing and the full article can be found on <a href="https://www.nature.com/articles/s43588-023-00503-5" target="_blank" rel="noopener noreferrer">Nature</a>.</p><h2>The Woes of Urban Development</h2><p id="isPasted">Cities are intricate puzzles with myriad pieces: roads, buildings, parks, and services. Urban planners face the daunting task of piecing together these elements to create functional and harmonious communities. Traditionally, this process relied on manual labor and heuristics, often resulting in suboptimal designs and lengthy planning cycles.</p><p>One of the fundamental challenges in urban planning is optimizing the spatial layout. How can we ensure that essential services like schools and hospitals are easily accessible to residents? How do we strike the right balance between green spaces and built-up areas? And how can we design road networks that are efficient and free from congestion?</p><h2>What&#39;s The Solution?</h2><p id="isPasted">The researchers behind this groundbreaking approach have devised a solution that takes urban planning to new heights. At its core is an AI agent trained to make informed decisions about community layouts. But training an AI to plan cities is no small feat. It involves running millions of simulations, a process akin to trial and error, where the AI learns from its mistakes and successes.</p><p>Central to this solution is a tool called a Graph Neural Network (GNN). Think of it as a virtual brain capable of comprehending and processing geographical data. It constructs a graph to represent the urban environment, where nodes symbolize various urban elements, and edges capture their relationships and contiguity.</p><p>Why opt for a GNN, you may wonder? Urban planning is complex, with countless interconnections between different elements. Traditional methods often struggle to consider these intricate relationships. Enter the GNN, with its ability to analyze these connections, making it a crucial asset. It examines city layouts, understands the interactions between different components, and uses this knowledge to make informed decisions.</p><h2>But Does It Actually Work?</h2><p id="isPasted">Now, let&#39;s talk about the real-world impact. This AI-powered approach isn&#39;t just theoretical; it&#39;s a game-changer for urban planning.</p><h3>Efficiency Boost</h3><p>The AI agent can generate spatial plans in milliseconds, a stark contrast to the hours or days traditional methods require. This significant time saving can expedite the planning process.</p><h3>Service Accessibility</h3><p>The AI excels at optimizing community services. It ensures that essential services like schools and hospitals are within a short walking or cycling distance for residents. The accessibility metric indicates a remarkable improvement compared to conventional planning methods.</p><h3>Ecological Enhancements</h3><p>The AI knows how to make communities greener. It excels at covering residential areas with greenery, improving the quality of life and environmental sustainability.</p><h3>Traffic Efficiency</h3><p>The AI is a traffic virtuoso too. It ensures roads are dense, well-connected, and appropriately spaced, leading to smoother traffic flow and reduced congestion.</p><p>By combining these quantitative results, the impact becomes clear. AI-driven urban planning promises substantial time savings, enhanced accessibility to services, greener environments, and efficient traffic networks. It&#39;s a recipe for creating smarter and more livable cities.</p><h2>What Are The Limitations?</h2><p id="isPasted">It&#39;s vital to recognize that the success of this AI system hinges on the quality of input data. Inaccurate or incomplete geographical information can hamper its performance and while AI is a potent tool, it&#39;s not a replacement for human planners; In fact, it <strong>should</strong> work alongside human experts, balancing technological prowess with human creativity and judgment.</p><h2>TL;DR (Too Lazy; Didn&#39;t Read)&nbsp;</h2><p>AI-driven urban planning marks a significant leap forward in the quest to create better cities. It harnesses the power of AI and GNNs to optimize spatial layouts, making cities more efficient, accessible, and sustainable. While challenges and limitations remain, the potential for smarter, more livable cities is within reach, thanks to the fusion of artificial and human intelligence.</p>

The framework which consists of two separate policy networks (b and d) that take actions for the land use planning task (e) and road planning task (f) respectively, and share a GNN state encoder (a) with a value network (c) that estimates the effect of the current planning result.

Researchers have harnessed the power of Artificial Intelligence (AI) to optimize community layouts, making cities more efficient, accessible, and sustainable

From Pixels to Pavement: AI's Impact on Urban Design

<h2 dir="ltr" id="isPasted">Introduction</h2><p dir="ltr">In the world of engineering, the integration of the Internet of Things (IoT), robotics, and artificial intelligence (AI) is transforming the capabilities of autonomous systems. This article focuses on the importance of connectivity in enabling robots to access and exchange data, leading to more intelligent and adaptable systems.&nbsp;</p><p dir="ltr">IoT allows robots to connect to networks, while robotics involves the design and operation of autonomous machines. AI enhances IoT-enabled robots by analysing data and making informed decisions. Sensor technology, connectivity modules, and AI processing units are key components in this integration.&nbsp;</p><h2 dir="ltr">Understanding IoT, Robotics, and AI</h2><p dir="ltr">When we talk about integrating IoT devices with robotics and adding a layer of AI in the system, it is necessary to understand the basic differences between AI, IoT, and robotics and how they form a base for IoT-enabled robotics. These three terms are the enablers of advanced robotics, impacting how IoT-enabled robots interact with the environment. For that reason, let&#39;s break down these concepts in simple terms.</p><h3 dir="ltr">IoT</h3><p dir="ltr">The IoT refers to a network of physical objects that are embedded with sensors, software, and other technologies to connect and exchange data with other devices and systems over the internet. This exchange of data expands the possibilities for automation, monitoring, and control. While IoT is primarily focused on connectivity and data exchange, it does not inherently possess autonomous decision-making capabilities.</p><h3 dir="ltr">Robotics</h3><p dir="ltr">Robotics is the science and technology involved in designing, constructing, and operating robots. Robots are autonomous or semi-autonomous machines that can perform complex tasks, interact with their environment, and manipulate objects. Unlike IoT devices, which primarily focus on connectivity and data exchange, robots are physical entities capable of interacting with the physical world. While some robots may be equipped with IoT capabilities, not all robots are inherently part of the IoT ecosystem.</p><p dir="ltr">In robotics, the IoT presents an opportunity for integrating advanced robots into broader networks, enabling them to act in a more intelligent and autonomous manner. The IoT has transformed robotics with the paradigm shift known as <a href="https://www.frontiersin.org/articles/10.3389/frobt.2020.00104/full" target="_blank">Internet of Robotic Things (IoRT)</a>.</p><h3 dir="ltr">AI</h3><p dir="ltr">AI encompasses the development of intelligent systems that can perform tasks requiring human-like intelligence. AI algorithms enable machines to analyse data, identify patterns, make predictions, and even make decisions based on available information. AI augments the capabilities of IoT and robotics by providing advanced data analysis capabilities and enabling autonomous decision-making. While AI can be integrated with IoT devices and robots to enhance their functionality, not all AI systems are directly part of the IoT ecosystem.</p><h2 dir="ltr">The Role of AI in the Convergence of Robotics and IoT</h2><p dir="ltr">AI is the core of this convergence between robotics and IoT. While IoT provides the mechanism for connecting robots and gathering data, AI is the engine that processes, learns from this data, and enables autonomous decision-making.&nbsp;</p><p dir="ltr">For instance, <a href="https://www.conurets.com/use-of-iot-and-robotics-in-daily-life/" target="_blank">an AI-powered IoT robot</a> could leverage machine learning algorithms to recognize patterns in the data, learn from them, and make predictions or decisions based on its learnings. This combination of IoT connectivity and AI-based learning results in a new breed of intelligent, autonomous robots capable of complex operations without requiring constant human oversight.&nbsp;</p><p dir="ltr">However, not all robots are inherently part of the IoT. A robot becomes an IoT device when it&#39;s equipped with sensors and connectivity capabilities that allow it to collect, transmit, and receive data over the internet. In essence, it&#39;s the ability to participate in the larger, interconnected ecosystem of data and devices that makes a robot an IoT device.&nbsp;</p><h2 dir="ltr">The Mechanics of IoT in Robotics and AI</h2><p dir="ltr">Three primary technological areas are integral to this interconnected system: sensor technology, connectivity modules, and AI processing units.</p><h3 dir="ltr">Sensor Technology</h3><p dir="ltr">By combining many sensors&mdash;including cameras, radars, lidars, and ultrasonic sensors&mdash;designers can create data that is merged into a single model of sensor fusion to create a robust sense function. As the Internet of Vehicles (IoVs) and edge intelligence are used for training and real-time environment models, the sense functions are evolving towards distributed model-based or AI-inference processing at the sense-node and in the central cognition.&nbsp;</p><p dir="ltr"><span class="fr-img-caption fr-fic fr-dib" style="width: 302px;"><span class="fr-img-wrap"><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1695746433856-shutterstock_2280373681+%281%29+%281%29.jpg" style="width: 300px;" class="fr-fic fr-dib"><span class="fr-inner">Figure 2: Robotic vision camera sensors enable seamless navigation, object recognition, and enhanced situational awareness.&nbsp;</span></span></span></p><p dir="ltr">The advancement of sensor technology in the IoRT system&#39;s capacity to sense the environment using a variety of sensor types, combine the information from the various sensors, and localize itself and other things using GPS/GNSS signals and both local and high-definition maps to create a semantic understanding and local and global models. Because perception information is the input for analytics and AI processing, the data that these sensors acquire must be in a format that can be used by various and unique cognitive processes of robotic things and applications.</p><h3 dir="ltr">Connectivity Modules</h3><p dir="ltr">Connectivity is the lifeblood of the IoT, facilitated by communication modules that enable data exchange between devices. These modules employ a variety of technologies, including Wi-Fi&reg;, Bluetooth&reg;, Zigbee, <a href="https://www.wevolver.com/article/an-introduction-to-lorawan" target="_blank">LoRaWAN</a>, and cellular networks.</p><p dir="ltr">In terms of connectivity, wireless communication methods are dominant for IoRT. When discussing the interactions and pairings of wireless technologies (such as cellular 5G and beyond), IoT/IIoT, and AI approaches and processes, the term &quot;intelligent connectivity&quot; is used.</p><p dir="ltr">The connectivity of modules for IoT-enabled robotics involves developing robotic objects with reliable wireless and cellular connectivity is essential. IoRT applications may use wired, wireless, cellular, optical, audio, video, voice, or other types of communication channels. Any of a wide range of protocols&mdash;including TCP, UDP, 802.15.1, 802.15.4, 802.11, 4G/LTE/5G&mdash;can be used as the foundation for the communication networks.</p><p dir="ltr">Edge-distributed processing, including analytics at the edge based on AI concepts and approaches, replaces centralised processing for mission- and safety-critical IoRT applications where latency, dependability, and throughput are crucial requirements. Edge-distributed processing makes use of multi-access edge computing, fog computing, and intelligent connection offered by wireless and cellular communication (4G/5G and beyond). This idea enables IoRT apps to process data locally and use local learning to apply AI algorithms to the data that has been acquired, reducing the need to transport huge volumes of data to the cloud, store data locally, and lighten the stress on connection lines.</p><h3 dir="ltr">AI Processing Units</h3><p dir="ltr">AI processing units, also known as AI accelerators, constitute the brainpower behind IoT-enabled robots. The progress of IoRT depends heavily on the AI processing units. The capabilities of particular robotic objects are improved by the AI algorithms. To improve cognition and decision-making, AI technologies are used to optimise the sensor fusion capabilities of IoRT devices (such as cameras for detecting sight, chemical sensors for identifying smell and taste, microphones for hearing, pressure sensors for detecting touch/pressure). They are also used to extract patterns from data. To give analytics and insights and to optimise the functions of the individual robotic things and their cooperative behaviours as a fleet, AI techniques and approaches are incorporated in the various layers of IoRT platforms.</p><p dir="ltr">Deep neural networks, such as convolutional neural networks (CNNs), are used to assess and extract visual features from images. To improve the performance of the recognition function by attaining high detection rates of quality variations or probable errors, the strategies are created for partitioning and de-noising monitored signals. IoRT applications can now handle extraordinarily huge data sets because of the transition from central compute to edge/fog nodes. To significantly increase the computing efficiency of an inspection model that can identify the type and <a href="http://www.ijmmm.org/vol7/445-ICMEM2019-216.pdf" target="_blank" data-lf-fd-inspected-kn9eq4roawkarlvp="true">severity of defects</a>, this method is also used in the case of effective manufacturing inspection systems. It combines AI techniques with edge processing by adapting a CNN model to the fog computing environment.</p><p dir="ltr">At the level of robotic things, video capture, video data compression, video picture pre-processing, and segmentation are performed using perception tools like cameras. Better object identification accuracy can be achieved by jointly training a context and scenery-aware adaption model using data from various video capture systems. An ideal offloading method must be established in order to balance the distribution of the deep learning (DL) computation among IoRT devices, edge servers, and the cloud. The trade-offs between important indicators such network health, video compression, data rates/usage, power consumption, processing delay, frame rate, and processing accuracy of analytics must be taken into account. Numerous distributed edge robotic thing devices can work together at the edge to provide better services.&nbsp;</p><p dir="ltr">The system&#39;s overall performance can be enhanced by edge computing federation and distribution of functions for compressing the DL model at the edge layer. According to <a href="https://ieeexplore.ieee.org/abstract/document/8337810" target="_blank">a research on object detection in edge computing</a>, the cloud can guarantee the integration of distributed learning models with the edge computing layer and update the parameters of these models on edge devices. The computing power and global knowledge in the cloud infrastructure can be used for processing and assisting the edge nodes in updating DL models when the edge infrastructure is unable to provide a reliable service with the required quality (e.g., detecting objects/patterns with low confidence).</p><p dir="ltr"><span class="fr-img-caption fr-fic fr-dib" style="width: 302px;"><span class="fr-img-wrap"><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1695746483237-shutterstock_668202985-scaled.jpg" style="width: 300px;" class="fr-fic fr-dib"><span class="fr-inner">Figure 3: The automation of robot arms within IoRT revolutionizing the manufacturing, logistics, logistics, and assembly processes. Image credit: Kuka</span></span></span></p><p dir="ltr">Mouser Electronics, an authorised global distributor of electronic components, offers a wealth of products and knowledge that support the development of IoT-enabled robotics and AI systems.&nbsp;</p><p dir="ltr">These products range from advanced microcontrollers and processors to sensors, connectivity modules, power management devices, and much more. By supplying these essential elements, Mouser is facilitating the development and deployment of IoT-enabled robotics and AI systems across various industries.</p><h2 dir="ltr">Conclusion</h2><p dir="ltr">The integration of the IoT with advanced robotics and AI is revolutionizing the capabilities of autonomous systems. Robots connected to IoT networks gain access to a wealth of data and the ability to communicate and collaborate with other devices, leading to more intelligent and adaptable systems.&nbsp;</p><p dir="ltr">The addition of AI further enhances the capabilities of these IoT-enabled robots, enabling them to learn, reason, and make informed decisions based on real-time data analysis. Together, IoT, robotics, and AI are reshaping industries and everyday life, offering new opportunities for innovation and automation.&nbsp;</p><p dir="ltr">As engineers and designers embark on the development of IoT-enabled robotics and AI devices, Mouser Electronics serves as a reliable partner, providing the tools to compare and acquire the necessary components for these groundbreaking technologies. Through their comprehensive inventory and user-friendly website, Mouser supports the advancement of IoT-enabled robotics and AI, driving progress and shaping the future of intelligent and autonomous systems.</p><h2 dir="ltr">References:</h2><p dir="ltr"><a href="https://www.frontiersin.org/articles/10.3389/frobt.2020.00104/full" target="_blank">https://www.frontiersin.org/articles/10.3389/frobt.2020.00104/full</a></p><p dir="ltr"><a href="https://geekflare.com/digital-transformation-ai-robots-iot/" target="_blank">https://geekflare.com/digital-transformation-ai-robots-iot/</a></p><p dir="ltr"><a href="https://www.analyticssteps.com/blogs/internet-robotic-things-robotics-iot" target="_blank">https://www.analyticssteps.com/blogs/internet-robotic-things-robotics-iot</a></p><p dir="ltr"><a href="https://iot.eetimes.com/the-internet-of-robotic-things-how-iot-and-robotics-tech-are-evolving-together/" target="_blank">https://iot.eetimes.com/the-internet-of-robotic-things-how-iot-and-robotics-tech-are-evolving-together/</a></p><p dir="ltr"><a href="https://ieeexplore.ieee.org/abstract/document/8976180/" target="_blank">https://ieeexplore.ieee.org/abstract/document/8976180/</a></p>

The integration of AI, IoT, and robotics allows robots to access and exchange data with other devices, enabling them to make informed decisions.


The Role of IoT in Robotics and AI: Understanding Connectivity

An investigation into innovative applications of SBCs


SBCs for Modern Engineering

<p>The internet of things (IoT) is quickly becoming a reality for businesses around the world. As the need for more and more device integration arises, companies are facing many connectivity and security issues. Where traditional approaches are stagnating, <a href="https://monogoto.io/" data-wpel-link="internal" target="_blank">connectivity management platforms</a> are a promising new approach for providing businesses with the IoT connectivity they need.</p><h2>Traditional MNO Solutions</h2><p>Traditional mobile network operators (MNO) have been a source of many early IoT connectivity solutions. They are well established and have an extensive infrastructure. During the earliest phase of IoT development and progress, incumbent mobile network operators like AT&amp;T and Verizon were essentially the only option for connectivity. As such, many IoT implementations successfully made use of MNOs for their connectivity.</p><p>Despite some success, traditional MNO infrastructure was not designed with the IoT in mind. They&rsquo;re moving forward with more LTE and 5G features, but these do not address some of the key areas that distinguish MNO from other IoT connectivity options.&nbsp;</p><h2>Global SIM Card MVNO IoT Connectivity</h2><p>A more versatile solution for the diverse needs of IoT connectivity is mobile virtual network operators (MVNO). MVNO IoT connectivity can allow for a more integrated IoT approach, delivering more security, connectivity, and versatility organizations need. While these solutions are a significant improvement, there is still a key component that is missing.</p><p>There is a wealth of features organizations can find in an&nbsp;<strong><a href="https://monogoto.io/iot-connectivity/" data-wpel-link="internal" target="_blank">IoT connectivity</a></strong> management platform that they cannot achieve with MVNO alone. AVSystem has laid out some of the&nbsp;<a href="https://www.avsystem.com/blog/iot-connectivity/" data-wpel-link="external" target="_blank" rel="external noopener noreferrer"><strong>key requirements for IoT connectivity</strong></a>, and it&rsquo;s clear that to transform an organization&rsquo;s hardware, software, and tech into a truly integrated IoT, a more thorough approach will be necessary.</p><h2>&nbsp;</h2><h2><img data-fr-image-pasted="true" src="https://monogoto.io/wp-content/uploads/2021/09/campaign-creators-K1Sq9qG-c70-unsplash-scaled.jpeg" alt="Connectivity Management Platform" width="749" height="514" srcset="https://monogoto.io/wp-content/uploads/2021/09/campaign-creators-K1Sq9qG-c70-unsplash-scaled.jpeg 2560w, https://monogoto.io/wp-content/uploads/2021/09/campaign-creators-K1Sq9qG-c70-unsplash-300x206.jpeg 300w, https://monogoto.io/wp-content/uploads/2021/09/campaign-creators-K1Sq9qG-c70-unsplash-1024x702.jpeg 1024w, https://monogoto.io/wp-content/uploads/2021/09/campaign-creators-K1Sq9qG-c70-unsplash-768x526.jpeg 768w, https://monogoto.io/wp-content/uploads/2021/09/campaign-creators-K1Sq9qG-c70-unsplash-1536x1053.jpeg 1536w, https://monogoto.io/wp-content/uploads/2021/09/campaign-creators-K1Sq9qG-c70-unsplash-2048x1404.jpeg 2048w" sizes="(max-width: 749px) 100vw, 749px" class="fr-fic fr-dii"></h2><h2>API-Based MVNO Connectivity Management Platforms</h2><p>API-based MVNO solutions deliver something that traditional MNOs and even global sim card MVNO solutions can&rsquo;t provide. These types of solutions focus on giving businesses the necessary tools to adapt IoT connectivity to their unique needs.&nbsp;</p><p>API-based connectivity management platforms increased security and versatility. With them, an organization can configure alerts for any events on the network, send custom commands, and maintain complete control over their security profile. This is the kind of versatility that&rsquo;s needed for an effective IoT connectivity solution.</p><p>The issue of proper IoT integration cannot simply be ignored, with&nbsp;<a href="https://www.statista.com/statistics/1101442/iot-number-of-connected-devices-worldwide/" data-wpel-link="external" target="_blank" rel="external noopener noreferrer"><strong>Statista projecting</strong></a> the number of IoT device connections to nearly triple by 2025. Organizations need reach, security, and efficiency for their IoT integration. A connectivity management platform will deliver results in all of those areas.</p><p>A connectivity management platform optimizes IoT connectivity, enabling businesses to deploy services faster and reach further. The entire development process is accelerated, with less debug time and many functions offloaded onto the platform.</p><p>Connectivity management platforms include automation tools that work off of information within the network and automatic commands. Combined with cloud integration with consumption-based pricing, organizations can make more effective use of their resources and their budgets.</p><h2>Getting Started With Monogoto</h2><p>Connectivity management platforms represent a new way of looking at IoT connectivity, and Monogoto is at the head of the pack when it comes to this new technology. Our connectivity management platform integrates all elements of your IoT connectivity, meaning there is no need for additional security measures. We know that there is no one-size-fits-all solution here, and we&rsquo;ve built our entire organization around that principle.</p>

IoT Connectivity: How to Choose the Right Connectivity Management Platform for My Organization?

How to Choose The Right IoT Connectivity Platform? Monogoto

<p id="isPasted">Many companies in the manufacturing industry around the world are striving to improve business value and raise operational efficiency through digital transformation (DX). On the other hand, there is now a strong demand for decarbonization efforts, which curb greenhouse gases (GHGs) emitted in production activities to achieve carbon neutrality. The response to these two megatrends of DX and decarbonization has become an important issue in encouraging each company in the manufacturing industry sustainable.</p><p>The purpose of decarbonization for the manufacturing industry since 2021 onward has changed from social contribution to achieving profits by observing conditions in transactions with customers and enhancing cost competitiveness. Some leading electronic equipment manufacturers have already stated that they will not procure parts or materials from suppliers that are not striving to reduce GHG emissions. An increasing number of investors are also making proactive decarbonization efforts a condition for investment. Moreover, at the 26th Conference of the Parties to the United Nations Framework Convention on Climate Change (COP26) held in November 2021, the so-called 1.5&deg;C target<sup>*1</sup> was raised to a stricter mandatory target. It is increasingly likely that policies with strong binding force will be implemented in the future. Those policies include strengthening environment-related regulations and introducing carbon pricing<sup>*2</sup> such as carbon taxes. As a result, decarbonization efforts have become directly linked to companies&rsquo; earnings in the manufacturing industry. That means they are starting to have the same meaning as productivity improvements.</p><p>*1: This is the target to keep the rise in the global average temperature within 1.5&deg;C compared to before the Industrial Revolution.&nbsp;</p><p>*2: This is the general term for the mechanism to pass on a company&#39;s CO2 emissions to costs. It includes a tax called a carbon tax imposed on the use of fossil fuels and emissions trading to buy and sell CO2 emission allowances to clear environmental regulations. According to the World Bank, carbon pricing has already been introduced in 46 countries and 35 regions as of April 10, 2021.</p><p>The two megatrends surrounding the manufacturing industry of DX and decarbonization appear to be separate trends at first glance. However, in reality, DX leads to more efficient production activities, energy saving, and decarbonization. Therefore, they have an inseparable relationship. We introduce here how to use DX initiatives as a means to promote decarbonization. In particular, we look at the latest trends in the utilization of information processing technologies such as IoT, AI, and digital twins. We then explain decarbonization in smart factories.</p><h2>Two Approaches to Promoting Decarbonization in Factories</h2><p>Many machine tools, industrial robots, motor-driven devices and equipment like compressors, electric heaters, control devices, and other devices and equipment operated by electric power are used in factories. The decarbonization of these devices and equipment operated by electric power has become a major issue in the manufacturing industry.</p><p>The approaches to decarbonization of devices and equipment that use electric power are broadly divided into two (Fig. 1). One is a method of switching to using sources of energy that do not emit greenhouse gases. Specifically, this includes the utilization of solar power, wind power, and other forms of renewable energy. The other is a method to completely cut out unnecessary power consumption. This is so-called power-saving. Promoting DX is an important condition for pushing ahead with these two approaches.</p><p><span class="fr-img-caption fr-fic fr-dib" style="width: 768px;"><span class="fr-img-wrap"><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjk1NjUwNzA5Mzg4LXNtYXJ0ZmFjdG9yeV8wOS0xZW4ucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 766px;" class="fr-fic fr-dib"><span class="fr-inner">Fig. 1: Two approaches to reducing greenhouse gas emissions / Source: Agency of Natural Resources and Energy, Ministry of Economy, Trade and Industry</span></span></span></p><p id="isPasted">In general, the amount of electric power obtained from renewable energy is unstable. It depends on the sun and the wind, for example. However, electric power systems must satisfy the principle of electric power supply called the &quot;same amount at the same time&quot; in which the amount of electric power supplied and consumed is constantly kept the same. The reason for this is that if there is&nbsp;a significant difference in the amount of electric power consumed and supplied, an abnormal load may be applied to power generators, power distribution equipment, electrical equipment, and other devices, causing them to fail, or the electric power quality may become unstable. That may cause malfunctions or power outages. In other words, it is necessary to cover only the electric power that corresponds to the amount consumed in the factory with electric power generated at that time, electric power stored in storage batteries, or other sources of electric power.</p><h2>Aiming for Compliance with RE100 by Utilizing IoT</h2><p>In recent years, there has been an increasing number of companies in the manufacturing industry joining the RE100 international environmental initiative. This is an initiative aiming to cover the electric power used in business activities with 100% renewable energy. It is important to introduce an electric power system capable of appropriately managing and controlling the electric power supply and demand balance without lowering productivity or quality and a mechanism to cover the shortfall from countermeasures to realize the ideals of RE100 in factories (Fig. 2).</p><p><span class="fr-img-caption fr-fic fr-dib" style="width: 768px;"><span class="fr-img-wrap"><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjk1NjUwNzI1NTQ1LXNtYXJ0ZmFjdG9yeV8wOS0yZW4ucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 766px;" class="fr-fic fr-dib"><span class="fr-inner">Fig. 2: Electric power system and mechanism for the realization of RE100-compliant factories</span></span></span></p><p id="isPasted">To ensure a factory is compliant with RE100, it is first necessary to build a&nbsp;renewable energy utilization infrastructure by introducing power generation and storage equipment for solar power and other forms of renewable energy. It is also important to have a mechanism to store surplus electric power in storage batteries and to cover the shortfall in electric power by visualizing the amount of electric power generated, which changes moment by moment due to changes in the weather, and the amount of electric power consumed in the factory, which increases or decreases depending on the production activity situation.</p><p>There are more and more examples of companies introducing an electric power management system called the Factory Energy Management System (FEMS) in advanced factories. This is a system that utilizes IoT to monitor the amount of electric power consumed. It then adjusts peak electric power, controls the operation of air conditioners, lighting equipment, and production lines according to the situation, and performs other similar operations. The system visualizes the electric power consumption situation across the entire factory. It then curbs the nonessential and nonurgent operation of equipment and minimizes unnecessary electric power consumption without a drop in productivity. The range of equipment managed by the FEMS has now expanded to include power generation and storage equipment. It has evolved to being capable of maintaining the supply and demand balance in RE100-compliant factories.</p><h2>Highly Accurate Prediction and Management of the Electric Power Supply and Demand Balance with AI and Digital Twins</h2><p>Attempts are also underway to further raise the accuracy of management and control with the FEMS by utilizing the latest information processing technologies such as AI and digital twins<sup>*3</sup>.</p><p>*3: A digital twin is a digital model that reproduces the same conditions and properties as in the real world by inputting data that reflects the current situation collected by IoT in the design data of real things.</p><p>For example, technologies are being developed that estimate the amount of electric power obtained from solar power generation. To achieve this, those technologies analyze weather forecast and past track record data using AI to accurately predict the amount of power generated, which can be obtained from the equipment owned by a company. If it is possible to accurately predict the amount of power generated, it becomes possible to more effectively utilize the electric power generated in a company by shifting the peak of electric power consumption through the adjustment of production plans.</p><p>Moreover, digital twins, which reproduce the conditions and movements over an entire factory using a computer, are being built, and technologies that increase the effect of power-saving measures are also being developed. It is becoming possible to take measures that allow the maximum effect to be obtained without risk by verifying on a digital twin the power-saving effect and the impact on productivity and product quality from&nbsp;the changes in the control and operation conditions of devices and equipment and alterations to production plans.</p><p>Decarbonization efforts in the manufacturing industry are inseparably related to DX initiatives in factories. Regarding DX-related efforts, it seems important to keep in mind not only productivity and quality improvements, but also decarbonization.</p><hr id="isPasted"><p><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1695650770461-1695650770461.png" class="fr-fic fr-dii"></p><p>If you have any questions based on this article that you would like to discuss with an expert at Murata, don&#39;t hesitate to reach out. There&#39;s an entire team ready to support you with your question.</p><p><a href="https://www.murata.com/en-eu/contactform?&Detail=Wevolver%20request" target="_blank" rel="nofollow" class="button-main-action">GET IN TOUCH</a></p>

Many companies in the manufacturing industry around the world are striving to improve business value and raise operational efficiency through digital transformation (DX). On the other hand, there is now a strong demand for decarbonization efforts, which curb greenhouse gases (GHGs) emitted in production activities to achieve carbon neutrality.

The Inseparable Relationship Between Digital Transformation and Decarbonization and Technologies Essential for a Sustainable Manufacturing Industry

<p id="isPasted">In April 1981, <em>The Washington Post&nbsp;</em>reported that the U.S. supermarket chain, Giant Food Inc., was about to stop marking prices on individual items in its stores in a bid to reduce operating costs. If there was no consumer backlash, the report predicted, the rest of the industry would follow, as it did when the company was the first food retailer to introduce barcode scanners at its checkouts, spurring the spread of that technology across the country.</p><p>Fast forward 40 years and individually priced items in supermarkets have long been consigned to history, with shelf pricing now the accepted norm. And it has, as Giant Food hoped, reduced operating costs for retailers that can stock as many as 50,000 different product lines. As recently as the 1990s, 7,000 product lines was considered average. Now technology is overhauling shelf labeling anew, and supermarkets will be the likely trailblazers once again.</p><h2><strong>The beginning of the end for paper labels</strong></h2><p>Electronic shelf labels (ESL) are connected, low-power &lsquo;e-paper&rsquo; display devices that can replace traditional paper labels and can display text, numbers, icons, lines, barcodes and pictures. They enable retailers to automatically update individual shelf price labels from a central point across multiple stores and branches&mdash;or in certain geographic locations&mdash;at the touch of a button. Comprised of a Cloud platform, access points or gateways, and wirelessly connected shelf labels, pricing commands can be sent from a web-based dashboard to store-located gateways, from which point commands are relayed to the smart labels.</p><p>According to analyst ABI Research, by the end of last year, 788 million electronic shelf labels (ESL) had been installed globally. The number may seem significant, but with tens of billions of paper labels still on shelves, the technology has yet to make it mainstream, despite not really counting as a &lsquo;new&rsquo; technology. Primitive versions using liquid crystal displays that could display a price but nothing else have been around for some 30 years. There are a number of reasons the technology has yet to hit the big time, including market fragmentation, cost of deployment, concerns over interoperability, security, and a fear of obsolescence. Now this could be about to change.</p><p>Earlier this year, the Bluetooth Special Interest Group (SIG), announced the release of the <a href="https://www.bluetooth.com/learn-about-bluetooth/use-cases/electronic-shelf-labels/?utm_campaign=2021%20wevolver" rel="noopener noreferrer" target="_blank">new wireless standard for the ESL market</a>, with the goal of making Bluetooth the standard protocol for ESL.&nbsp;The scalable, low-power, secure ESL standard (consisting of ESL Profile and Service specifications) has been developed by a working group comprised of a leading ESL vendor and enabling technology suppliers, and standardizes the process for message transmission between access points and ESLs. To do so it leverages feature enhancements introduced in the Bluetooth Core Specification Version 5.4, including Periodic Advertising with Responses (PAwR) and Encrypted Advertising Data (EAD).</p><p>In general, PAwR and EAD are intended for one-to-many applications that involve a large number of devices (tags) receiving and transmitting small amounts of data from and to an access point, that accept longer latencies (e.g. 2 seconds) in exchange for extended battery life. Together, they enable connectionless, bidirectional, secure communication with thousands of very low-power end nodes in a star topology, essential in a retail ESL application where many thousands of labels could be required to cover all of the items stocked. For a technical deep dive on ESL, PAwR and EAD see <a href="https://devzone.nordicsemi.com/nordic/nordic-blog/b/blog/posts/whats-new-in-bluetooth-v5-4-an-overview?utm_campaign=2021%20wevolver" rel="noopener noreferrer" target="_blank">What&#39;s new in Bluetooth v5.4: An overview</a>.</p><h2><strong>Dynamic, efficient pricing operations</strong></h2><p>If the introduction of the standard has the intended effect on the retail industry and ESL becomes widespread, retailers are set to benefit in several ways. Updating paper price labels requires staff to change thousands of tags every week. It&rsquo;s not only a lot of labor to do very little, it also takes time and is prone to error, and inaccurate pricing on shelves even for a short time can cost grocery retailers profit. ESL eliminates the manual process and at the same time enables dynamic pricing strategies allowing retailers to adjust pricing based on stock levels, demand, and market conditions.</p><p>Standardization is key here to ensure interoperability, security and to allow retailers to have systems that can be installed and easily maintained over a long lifespan. At the same time, Bluetooth can also be leveraged to keep tags updated with the latest firmware, using Over-The-Air Device Firmware Updates from the gateway itself.</p><p>Moreover, by using Bluetooth as the protocol, some ESL systems can mix and match with other Bluetooth technologies, such as Bluetooth Direction Finding for a quick positioning, enabling staff to quickly and easily identify the specific location of individual product lines across the store. This is particularly beneficial to staff responsible for picking and replenishing stock. Paired with Wi-Fi-connected shelf cameras and Cloud-based AI models, savvy retailers are also remotely monitoring stock to ensure shelves are well stocked and only replenished when necessary.</p><p>The smart labels can also be used as beacons for marketing to consumers in close proximity via compatible smartphone apps, at the same time allowing retailers to gather insights into customer behavior to provide improved shopping experiences, personalized marketing, and to increase conversion rates in store.</p><h2><strong>Widescale adoption looms</strong></h2><p>Nordic Semiconductor, as the market leader in Bluetooth LE, has already introduced the PAwR and EAD features as standard in its qualified Bluetooth 5.4 SoftDevice Controller in the <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>, and companies developing ESLs can start working with this technology today thanks to the pre-release reference example (both gateway and tags) now available on request by opening a <a href="https://devzone.nordicsemi.com/support/add?utm_campaign=2021%20wevolver" rel="noopener noreferrer" target="_blank">private ticket on DevZone</a> or by <a href="https://www.nordicsemi.com/About-us/Contact-Us?utm_campaign=2021%20wevolver" rel="noopener noreferrer" target="_blank">contacting Nordic sales</a>.</p><p>Nordic&rsquo;s SoCs meet the ultra low power requirements of ESLs where the number of tags involved prohibits even infrequent battery changes, while the Flash and RAM allocation ensures they can store the volume of information required to implement a fully-featured ESL system. Both the nRF53 Series and several of the nRF52 Series SoCs also support Direction Finding, enabling optimized order picking and replenishment functionality.</p><p>The announcement of the standard has provided retailers with the impetus to commit to this technology. ABI Research claims 185 million ESL units were shipped last year, and that by 2028 annual shipments will reach 558 million, with a total installed base of some three billion ESLs. For example, Fortune 500 leading light and U.S. retail behemoth Walmart has entered an agreement to roll out 60 million digital shelf labels across 500 locations over the next 12 to 18 months. Others will follow.</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>

Electronic shelf labels (ESL) are connected, low-power ‘e-paper’ display devices that can replace traditional paper labels and can display text, numbers, icons, lines, barcodes and pictures. They enable retailers to automatically update individual shelf price labels from a central point across multiple stores and branches—or in certain geographic locations—at the touch of a button.

Bluetooth Electronic Shelf Label standard heralds new retail dawn

<p id="isPasted"><strong>Unveiling Battery Performance Secrets</strong></p><p>Explore the intricacies of LPWAN IoT device battery performance. Factors impacting battery life are dissected, aiding tailored battery selection for specific applications. Optimization strategies maximize battery efficiency, enabling peak device performance and extended lifecycles.</p><p><strong>Managing Power Consumption</strong></p><p>IoT devices demand efficient power management. Factors like data rate, duty cycle, and connectivity impact battery life. Learn how to optimize sleep modes and wake-up intervals, as well as transmission power, to conserve energy effectively.</p><p><strong>Choosing the Right Battery</strong></p><p>Battery selection is critical. Discover how matching battery behavior with device needs ensures reliable power. Follow the guide in selecting batteries aligned with your application requirements.</p><p><strong>Real-World Case Study</strong></p><p>The white paper &ldquo;Powering IoT devices: How to choose the right battery and make it last includes&rdquo; a practical case study illustrating battery selection techniques for a waste management IoT deployment. Learn how to profile your IoT device from prototype, estimate battery life, and analyze different battery profiles.</p><p><strong>Proactive Battery Profiling</strong></p><p>Profiling your IoT device, even during early prototyping, is crucial. The white paper provides guidance on power profiling, emulation, and iterative refinement throughout your product development.</p><p><strong>Comprehensive Battery Insights</strong></p><p>Battery data sheets are just the beginning. We delve deeper, profiling batteries across brands, chemistries, and form factors to understand subtle performance differences that influence decision-making.</p><p><strong>Download the White paper</strong></p><p>Discover the secrets to sustainable IoT device power management. Download the <a href="https://bit.ly/46koBoX" target="_blank" rel="noopener noreferrer">white paper</a> to empower your LPWAN IoT deployments with optimized battery solutions.</p>

Long battery life is one of key enablers of IoT 

In the rapidly evolving landscape of IoT, battery life is paramount for device sustainability. We dissect the challenges and strategies for battery longevity of LPWAN IoT devices. Explore battery profiling and optimization for extended device life and reduced costs.

Powering IoT Devices for Sustainable Performance

<p id="isPasted"><strong>On 16 May, the world came to High Tech Campus Eindhoven to celebrate women in tech, their male allies and to get a preview of what the future holds.&nbsp;</strong></p><p><strong>They were not disappointed.</strong></p><p><strong>The theme of the fourth annual Fe+male Tech conference was &ldquo;Dare to Grow,&rdquo; and that was the consistent message from speakers: be bold, embrace risk and find your career path in a tech world where women in leadership roles are still a rarity. Or, as ASML&rsquo;s Wendy Gehoel van Ansem put it, an event meant to send you away &ldquo;confident so that you kick ass.&rdquo;</strong><br><br>If you think women don&rsquo;t belong in tech and STEM jobs, we know 300 women who&rsquo;d passionately disagree.&nbsp;More than 300 women, as well as male allies, came from the Netherlands, other countries in Europe and the United States for the sellout event.</p><p>Watch the recording of the plenary program here:</p><p><span contenteditable="false" draggable="true" class="fr-video fr-deletable fr-fvc fr-dvb fr-draggable"><iframe width="640" height="360" src="https://www.youtube.com/embed/BmPFVFMz8Mo?&wmode=opaque&rel=0&enablejsapi=1&origin=https://www.wevolver.com" frameborder="0" allowfullscreen="" 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></p><p id="isPasted">They came to hear 30 speakers and panel members, including Lori Glover from the Massachusetts Institute of Technology&rsquo;s Computer Science Artificial Intelligence Laboratory, Kimberly Fuqua from Microsoft Netherlands, workshops, panels and off-the-charts networking. Also participating were executives from Eindhoven&rsquo;s signature tech corporations, including Moyra McManus and Marco Pieters from ASML, the Eindhoven-based semiconductor giant.</p><h2>Trailblazing Women Throughout History</h2><p>With her keynote &quot;She Who Dares, Wins: Women Leading Fearlessly in Tech,&rdquo; Glover set the tone early, revealing some of the unsung female tech heroes whose trailblazing achievements never got the recognition they should have. They included Hedy Lamarr, the 1930s movie star who invented the frequency-hopping signal that makes wi-fi, Bluetooth and GPS possible, and the women at the Jet Propulsion Lab who did the high-level mathematics and trajectory calculations that made space exploration possible. These are the women who were actually referred to as &ldquo;computers.&rdquo;</p><p><span class="fr-img-caption fr-fic fr-dib" style="width: 768px;"><span class="fr-img-wrap"><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjk0NjkwMzc1MTA0LWlLWXBJUURBLndlYnAiLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjk1MCwiZml0IjoiY292ZXIifX19" style="width: 766px;" class="fr-fic fr-dib"><span class="fr-inner"><em id="isPasted">Lori Glover of MIT&nbsp;</em></span></span></span></p><p id="isPasted">Glover advised the current generation of women in tech to take full advantage of new opportunities opening up at tech companies: &ldquo;When you go to meetings, take a seat at the table, not along the wall.&rdquo;</p><p>Then, Glover opened a new chapter in Eindhoven&rsquo;s history by inviting attendees to connect directly with her and her CSAIL program at MIT, the legendary engineering school that&rsquo;s home to dozens of world-class scientists and Nobel Prize laureates, including Sir Tim Berners-Lee, inventor of the Internet. Glover also gave a detailed presentation about MIT and CSAIL at the AI Innovation Center as part of the conference.</p><p>THAT was just the beginning of the day.</p><p>In 1988, 35 years ago, women earned 33 percent of computer science degrees, but that fell to less than 20 percent by 2016. Women have only about 30 percent of top jobs in tech. More women are going into tech, but half drop out by age 35. Why are women dropping out? Glover asked. &ldquo;Why aren&rsquo;t women moving up?&rdquo;</p><h2>Tech to Career: Exploring Breakout Sessions</h2><p>Conference attendees chose to attend one of six tech and seven career breakout sessions led by inspiring women in their fields and included topics such as data science, personalized medicine, wearable devices and cancer research. A panel of deep-tech female founders talked about the challenges and rewards of their venture journeys. As usual, attendees found it hard to choose only one breakout session!</p><p>Career breakout topics included imposter syndrome, exhaustion, personal presence, equality for bi-cultural women, confidence boosting and how to be an effective role model. Several presentations and workshops addressed the unique career challenges women in tech face, including the career penalty for taking time out of the workforce. Glover cited statistics and trends indicating so much more has to be done.</p><p><span class="fr-img-caption fr-fic fr-dib" style="width: 768px;"><span class="fr-img-wrap"><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjk0NjkwNDQxMTE3LTFHOEE3OTE5LndlYnAiLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjk1MCwiZml0IjoiY292ZXIifX19" style="width: 766px;" class="fr-fic fr-dib"><span class="fr-inner"><em id="isPasted">Diana M&auml;kel &nbsp;(Thermo Fisher) during her Tech Breakout about data science</em></span></span></span></p><h2 id="isPasted">Fix the system, not the girls</h2><p>Sahar Yadegari and Rian de Heur from VHTO led a workshop on how we can &ldquo;Fix the system, not the girls&rdquo; so more females can be inspired by science and technology from an early age. With women only making up 16 percent of the Dutch STEM workforce and the Netherlands ranking No. 1 in strongest gender stereotypes, their talk was hard-hitting and eye-opening.</p><p>Many audience members shared deeply personal stories about their experiences fighting gender bias with their children. With advice ranging from women in tech being more visible to encouraging a growth mindset in children, every attendee walked away with valuable insights and actionable tasks.</p><p>The day was not just about corporates, even though Eindhoven is home to multiple dominant semiconductor companies such as ASML and NXP. It was also about a new generation of female entrepreneurs at startups and scale-ups.</p><h2>Spectrometer-In-A-Chip</h2><p>Kaylee Hakkel, COO of MantiSpectra, said her company is taking the functionality of a spectrometer and shrinking it down to the size of a chip. When trained with AI and a robust database, this deep-tech solution uses light to detect various types of materials, and it will be used to solve societal challenges, problems from detecting what type of plastic is pulled from the ocean to quality control in food and beverage to sampling illegal drugs.</p><p><span class="fr-img-caption fr-fic fr-dib" style="width: 768px;"><span class="fr-img-wrap"><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjk0NjkwNDkwNjI1LTFHOEE3OTM0LndlYnAiLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjk1MCwiZml0IjoiY292ZXIifX19" style="width: 766px;" class="fr-fic fr-dib"><span class="fr-inner"><em id="isPasted">Kaylee Hakkel (MantiSpectra)&nbsp;</em></span></span></span></p><p>At only 28 years old, Kaylee already has a wealth of experience from being a startup co-founder. Her talk drew an audience of women that filled the room and who asked probing questions about the science and applicability of MantiSpectra&rsquo;s solution.</p><p><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjk0NjkwNTE5MTI2LTFHOEE3NDQ1LndlYnAiLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjk1MCwiZml0IjoiY292ZXIifX19" style="width: 766px;" class="fr-fic fr-dib"></p><h3 id="isPasted"><strong>Here are some highlights from the day, curated by conference attendees:</strong></h3><ul><li>Lori Glover noted that leaders&nbsp;aren&rsquo;t necessarily bosses. Leaders are people with intelligent, curious minds and the vision to see what&rsquo;s possible. They have exceptional communication skills and the ability to inspire. They show responsibility and share credit with others.<br><br></li><li>In her keynote, Microsoft&rsquo;s Kimberly Fuqua told attendees that women in tech shouldn&rsquo;t underestimate the human touch. &ldquo;Don&rsquo;t call them soft skills anymore. Call them superpower skills,&rdquo; she said.<br><br></li><li>Fuqua advised continually reevaluating your relationships. &ldquo;Take note of the energy of the relationship. You are responsible for the energy you bring to the relationship and the energy you take away from it.&quot;</li></ul><p><span class="fr-img-caption fr-fic fr-dib" style="width: 768px;"><span class="fr-img-wrap"><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjk0NjkwNTM5MDc4LTFHOEE4MjI1LndlYnAiLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjk1MCwiZml0IjoiY292ZXIifX19" style="width: 766px;" class="fr-fic fr-dib"><span class="fr-inner"><em id="isPasted">Kimberly Fuqua (Microsoft)&nbsp;</em></span></span></span></p><ul id="isPasted"><li>ASML executives and others noted that while men tend not to take &ldquo;no&rdquo; for an answer, reapplying over and over for jobs they were rejected for until they get it, women typically only apply once or twice.<br><br></li><li>The male allies panel featured Marco Pieters, ASML; Andy L&uuml;rling, LUMO Labs; Johan Feenstra, SMART Photonics and Ed Heerschap, City of Eindhoven. Eindhoven-based serial entrepreneur Johan Feenstra told the audience during the panel discussion,&nbsp;&ldquo;We need to pay the role and not the person.&rdquo; Feenstra said women and highly skilled internationals often don&rsquo;t negotiate and fall behind when it comes to salary.<br><br></li><li>Ed Heerschap, Living In Program Coordinator for the city of Eindhoven, noted that families are crucial to Eindhoven&rsquo;s tech talent shortage because many highly skilled internationals won&rsquo;t come unless they can bring spouses and families.</li></ul><h2>Conference Donates to Gender Diversity Cause</h2><p>The fourth edition of the Fe+male Tech Heroes conference marked the first time organizers charged for the conference. Attendees paid &euro;30 for a day full of amazing speakers, meaningful content, great food and networking while also contributing to a worthy cause. More than 80 percent of ticket sales went to VHTO, a Dutch foundation and Expertise Center that actively champions and empowers Gender Diversity in STEM, Engineering, and IT.</p><p>And it wasn&rsquo;t just the attendees with key takeaways. Keynote speakers and breakout session speakers also saw great value in the conference.&nbsp;&ldquo;The best word I can use to describe about how I felt about the conference is GRATEFUL!! The atmosphere was so electric, the people and other presenters were so encouraging with a learning and curious mindset. I will make this event one of my annual &#39;not to miss&#39; going forward,&rdquo; said Kimberly Fuqua.</p><p>Keynote speaker Dan Jing Wu, CEO and Co-Founder VivArt-X and <em>co-founder of fashion company NOYA NOIR,&nbsp;</em>said &quot;I&#39;m so impressed with the organization and the audience was so kind and responsive. It gave me so much energy!&rdquo;</p><p>And that&rsquo;s a wrap! Watch this space and mark your calendars for other Fe+male Tech Heroes events. If you&rsquo;re not already a member, join the <a href="https://insights.hightechcampus.com/female-tech-heroes" rel="noopener" target="_blank">Fe+male Tech Heroes community</a> and stay updated about news and events!</p><p><span class="fr-img-caption fr-fic fr-dib" style="width: 768px;"><span class="fr-img-wrap"><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjk0NjkwNTY2MzY1LTFHOEE4MzY4LTIud2VicCIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 766px;" class="fr-fic fr-dib"><span class="fr-inner"><em id="isPasted">Hilde de Vocht (Fe+male Tech Heroes), Rian van Heur (VHTO), Sahar Yadegari (VHTO), Ingelou Stol (Fe+male Tech Heroes)&nbsp;</em></span></span></span></p>

On 16 May, the world came to High Tech Campus Eindhoven to celebrate women in tech, their male allies and to get a preview of what the future holds. 

Breaking Barriers and Forging Paths: Key Lessons from the Fe+male Tech Heroes Conference 2023

Low-power computer vision provides a new opportunity to gain a practical understanding of the world through data collection and vision in remote areas.


Leveraging low-power embedded computer vision to solve urgent sustainability and safety challenges

Harnessing the Power of TinyML and Machine Learning: A Deep Dive into Modern Healthcare Innovations


Revolutionizing Healthcare: The Profound Impact of TinyML and Machine Learning on Medical Outcomes

<p id="isPasted">The world of technology is in a constant state of flux, and the Internet of Things (IoT) is no exception. Today, &ldquo;IoT&rdquo; no longer refers to simple machines &ldquo;just talking&rdquo; to each other as it once was. Rather, modern IoT devices, or &ldquo;Connected Devices,&rdquo; are much smarter. They are now mostly Linux-based devices, such as connected mobility, connected robots, connected trackers, connected street lights, and connected payment devices that require continuous and ubiquitous connectivity. Before we dive into what this connectivity looks like today and how we came to design it the way we did, let&rsquo;s briefly look at the past.</p><p>&nbsp;</p><h2>The Early Days: IoT Devices with Limited Connectivity</h2><p>IoT devices used to be primarily designed to serve specific functions, such as monitoring environmental conditions, optimizing energy usage, or tracking inventory. These devices were often constrained by limited processing power and connectivity options.</p><p>While these IoT devices were groundbreaking for their time, they came with several limitations. As cost considerations often took precedence over user experience, manufacturers&rsquo; goals were to produce high quantities of these devices with basic functionality. The connectivity needs were confined to localized networks, such as Bluetooth and WiFi. &nbsp;Today, we can all agree that the promise of a boom of endless IoTs everywhere has fallen short of expectations.</p><p>&nbsp;</p><h2>The Evolution: From Limited IoT Devices to Connected Devices</h2><p>Fast forward to the present, and we see sophisticated machines have transcended their previous limitations and can operate with advanced features like real-time precise tracking, AI/ML capabilities, log storage, and continuous firmware updates. Because of the software component of the way they are connected (more on that later), they are able to prioritize the user experience and cyber posture, allowing them to truly enrich the way we work, the way we travel, the way we consume, and the way we live. We refer to these as &ldquo;Connected Devices&rdquo;, not just &ldquo;IoT&rdquo;.</p><p><img data-fr-image-pasted="true" src="https://monogoto.io/wp-content/uploads/2023/08/CEO-Series-Part-1-graph_Revised.png" alt="" width="728" height="893" srcset="https://monogoto.io/wp-content/uploads/2023/08/CEO-Series-Part-1-graph_Revised.png 728w, https://monogoto.io/wp-content/uploads/2023/08/CEO-Series-Part-1-graph_Revised-245x300.png 245w" sizes="(max-width: 728px) 100vw, 728px" class="fr-fic fr-dii"></p><p>&nbsp;</p><h2>The Turning Point</h2><p>The evolution of IoT from its humble beginnings to the realm of sophisticated Connected Devices marks a significant milestone in technology&rsquo;s progress. Calling these devices &ldquo;IoT&rdquo; doesn&rsquo;t do justice to them, or to their developers.&nbsp;</p><p>These teams require tools and technologies that conform to &ldquo;cloud best practices,&rdquo; allowing the product owner to deliver the best experience and value to their customers. For example, they continuously:</p><ul><li>Deploy software updates to their globally-deployed devices;</li><li>Use Network Capturing tools or log extraction for debugging;</li><li>Rely on Deep Packet Inspection or Data Leak Prevention for cyber posture;</li><li>Use Geolocation routing for compliance (GDPR for example).</li></ul><p>&nbsp;</p><h3>Key Takeaways</h3><p>It&rsquo;s time for a whole new connectivity narrative. Connectivity depends on context, as it offers versatility and flexibility, and serves multiple purposes across different stages of the product life cycle, for both legacy and modern businesses. What&rsquo;s really new is that it:</p><ul><li>Leverages advanced cellular network capabilities, public networks/private LTE/5G, and satellite, enabling enterprises to ensure their devices are continuously and seamlessly connected in the most reliable way.&nbsp;</li><li>Prioritizes user experience, control, and ease of management across devices.</li><li>Adheres to the most advanced cybersecurity requirements, both in terms of being able to enforce policies based on geographic location and react to real-time events, for example, automatically blocking traffic in response to abnormal behavior or Geolocation routing for GDPR compliance.</li></ul><p>It&rsquo;s a brand-new connected world. Entire industries are reinventing themselves. Leading enterprises are transforming their products by connecting them. New technologies such as Software-Defined Connectivity (SDC) are taking this revolution further, allowing everyone to consume connectivity just the way AWS transformed the way computing is consumed. Time is saved, money is saved, productivity is boosted, and better and more sophisticated Connected Devices are introduced to the market.</p><p>All of this is made possible by a new type of connectivity Connected Devices rely on. More on that in the next blog&hellip;</p>

The world of technology is in a constant state of flux, and the Internet of Things (IoT) is no exception. 

The Rise of Connected Devices: Redefining the Internet of Things (IoT)

<p id="isPasted">The Sustainable Development Goals (SDGs) advocated by the United Nations for the realization of a sustainable society include multiple goals related to environmental conservation.</p><p>Since the start of the industrial revolution in the latter half of the 18th century, humankind has harvested the materials of the natural world on a massive scale, processed them into industrial products, and consumed them in large quantities. Subsequently, a large volume of waste products was also produced due to such production and consumption. As a result, things that do not belong were dispersed in places in nature where they should not be, which is causing the environment to be destroyed. In fact, desertification due to the logging of tropical rainforests, the destruction of marine ecosystems due to microplastics<sup>*1</sup>, as well as space junk which impedes future space development, and various other effects are becoming apparent.</p><p>*1 Microplastics are plastics that are broken down to a size that is invisible to the naked eye during the process in which discarded plastic products flow into the ocean. They continue to drift in the ocean for a long time and destroy the marine ecosystem when marine organisms take the microplastics into their bodies, and there are also concerns that they may pose a risk to the health of people who eat such marine organisms.</p><p>When it comes to conservation of the global environment, people are apt to focus on the decarbonization of energy. However, such destruction of the natural environment also requires immediate measures similar to decarbonization. Moreover, the movement to utilize the latest technologies to attempt to resolve environment-related issues has become increasingly active. Here, we select non-decarbonization initiatives from within the &ldquo;cleantech&rdquo; technology development movement aimed at environmental conservation to focus on and describe the measures that utilize ICT (information and communications technology) in particular.</p><p><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjkzMjEyOTk4NjA2LXZhcmlvdXMtdGVjaC03LTEucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 766px;" class="fr-fic fr-dib"></p><h2 id="isPasted">Cleantech is a cluster of multidisciplinary technologies</h2><p>&ldquo;Cleantech&rdquo; is a neologism that combines the idea of restoring the natural environment to a &ldquo;clean&rdquo; state and &ldquo;technology.&rdquo; Cleantech&rsquo;s aims and the scientific and technological knowledge that are applied are extremely diverse.</p><p>For example, in the case of alternative plastics, the development of materials to replace substances, which may have a negative impact on the environment if they are simply discarded, into naturally degrading substances is one cleantech initiative. Accordingly, knowledge of fields such as chemistry and materials engineering is required. Moreover, there is also a method that involves reliably separating waste that contains hazardous substances, detoxifying it, and returning it to nature. In order to put that method into practice, you need sensing technologies that sort out hazardous substances, chemistry to detoxify the substances, as well as ICT to reliably and smoothly advance the process of collecting, separating, and detoxifying the waste.</p><p>Until now, we have gathered the products that are useful for daily life and social activities from the natural world, processed them into industrial products, and skillfully used them. However, by-products during processing and waste as well as products that have served their purpose after use were discarded through methods such as &ldquo;burning,&rdquo; &ldquo;burying,&rdquo; and &ldquo;discharging.&rdquo; That is because it is much more difficult to competently discard something than it is to make it and because people incorrectly believe that &ldquo;if they only throw away a little bit of trash, nature will not be destroyed.&rdquo; However, while humanity has looked away, nature was in fact certainly being destroyed.</p><h2>The &ldquo;bird&rsquo;s eye,&rdquo; &ldquo;insect&rsquo;s eye,&rdquo; and &ldquo;fish&rsquo;s eye&rdquo; that are essential to cleantech</h2><p>In order to take effective environmental conservation measures, we need to accurately assess the impact on the natural world of the processes of production, consumption and use, and disposal. There are reasons to utilize ICT here.</p><p>Generally, as perspectives to keep in mind when visualizing and optimizing information, there is the &ldquo;bird&rsquo;s eye&rdquo; that looks at the entire picture, the &ldquo;insect&rsquo;s eye&rdquo; that pays close attention to the details, and the &ldquo;fish&rsquo;s eye&rdquo; that grasps the change and flow of time and state. Within environmental measures as well, information processing from a multifaceted perspective using these three types of eyes is essential. That is because there is a need to take an extensive view of society as a whole, know the status of the enormous number of items used in the world, and track their origin and movements.</p><p>For example, in order to respond to waste plastic-related issues, let us say that one company changed its plastic containers to paper containers. At first glance, it may appear to be the appropriate measure, but if paper is used as the material for new containers, the destruction of forests will advance. This cannot be said to be a proper environmental measure. Each company must take a bird&rsquo;s-eye view of the supply chain for their own products and implement environmental measures. Measures from a multifaceted view cannot be accomplished with only the limited senses and cognitive abilities of humans. For that very reason, there is a need to utilize ICT with its enormous computing power.</p><h2>Recycling society that minimizes the final discarding of items</h2><p>The products obtained from nature and the industrial products that are made by processing them are essential for living an affluent lifestyle. However, in order to make affluence into something sustainable, we need to decrease the self-centered discarding of items and wasteful consumption.</p><p>As a form of the ideal social system for environmental conservation, governments around the world are now aiming to realize the &ldquo;recycling society.&rdquo; The recycling society refers to a society that efficiently uses limited resources to circulate them through recycling, etc. while minimizing the items that are permanently discarded without waste in the future while continuing to effectively use resources. It is believed that the recycling society will become a radical measure with respect to both the issues of environmental measures and the depletion of natural resources. In Japan, the &ldquo;Basic Act on Establishing a Sound Material-Cycle Society&rdquo; was officially announced in 2000, and efforts are underway to define, etc. the obligations, etc. of the nation, local public bodies, and business operators.</p><p>The recycling society concept promotes the 3Rs consisting of &ldquo;reduce&rdquo; to curtail the occurrence of waste, &ldquo;reuse&rdquo; to reuse resources, and &ldquo;recycle&rdquo; to recycle by adding processing (Figure 1). The EU has already adopted a law that prohibits the distribution of single-use plastics by 2021, and other specific measures are being implemented such as increasing the collection rate of plastic bottles to 90% by 2029. Moreover, there are now also companies that utilize big data and AI to analyze past market demand trends and increase forecasting accuracy to prevent the excessive procurement of raw materials and waste loss due to the production of products and reduce resource consumption.</p><p><span class="fr-img-caption fr-fic fr-dib" style="width: 768px;"><span class="fr-img-wrap"><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjkzMjEzMDE5MjIzLXZhcmlvdXMtdGVjaC03LTJlbi5wbmciLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjk1MCwiZml0IjoiY292ZXIifX19" style="width: 766px;" class="fr-fic fr-dib"><span class="fr-inner">Figure 1 Flow of goods in a recycling society</span></span></span></p><h2 id="isPasted">Sharing information about items handled through arterial and venous physical distribution</h2><p>Moreover, there is also a movement to make it mandatory for companies to perform an environmental impact assessment through the entire product and service life cycle (flow from the extraction of resources to raw material production, product production, distribution, and consumption to disposal and recycling), which is called the &ldquo;Life Cycle Assessment&rdquo; (LCA). In order to implement environmental measures according to the LCA, the impact on the environment must be minimized from various perspectives such as the destruction of the ozone layer, acidification, land/sea/river/atmospheric pollution, toxicity to humans, and the impact on the ecosystem, etc. The evaluation method is standardized as the &ldquo;ISO 14040&rdquo; and &ldquo;ISO 14044&rdquo; international standards for environmental management through the ISO (the International Organization for Standardization).</p><p>In addition, initiatives are also underway to create a &ldquo;venous physical distribution&rdquo; mechanism that collects and sorts marketed products and waste products in a flow that runs in the opposite direction of the typical supply chain to smoothly facilitate reuse and recycling. To effectively and efficiently carry out venous physical distribution, nothing will be more important than accurately assessing the origin and condition of products that appeared and were used in the market, sharing that information in society, and promoting the appropriate 3Rs (Figure 2). Therefore, the traceability to track and visualize the production, distribution, and usage processes of individual products will become important.</p><p><span class="fr-img-caption fr-fic fr-dib" style="width: 768px;"><span class="fr-img-wrap"><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjkzMjEzMDQzMTA3LXZhcmlvdXMtdGVjaC03LTNlbi5qcGciLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjk1MCwiZml0IjoiY292ZXIifX19" style="width: 766px;" class="fr-fic fr-dib"><span class="fr-inner">Figure 2 Sharing information about handled items between typical distribution (arterial physical distribution) and venous physical distribution</span></span></span></p><p id="isPasted">To ensure traceability, the utilization of technologies such as barcodes and QR codes, RFID to wirelessly write product and distribution information into semiconductor chips attached to products, as well as IoT (Internet of Things), which will connect individual products to the Internet in the future, etc., are essential. In addition, attempts are already underway to utilize the newest forms of ICT such as the blockchain<sup>*2</sup> to track the process as a discarded product is recycled into a new product through the supply chain and the collaborative operations of companies.</p><p>*2 Blockchain is a technology that encrypts digital information that records the transaction details and process and ensures information reliability by having it supplied by many people on the Internet. In addition to being used as a technology for ensuring the value of encrypted assets, it is also applied to automated transactions using machines.</p><p>Environmental issues are social issues that are difficult to get a real sense of in daily life, but we are in a critical situation where a bright future cannot be pictured without initiatives aimed at conservation. It can be said that our bright future depends on the evolution and utilization of cleantech.</p><hr id="isPasted"><p><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjkzMjEzMjEwNTMxLTE2OTMyMTMyMTA1MzEucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" class="fr-fic fr-dii"></p><p>If you have any questions based on this article that you would like to discuss with an expert at Murata, don&#39;t hesitate to reach out. There&#39;s an entire team ready to support you with your question.</p><p><a href="https://www.murata.com/en-eu/contactform?&Detail=Wevolver%20request" target="_blank" rel="nofollow" class="button-main-action">GET IN TOUCH</a></p>

Electronic Technology Supporting the Evolution of “Next Tech”

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<p>This article was first published on <a href="https://news.mit.edu/2023/ai-technique-robots-manipulate-objects-whole-bodies-0824" target="_blank" rel="noopener noreferrer" id="isPasted">MIT News</a>. &nbsp;</p><hr><p id="isPasted">Imagine you want to carry a large, heavy box up a flight of stairs. You might spread your fingers out and lift that box with both hands, then hold it on top of your forearms and balance it against your chest, using your whole body to manipulate the box.&nbsp;</p><p>Humans are generally good at whole-body manipulation, but robots struggle with such tasks. To the robot, each spot where the box could touch any point on the carrier&rsquo;s fingers, arms, and torso represents a contact event that it must reason about. With billions of potential contact events, planning for this task quickly becomes intractable.</p><p>Now MIT researchers found a way to simplify this process, known as contact-rich manipulation planning. They use an AI technique called smoothing, which summarizes many contact events into a smaller number of decisions, to enable even a simple algorithm to quickly identify an effective manipulation plan for the robot.</p><p><span contenteditable="false" draggable="true" class="fr-video fr-deletable fr-fvc fr-dvb fr-draggable"><iframe width="640" height="360" src="https://www.youtube.com/embed/D8VIzBRy_m4?&wmode=opaque&rel=0&enablejsapi=1&origin=https://www.wevolver.com" frameborder="0" allowfullscreen="" 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></p><p id="isPasted">While still in its early days, this method could potentially enable factories to use smaller, mobile robots that can manipulate objects with their entire arms or bodies, rather than large robotic arms that can only grasp using fingertips. This may help reduce energy consumption and drive down costs. In addition, this technique could be useful in robots sent on exploration missions to Mars or other solar system bodies, since they could adapt to the environment quickly using only an onboard computer. &nbsp; &nbsp; &nbsp;</p><p>&ldquo;Rather than thinking about this as a black-box system, if we can leverage the structure of these kinds of robotic systems using models, there is an opportunity to accelerate the whole procedure of trying to make these decisions and come up with contact-rich plans,&rdquo; says H.J. Terry Suh, an electrical engineering and computer science (EECS) graduate student and co-lead author of a&nbsp;<a href="http://groups.csail.mit.edu/robotics-center/public_papers/Pang22.pdf" target="_blank" data-lf-fd-inspected-kn9eq4roawkarlvp="true">paper</a> on this technique.</p><p>Joining Suh on the paper are co-lead author Tao Pang PhD &rsquo;23, a roboticist at Boston Dynamics AI Institute; Lujie Yang, an EECS graduate student; and senior author Russ Tedrake, the Toyota Professor of EECS, Aeronautics and Astronautics, and Mechanical Engineering, and a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL). The research appears this week in&nbsp;<em>IEEE Transactions on Robotics.</em></p><h2><strong>Learning about learning</strong></h2><p>Reinforcement learning is a machine-learning technique where an agent, like a robot, learns to complete a task through trial and error with a reward for getting closer to a goal. Researchers say this type of learning takes a black-box approach because the system must learn everything about the world through trial and error.</p><p>It has been used effectively for contact-rich manipulation planning, where the robot seeks to learn the best way to move an object in a specified manner.</p><p>But because there may be billions of potential contact points that a robot must reason about when determining how to use its fingers, hands, arms, and body to interact with an object, this trial-and-error approach requires a great deal of computation.</p><p>&ldquo;Reinforcement learning may need to go through millions of years in simulation time to actually be able to learn a policy,&rdquo; Suh adds.</p><p>On the other hand, if researchers specifically design a physics-based model using their knowledge of the system and the task they want the robot to accomplish, that model incorporates structure about this world that makes it more efficient.</p><p>Yet physics-based approaches aren&rsquo;t as effective as reinforcement learning when it comes to contact-rich manipulation planning &mdash; Suh and Pang wondered why.</p><p>They conducted a detailed analysis and found that a technique known as smoothing enables reinforcement learning to perform so well.</p><p>Many of the decisions a robot could make when determining how to manipulate an object aren&rsquo;t important in the grand scheme of things. For instance, each infinitesimal adjustment of one finger, whether or not it results in contact with the object, doesn&rsquo;t matter very much. &nbsp;Smoothing averages away many of those unimportant, intermediate decisions, leaving a few important ones.</p><p>Reinforcement learning performs smoothing implicitly by trying many contact points and then computing a weighted average of the results. Drawing on this insight, the MIT researchers designed a simple model that performs a similar type of smoothing, enabling it to focus on core robot-object interactions and predict long-term behavior. They showed that this approach could be just as effective as reinforcement learning at generating complex plans.</p><p>&ldquo;If you know a bit more about your problem, you can design more efficient algorithms,&rdquo; Pang says.</p><h2><strong>A winning combination</strong></h2><p>Even though smoothing greatly simplifies the decisions, searching through the remaining decisions can still be a difficult problem. So, the researchers combined their model with an algorithm that can rapidly and efficiently search through all possible decisions the robot could make.</p><p>With this combination, the computation time was cut down to about a minute on a standard laptop.</p><p>They first tested their approach in simulations where robotic hands were given tasks like moving a pen to a desired configuration, opening a door, or picking up a plate. In each instance, their model-based approach achieved the same performance as reinforcement learning, but in a fraction of the time. They saw similar results when they tested their model in hardware on real robotic arms.</p><p>&ldquo;The same ideas that enable whole-body manipulation also work for planning with dexterous, human-like hands. Previously, most researchers said that reinforcement learning was the only approach that scaled to dexterous hands, but Terry and Tao showed that by taking this key idea of (randomized) smoothing from reinforcement learning, they can make more traditional planning methods work extremely well, too,&rdquo; Tedrake says.</p><p>However, the model they developed relies on a simpler approximation of the real world, so it cannot handle very dynamic motions, such as objects falling. While effective for slower manipulation tasks, their approach cannot create a plan that would enable a robot to toss a can into a trash bin, for instance. In the future, the researchers plan to enhance their technique so it could tackle these highly dynamic motions.</p><p>&ldquo;If you study your models carefully and really understand the problem you are trying to solve, there are definitely some gains you can achieve. There are benefits to doing things that are beyond the black box,&rdquo; Suh says.</p><hr><p>&quot;Reprinted with permission of <a href="https://news.mit.edu/2023/ai-technique-robots-manipulate-objects-whole-bodies-0824" target="_blank" rel="noopener noreferrer" id="isPasted">MIT News</a>&quot; &nbsp;</p>

MIT researchers developed an AI technique that enables a robot to develop complex plans for manipulating an object using its entire hand, not just the fingertips. This model can generate effective plans in about a minute using a standard laptop. Here, a robot attempts to rotate a bucket 180 degrees. Image: Courtesy of the researchers

With a new technique, a robot can reason efficiently about moving objects using more than just its fingertips.

AI helps robots manipulate objects with their whole bodies

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