<h2 id="isPasted">The hidden waste</h2>At least 15 billion&nbsp;<a href="https://en.wikipedia.org/wiki/Primary_cell" target="_blank">primary batteries</a> are being disposed of yearly worldwide. The world is getting better at recycling, which is excellent news. However, the bad news is that we are still throwing batteries that are not fully utilized. Unused battery capacity is hidden waste that goes unnoticed for consumer electronics, but it is getting noticeably annoying for the businesses within the Internet of Things (IoT) and medical space. IoT and medical device suppliers need to deliver on promised battery life but don’t know how well their devices are using the batteries.<h2>The good or bad fit</h2>Batteries have specific performance characteristics. The electronic device needs to have a matching power consumption profile for the capacity to be fully used. The power consumption profile depends on the choice of hardware, layers of software and connectivity and the actual device usage. Suppose the power profile doesn’t match the battery characteristics. There will be energy that is never extracted, which is valid for primary batteries and rechargeable batteries for any application and industry. There could be a good or a bad fit for your small loT sensor, a smartwatch or the electrical vehicle (EV) that you are developing.Furthermore, the batteries can be of bad quality. For everyone working in development projects where second sourcing of components is essential for the reliability or cost-down activity (and batteries are one of the most expensive components), validating the battery performance is the key. You may have figured out your device’s power consumption performance but are still underutilizing the energy source due to a particular bad battery batch or an overall bad design and quality. The difference between brands is noticeable.<h2>Unused battery capacity</h2>One thing is for sure, there is no such thing as utilizing the battery to 100%, but you can get close. On the other hand, a bad match can be pretty bad. Our testing shows between 30-50%, on average, of capacity never being used.Let’s look at an example of an IoT device with a coin cell battery.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1721608956514-connect-device-undertest-to-otii-1024x768.png" style="width: 100%px;" class="fr-fic fr-dib">Table 1. Capacity of batteries from two brands shown for an ideal, data sheet case and actual measured power consumption profile. Used capacity differs between the two batteries despite the same type.The battery data sheets usually show a typical capacity that you could expect if you match your device well with the battery and use it in a normal temperature type of use case. However, suppose the matching is not good or the battery is bad quality. You may be limited to utilizing only 16% of the available energy, as for Battery 1 in table 1 above.&nbsp;If you are interested, you can read the technical benchmark study where this example is from&nbsp;<a href="https://www.qoitech.com/blog/will-my-lorawan-iot-device-work-with-a-coin-cell-battery/" target="_blank">here</a>.&nbsp;<h2>Battery life impacts your business</h2>Unused battery capacity can make or break a business. As a device supplier, you can not guarantee battery life if you don’t understand how well your product and the energy source are matched. The hidden energy waste can mean countless and expensive maintenance and replacements of the batteries and costly IT downtime, either for you or your customer.Let’s play with an example of having 10 000 IoT devices deployed for tracking purposes. In general, we hear five years of battery life presented. Though not guaranteed, this is most likely only calculated by simply dividing battery capacity with an average current across use cases. Also, the battery characteristic is taken from the datasheet for a ‘typical’ use case. In this case, there will be a normal distribution of batteries running out, which means at least twice during the five years, there will be changes in batteries. At the worst, you may be looking at 10 000 x 2 x $300 (approx. cost per battery change) = $6M in maintenance cost per the life cycle. Who is paying for this, you or your customer?If the IoT solution that you are providing is for mission critical purposes, then you have to consider the IT downtime. According the Gartner the downtime can be very expensive, up to $5 600 per minutes are mentioned&nbsp;<a href="https://www.the20.com/blog/the-cost-of-it-downtime/" target="_blank">here</a>. Doing an software over the upgrade for the deployed IoT device and not checking that the upgrade doesn’t have negative impact on the battery life and thus your&nbsp;<a href="https://www.zdnet.com/article/google-nests-battery-drain-chilly-users-turn-up-heat-over-thermostat-software-glitch/" target="_blank">business</a> is really risky.<h2>What can be done?</h2>Start measuring! Gain insights into how your device behaves for different use cases and start characterizing and validating your batteries. It is simple as that. To understand your device, you can use&nbsp;<a href="https://www.qoitech.com/otii-arc-pro/" target="_blank">Otii Arc</a> and&nbsp;<a href="https://www.qoitech.com/automation-toolbox/" target="_blank">Otii Automation Toolbox</a> for software quality assurance. For battery validation and analytics,&nbsp;<a href="https://www.qoitech.com/battery-toolbox/" target="_blank">Otii Battery Toolbox</a> can help. You can&nbsp;<a href="https://www.qoitech.com/demo/" target="_blank">book a demo</a> to see what solution fits your organization the best for characterization, benchmark, and validation of batteries.&nbsp;

At least 15 billion primary batteries are being disposed of yearly worldwide. The world is getting better at recycling, which is excellent news. However, the bad news is that we are still throwing batteries that are not fully utilized.

How much of the IoT battery capacity is actually used?

Explore the future of connected communities in intelligent cities and underserved regions, highlighting the role of technologies like 5G, AI, and blockchain in enhancing connectivity and promoting inclusive development.

Connecting the Future: Bridging the Digital Divide in Intelligent Cities and Underserved Regions

Evolution and Selection of Power over Ethernet (PoE) Standards for Modern Network Infrastructure

PoE vs PoE+ vs PoE++ Switch: Powering the Future of Network Connectivity

Explore how IoT revolutionizes remote infrastructure management, enhancing efficiency and resilience with solutions like Particle's M-Series for future-ready connectivity.



Bridges to the Future: Revolutionizing Remote Infrastructure Management with IoT

In a world where connectivity is king, the choice of SIM form factor plays a crucial role in the success of any deployment, from consumer electronics to IoT applications. As a versatile platform, Monogoto supports an array of SIM types, each tailored to meet specific operational needs and strategic goals. Whether you’re prioritizing security, seeking cost-efficiency, or navigating device constraints, we provide a solution to match. This comprehensive comparison of Physical SIM, MFF2 SIM, iSIM, and SoftSIM technologies aims to illuminate their unique advantages, guiding you toward the ideal selection for your project.&nbsp;<h2>A Comparative Look at SIM Form Factors</h2>Delving into the specifics of Physical SIM, MFF2 SIM, iSIM, and SoftSIM, we evaluate critical aspects such as security, OTA updates, SIM storage capabilities, and price. This comparison offers a foundation for understanding which SIM form factor aligns best with your project’s requirements.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1719853142970-Network-Settings-Storage-e.g.-FPLMNPLMN-1536x1086.png" style="width: 100%px;" class="fr-fic fr-dib"><h2>A Note from Monogoto</h2>At Monogoto, we’re thrilled by the shift from Physical SIMs to innovative software-based solutions like SoftSIM. This transition not only reflects our drive for cutting-edge technology but also our commitment to providing flexible and scalable connectivity solutions. As the telecom landscape evolves, our platform continues to support all SIM types, ensuring robust, secure, and adaptable options for every use case.&nbsp;<h2>Conclusion: Tailoring the Choice to Your Needs</h2>Monogoto’s horizontal platform embraces the diversity of SIM technologies, ensuring you have the freedom to choose the form factor that best suits your project’s demands. Whether you’re navigating the complexities of global IoT deployments or launching consumer tech, we are here to support you with state-of-the-art connectivity solutions that meet today’s needs and anticipate tomorrow’s challenges.Special thanks to ChatGPT for assisting in crafting this blog post. The integration of AI-driven insights has been invaluable in presenting a clear and comprehensive perspective on the diverse world of SIM technologies.This addition not only thanks ChatGPT but also underscores the innovative approach Monogoto takes in leveraging advanced technology tools like AI to enhance communication and insight sharing.

In a world where connectivity is king, the choice of SIM form factor plays a crucial role in the success of any deployment from consumer electronics to IoT applications. As a versatile platform Monogoto supports an array of SIM types, tailored to meet specific operational needs and strategic goals. 

The Right Approach for My Use Case. SIM Form Factor.

The micromobility industry is at an exciting crossroads. As cities worldwide strive for smarter, cleaner, and more efficient modes of transportation, the importance of reliable connectivity in the micromobility sector is paramount.&nbsp;Let’s explore the impact of connectivity on micromobility, offering insights into how businesses like&nbsp;<a href="https://getwhizz.com/" data-wpel-link="external" target="_blank" rel="external noopener noreferrer">Whizz</a>, a New York City-based company that offers flexible e-bike rentals tailored for delivery riders, leverage software-defined connectivity to enhance customer satisfaction.<h2>The Right Connectivity Partner is the Backbone of Micromobility</h2>A trustworthy connectivity partner is the backbone of a micromobility provider. It enables real-time data collection and analysis, and, with the right monitoring software, can provide invaluable insights into device performance, user behavior, and operational efficiency.&nbsp;Micromobility device providers continue to be faced with &nbsp;two crucial challenges: maintaining profitability, and ensuring seamless operational integration. Innovators within the industry are pioneering solutions to these obstacles, leveraging technologies such as GPS tracking, AI, and machine learning to enhance user experience and foster brand loyalty, which in turn boosts revenue through repeat customers. Whizz, for example, uses Monogoto’s connectivity solutions to track their bicycles, monitoring operational health—including preventing device theft. &nbsp;<h2>Enhancing Customer Experience and Fostering Brand Loyalty</h2>Software-defined connectivity is revolutionizing how micromobility services operate, providing the agility to adapt to changing environments and user needs. From enhancing service reliability with private networks to automating maintenance through predictive algorithms, this approach is setting new standards for operational excellence and cost efficiency in the micromobility sector.&nbsp;At the heart of micromobility’s future is the imperative to deliver exceptional customer experiences and build lasting brand loyalty. Reducing failure rates and ensuring successful user engagements are critical to achieving this goal. Software-defined connectivity, like that offered by Monogoto, enables service providers like Whizz to develop reliable and user-friendly solutions that align with the high expectations of modern consumers. With Monogoto as their connectivity partner, Whizz can manage and scale their e-bike connectivity effortlessly, ensuring optimal service availability and performance. This technology also allows for better network management, security features, and seamless integration across different communication platforms, enhancing both operational efficiency and customer satisfaction.Watch this webinar featuring Tanya Kashina, Head of Supply Chain at Whizz, to discover more about how software-defined connectivity solves salient challenges in the micromobility industry.&nbsp;WATCH THE WEBINAR&nbsp;<a href="https://www.youtube.com/watch?v=leR1ztubJuE&feature=youtu.be" data-wpel-link="external" target="_blank" rel="external noopener noreferrer">HERE</a>As the micromobility industry evolves, embracing connectivity advancements will be key to unlocking new opportunities for growth and customer engagement. Monogoto stands at the forefront of this journey, offering cutting-edge connectivity solutions that empower micromobility providers to redefine urban transportation.&nbsp;<a href="https://lp.monogoto.io/book-a-demo" data-wpel-link="external" target="_blank" rel="external noopener noreferrer">Book a demo</a> with Monogoto today and take the first step towards a revolutionary experience.

The micromobility industry is at an exciting crossroads. As cities worldwide strive for smarter, cleaner, and more efficient modes of transportation, the importance of reliable connectivity in the micromobility sector is paramount. 

Revolutionizing Transportation: How Connectivity Shapes the Future of Micromobility

The advent of cellular IoT connectivity revolutionized the way businesses were able to track assets and fleets around the world, and the exponential growth of connected devices continues at a rapid pace. The GSMA reports that between 2020 and 2022, the number of LTE-M networks increased nearly 30%. This increase demonstrates how fundamental connectivity has become to support the way businesses manage their fleets.&nbsp;But what happens when those fleets move outside the boundaries of cellular services? How can businesses circumvent issues when assets are in remote locations? Here we’ll discuss the benefits of satellite asset tracking, and how using satellite connectivity along with cellular should become standard for the future success of asset management enterprises.<h2>Combining Satellite and Cellular Connectivity for More Effective Asset Tracking</h2>The ability to track fleets on the move and on the ground in areas where cellular connectivity is reliable and readily available has significantly improved in recent years. But as companies expand their global presence, sending assets or fleets across oceans or into remote areas, cellular connectivity is no longer a viable or singular option for asset monitoring. In the shipping industry, for example, cellular connectivity allows companies to check ship location statuses from port to port, but not in between.&nbsp;Satellite tracking bridges the gap when ships are traveling across oceans, allowing for more efficient and effective fleet tracking. And while satellite services were once prohibitively expensive, demand has pushed prices down, and more satellite providers make the cellular/satellite connection financially viable. Now, the use of cellular and satellite networks offers a perfect balance between performance and price.Plus, when devices are on the move in remote locations—where cell towers are scarce or non-existent—satellite connectivity becomes the only reliable method to track assets and fleets.<h2>When The Assets You’re Tracking are People: NEYOS Otrac</h2>There are recognizable use cases for a combined cellular/satellite asset tracking—container shipping, as we’ve mentioned, and other supply chain logistics. But there are other use cases—ones in which the devices that need to be tracked are people.NEYOS, a manufacturer of a portable geolocation beacon, was founded following a life-threatening incident in which its co-founder was unable to reach emergency services while located on a mountain. Based on that experience, they developed the NEYOS Otrac, the first satellite and cellular geolocation beacon that allows the tracking of remote sporting activities, like ultra-marathons. And this tracker has become available at a time when ultra-marathoning is rapidly growing. Ultra marathon participation has vastly increased over the years—a staggering 345% in the last decade.&nbsp;As more people become interested in this activity, tracking participants becomes even more essential to ensure runner safety.NEYOS provides sporting event organizers the Otrac and a subscription connectivity plan that offers 4G cellular and satellite tracking ideal for monitoring in remote locations. Those tracking beacons are handed out to runners as part of their marathon safety protocol. If a runner participating in an organization’s event deviates from the planned course or experiences an emergency, the event organizers are immediately alerted through the Otrac security beacon and help can be dispatched promptly.<h2>Other Industries Benefiting from Using Cellular/Satellite Connectivity Combination&nbsp;</h2>The NEYOS beacon use case applies not only to ultra-marathoning, but also to many other remote sporting events, like sailing competitions, remote hiking and cycling, and rally raids. And it also benefits many more emerging industries thanks to its flexible use of both cellular and satellite connectivity. Another instance in which people need to be monitored is when companies dispatch lone workers to remote areas. Similar to sporting event participant tracking, using a monitoring device in conjunction with satellite connectivity gives businesses peace of mind that their employees can make emergency contact using their tracking device. Other sporting activities, like sailing competitions, or agricultural goods tracking—where food is monitored from farm, to port, to ship, then to store—also require both remote satellite and cellular services.<h2>Cellular/Satellite Tracking for Asset Management</h2>Businesses have benefited from asset tracking and management thanks to cellular IoT connectivity, but they need to look to the future in which assets are moving across areas without cell towers. Devices like the NEYOS Otrac, combined with cellular and satellite services provided by Monogoto and Skylo, ensure a smooth transition into the future of asset management.<h2>Scale and Innovate with Monogoto</h2>With Monogoto’s cloud best practices, developers and innovators can start small, with access to all APIs immediately, and scale with a truly global cloud offering. Secure, seamless connectivity across cellular, satellite, and private LTE/5G networks forms the foundation of the future of asset tracking. As the industry evolves, embracing connectivity advancements is key to unlocking new opportunities for growth. Monogoto stands at the forefront of this journey, offering cutting-edge connectivity solutions and developer tools that empower enterprises to innovate like never before.&nbsp;<a href="https://lp.monogoto.io/book-a-demo" data-wpel-link="external" target="_blank" rel="external noopener noreferrer">Book a demo</a> with Monogoto today and take the first step towards a revolutionary experience.

The advent of cellular IoT connectivity revolutionized the way businesses were able to track assets and fleets around the world, and the exponential growth of connected devices continues at a rapid pace. The GSMA reports that between 2020 and 2022, the number of LTE-M networks increased nearly 30%. 

How Combining Cellular and Satellite Connectivity Improves Asset Tracking

Standard data communication protocols like BACnet & Modbus have revolutionized and simplified industrial automation, helping devices to efficiently exchange data. Choosing the best one requires - understanding their key differences, challenges, and advancements, as we discuss in this article.

BACnet vs Modbus: A Comprehensive Guide for Engineers

AI and ML have formed the driving force behind the fourth industrial revolution. Industry 4.0 features the development of “smart” machines and devices that can intercommunicate in a network, now evolved into the Internet of Things (IoT) and the Industrial Internet of Things (IIoT). AI is the foundation on which all these structures are based.&nbsp;AI technologies have been incorporated into devices that can sense their surroundings and communicate this information to a central control system. This system then uses ML and&nbsp;<a href="https://www.rowse.co.uk/blog/post/what-is-big-data" title="What Is Big Data?" target="_blank">big data</a> analysis to resolve complex problems and learn how to avoid repeating such problems.<h2 dir="ltr">Impact of AI on Industry</h2>Smart manufacturing is an integral part of Industry 4.0. It can integrate advanced intelligent systems into production processes. This saves time, improves quality and eliminates unnecessary waste. By using AI and ML to streamline and optimise these processes, we can also use them to react more efficiently and rapidly to changes. These changes may arise in product demand, customer requirements or external events throughout the value chain.&nbsp;In manufacturing, AI offers considerable benefits in areas like predictive maintenance, inventory management, production planning, process control, machinery inspection and logistics. Industry strategy is also changing, as manufacturers can focus more accurately on sustainability, with an increasing shift towards customer-centric and often highly customised production. Technologies such as 3D printing have enabled some companies to turn towards on-demand production, adapting their strategies to&nbsp;<a href="https://www.rowse.co.uk/blog/post/what-is-lean-manufacturing" title="What Is Lean Manufacturing?" target="_blank">lean manufacturing</a> rather than keeping an extensive inventory.&nbsp;The new technological advancements, especially in the IoT and IIoT, have leveraged the flexibility and agility of AI to solve many supply, production and logistical challenges. AI is now recognised as the essential technology for developing Industry 4.0. Only AI possesses the capabilities to manage the way we structure today’s industrial processes and business models.<h2 dir="ltr">Development and Key Features of AI/ML in Industry</h2>The role of AI is to understand what constitutes intelligence and to learn from human intelligence how to create computers that perform similarly to human beings. It’s a large and continuously expanding field of technology that underpins many of the most advanced approaches used in industry today. These include simulation,&nbsp;<a href="https://www.ibm.com/topics/speech-recognition" target="_blank" rel="nofollow">speech recognition</a> and virtual reality, which have many different industrial applications.<h3 dir="ltr">SIMULATION</h3>AI uses computer simulation systems to create a production model that can incorporate product improvement, quality control and safety features. These simulations can leverage extensive data analysis to improve production accuracy and efficiency. They can identify problems and take precautionary action to prevent or mitigate an emergency, reducing the risk of unplanned downtime. This helps to ensure a more efficient production system, reducing running costs and the risk of capital loss.&nbsp;<h3 dir="ltr">VIRTUAL REALITY</h3>Technologies such as&nbsp;<a href="https://www.rowse.co.uk/blog/post/an-introduction-to-digital-twins" title="An Introduction To Digital Twins" target="_blank">digital twins</a> are increasingly used in large-scale industrial manufacturing like automotive and shipyards, where they eliminate the necessity of building physical models. A digital twin replicates a physical asset in virtual reality, where a constant flow of data allows design engineers to update the digital model in real time. They can be used to control, monitor and predict the behaviour of any product, throughout its entire lifecycle, thus achieving greater effectiveness and productivity.&nbsp;Digital twinning allows various stakeholders – such as designers, end users and manufacturers – to participate in the product creation process. Connecting from anywhere on the globe, these participants can communicate with each other, sharing information on a single common project and enabling much greater precision in product and project management.&nbsp;<h3 dir="ltr">SPEECH RECOGNITION&nbsp;</h3>Advances in digital technologies and AI have made speech recognition applications commonplace – from asking your phone to search for something to telling your car where to go. They also allow your car to tell you where to go, as well as help identify and solve problems. These features will increase in importance when self-driving vehicles become more widespread.&nbsp;In industry, AI and ML are making significant advances in areas related to customer service. AI chatbots can schedule functions like service calls or test runs, as well as fielding queries and giving customers advice. In the energy sector, for instance, speech recognition applications allow customers to inquire about billing or report outages. Speech AI can support field technicians, using voice commands to take notes or access work orders and streamline meter readings. In some applications, customers’ conversations are analysed by speech AI to assess their intent, sentiment and propensity. This allows customer service agents to formulate appropriate and effective responses.<h2 dir="ltr">How AI/ML Benefits Industry 4.0</h2>The role of AI/ML technologies in Industry 4.0 is to aid the growth of companies in the manufacturing sector. They do this in several major ways, including the introduction of robotics and human-robot interfaces. This enables greater customisation and adding value throughout the production cycle. AI/ML applications also benefit process and plant automation, warehouse management and logistics and inspection.&nbsp;Their predictive facilities improve equipment maintenance schedules and repair requirements, together with output and quality. AI/ML technologies increase supply chain value – locating and making better use of resources. This helps companies become more sustainable, reducing waste and better fulfilling customer demands.AI applications also offer strategic benefits in business, such as faster decision-making, reduced levels of human error, rapid response, and assistance in troubleshooting problems. They’re able to function 24/7 and can work remotely, even in extreme conditions. They help workforces to perform repetitive jobs, improve the scope for creating and marketing new inventions and enhance cybersecurity. With connected systems and devices, companies can maintain secure, continuous and seamless communications with all involved parties.

Artificial Intelligence (AI) is a branch of computer science that has developed a processing system capable of behaving like human intelligence. It can perform reasoning, calculation and analytical tasks and learn from these to improve its performance. 

The Role of AI ML in Industry 4.0

<table style="width: 100%;"><tbody><tr><td style="width: 100%;"><h2>Webinar: Unlocking Continuous Connectivity with Particle.io's M-Series Products</h2>Don't miss this opportunity to join our informative webinar on Particle's M-Series Products. These products, designed to offer ubiquitous and continuous connectivity, are a game-changer for IoT developers and companies seeking to boost their device network reliability and efficiency.This webinar will explore the M-series, Particle's multi-radio line of products. It will go over the case for multi-radio, best practices, and the best use case for them. Developers will also learn how to get started with the m-series and when to choose it over particle's cellular or wifi devices.The webinar will be hosted by Colleen Lavin. Colleen is the Developer Success Lead at Particle and a total hardware geek. She first encountered Particle in 2016 when she taught a Photon class at computer camp and has been a fan ever since, joining the Particle team in 2021. Prior to Particle, Colleen worked in consulting and had clients such as NASA and the DOE.&nbsp;Date: July 25, 2024 Time: 6pm CET, 12 pm EST Duration: 1 hour Platform: Zoom Cost: Free Why join?In the hour-long webinar, Colleen Lavin will showcase the capabilities and use cases of Particle's M-Series and take questions from the audience.&nbsp;<ul data-stringify-type="unordered-list" data-indent="0" data-border="0" id="isPasted"><li data-stringify-indent="0" data-stringify-border="0">Multi-Radio Networking: How combining multiple wireless technologies can achieve near 100% connectivity.</li><li data-stringify-indent="0" data-stringify-border="0">Real-World Applications: Use cases in remote and challenging environments.</li><li data-stringify-indent="0" data-stringify-border="0">Technical Deep Dive: Features and benefits of the M-Series devices, including the M-SoM, Muon, and Monitor M.</li></ul>Don't miss this opportunity to learn how the M-Series can enhance your IoT projects with reliable, flexible, and powerful connectivity solutions. Register now to stay ahead in the IoT innovation curve! <a href="https://us02web.zoom.us/webinar/register/6317132549686/WN_d8ZxEtuFQg-RKP2AenDf5A#/registration" target="_blank" rel="noopener noreferrer" class="button-main-action">Register Here</a></td></tr></tbody></table>As our planet grapples with the escalating challenges of climate change and natural disasters, the significance of environmental monitoring and disaster response has surged. These critical fields are our first line of defence, enabling us to understand, predict, and mitigate the impacts of environmental threats with greater precision. The advent of cutting-edge technologies, notably the Internet of Things (IoT), is revolutionizing these domains. IoT's real-time data collection, analysis, and communication capabilities transform how we approach environmental stewardship and disaster preparedness. 1,2IoT offers unparalleled insights into our environment through advanced sensors and networked devices, providing early warnings for disaster response and fostering a more resilient and sustainable future. Integrating IoT technology into environmental monitoring and disaster management enhances our ability to protect vulnerable ecosystems. It empowers communities worldwide to respond more effectively to the inevitable challenges posed by our changing climate.<h2 dir="ltr">The Climate Challenge: Understanding Environmental Monitoring</h2>Environmental monitoring is a critical process aimed at observing, characterizing, and quantifying the impact of activities on the environment. It encompasses a variety of tools and techniques designed to gauge environmental quality and establish parameters that accurately reflect the influence of human and natural activities on environmental conditions.&nbsp;The importance of environmental monitoring has grown with increasing concerns about climate change, pollution, and biodiversity loss. Through rigorous data collection and analysis, environmental monitoring provides essential insights for risk assessments and the development of impact assessment reports, facilitating informed decision-making and policy formation aimed at environmental protection and sustainable management.3Traditional environmental monitoring methods have included a range of manual and automated techniques focused on assessing soil, atmospheric, and water conditions. Instruments such as hygrometers, anemometers, rain gauges, and pyranometers have been deployed in various settings, from weather stations to dedicated buoys at sea, to gather essential environmental data.4While traditional Geographic Information Systems (GIS) platforms have been instrumental in compiling and analyzing spatial data, they often need to improve their capacity for temporal analysis and handling the vast quantities of space-time data generated by global climate models. The need for real-time, accurate data is more pressing than ever, as the dynamic nature of environmental systems requires sophisticated tools capable of capturing and processing complex datasets rapidly and efficiently.5Advancements in technology have ushered in Smart Environmental Monitoring (SEM) systems, which leverage modern sensors, Machine Learning (ML) techniques, and the Internet of Things (IoT) to enhance the scope and precision of environmental monitoring. In particular, IoT devices and wireless sensor networks have transformed environmental monitoring into a more integrated, AI-controlled process. These technologies enable the development of wireless, remote monitoring systems that minimize human intervention, expand the frequency and range of sampling, and provide lower latency in detecting and responding to environmental changes and potential disasters.<h2 dir="ltr">The Tech Tide: IoT's Role in Environmental Vigilance</h2>The Internet of Things (IoT) is revolutionizing environmental monitoring, transforming it into a more efficient, accurate, and comprehensive process. IoT technology employs interconnected sensors and devices that collect and transmit data about various environmental parameters to central databases or cloud platforms for real-time analysis. This advanced approach is critical for tracking and managing the impacts of climate change, pollution, and biodiversity across different environments.2,6IoT applications in environmental monitoring span air quality, water levels, soil conditions, and wildlife, showcasing its versatility and depth. For instance, air quality monitoring systems utilize IoT devices to measure particulate matter, nitrogen dioxide, and sulfur dioxide, especially in urban areas where air pollution poses significant health risks. Similarly, IoT technologies play a crucial role in water quality monitoring by evaluating parameters such as temperature, pH, oxygen levels, and turbidity, which are essential for protecting aquatic ecosystems and ensuring the safety of drinking water.2,7In agricultural settings, soil moisture monitoring through IoT devices aids in efficient crop management and irrigation practices, allowing for optimized water usage and improved crop yields. Additionally, IoT extends its capabilities to wildlife monitoring, enabling the observation of animal behaviours and habitat conditions, which is crucial for conservation efforts and protecting endangered species. Another vital application is energy consumption monitoring, where IoT systems track energy usage in buildings and industries to promote energy efficiency and sustainability.6,7Despite its vast potential, IoT in environmental monitoring faces challenges such as data management, ensuring security and privacy, and maintaining power supply in remote areas. However, advancements in low-power, long-life IoT devices and secure data transmission technologies continue to mitigate these issues, making IoT an indispensable tool in the fight against environmental degradation and climate change.6<h2 dir="ltr" id="isPasted">Navigating the Storm: IoT in Disaster Response</h2>IoT technology significantly enhances disaster management and response strategies, offering a proactive and efficient approach to dealing with natural and man-made catastrophes. By integrating IoT technologies, emergency management can transition from traditional, reactive methods to more proactive and predictive strategies, improving outcomes and saving lives, resources, and finances.The role of IoT in disaster management encompasses several crucial aspects. First, IoT can identify life-threatening hazards early, alert authorities and the public, and assist in rapidly deploying rescue and relief operations.&nbsp;For instance, in the face of increasing natural disasters such as bushfires, monsoons, earthquakes, and hurricanes, IoT technologies have shown tremendous potential in early detection, providing critical data for emergency planning and response. This early detection is crucial for mitigating the impacts of such events, which have seen a significant rise in frequency and severity over the past decades.8IoT applications in disaster preparedness and response include deploying sensors and devices that collect real-time data on environmental conditions such as water levels, atmospheric conditions, and ground movements. This real-time monitoring allows for early warnings of potential disasters like floods, wildfires, and storms. Furthermore, IoT technology aids in coordinating emergency services by facilitating communication between different agencies and ensuring that help is dispatched where it is most needed. This ensures a faster and more efficient response to emergencies, which is critical in minimizing damage and saving lives.The importance of data analysis and communication in effective disaster response cannot be overstated. The vast amount of data IoT devices collect can be analyzed through advanced analytics to predict disaster patterns, assess risks, and plan responses accordingly. This data-driven approach enhances decision-making processes, ensuring that emergency responses are timely and effective. Additionally, IoT technologies facilitate better communication among emergency responders and between authorities and the public, ensuring that everyone has access to the information they need during a crisis.Innovative uses of IoT for disaster response also include monitoring infrastructure resilience, managing evacuation routes, and supporting search and rescue operations. For example, IoT devices embedded in infrastructure can monitor structural integrity in real-time, enabling authorities to make informed decisions about evacuations or emergency interventions. Drones equipped with IoT sensors can survey disaster-stricken areas, providing critical information for rescue teams and aiding in delivering emergency supplies.The integration of IoT in disaster management represents a paradigm shift towards more resilient and adaptive emergency preparedness and response mechanisms. By leveraging IoT technologies, communities can enhance their ability to anticipate, respond to, and recover from disasters, ultimately saving lives and reducing the economic impact of such events.9,10<h2 dir="ltr" id="isPasted">Spotlight on Particle's M-Series: Connecting the Dots in Environmental and Disaster Solutions</h2>Alongside the popular Photon 2 WiFi and B-Series cellular devices, Particle recently introduced the M-Series, which represents a significant leap in IoT connectivity and offers a robust solution tailored for environmental monitoring and disaster response applications. This innovative series integrates multi-radio connectivity on a single device, including Wi-Fi, cellular, LoRaWAN, and satellite communications. Such diversity ensures global connectivity, enhancing the deployment and efficiency of remote sensors and devices in various challenging environments, from urban infrastructures to remote agricultural fields.11,12The global connectivity provided by the M-Series is pivotal for environmental and disaster management applications. Devices can switch between communication protocols to maintain connectivity in diverse conditions, ensuring critical data from remote sensors reaches the cloud efficiently. This capability is crucial for timely decision-making and action in scenarios like stormwater management in major cities, monitoring agricultural equipment, and optimizing energy production with minimal environmental impact.12,13Particle's ecosystem facilitates seamless data collection, analysis, and sharing, including professional-grade IDE, CLI, SDKs, and a comprehensive Device Cloud API. This integrated platform supports rapid prototyping and deployment, making it easier for businesses and developers to bring their IoT solutions to market. Success stories from various sectors, including smart agriculture and energy management, underscore the ecosystem's capability to drive innovation and efficiency in environmental and disaster management solutions.13<h2 dir="ltr">Overcoming Barriers: Challenges in Tech-Driven Environmental Efforts</h2>The deployment of IoT solutions in environmental monitoring and disaster response faces several challenges, including technological accessibility, cost, maintenance, and the need for interdisciplinary collaboration. Particle's M-Series and its ecosystem offer solutions to these challenges, emphasizing ease of deployment, scalability, and cost-effectiveness.The M-Series' multi-radio capability addresses ensuring reliable connectivity in diverse environments, a critical factor in monitoring and managing environmental and disaster-related events. This flexibility reduces the need for multiple devices with different connectivity options, streamlining deployments and reducing costs. 12,14Furthermore, Particle's comprehensive ecosystem supports developers and businesses in overcoming the technological complexities associated with IoT deployments. With resources like professional-grade development tools, guides, and case studies, Particle simplifies the development process, enabling users to focus on creating solutions that address real-world environmental challenges. The platform's scalability and ease of use also make it accessible to a broader range of users, from startups to large corporations, fostering interdisciplinary collaboration and innovation in environmental solutions.13,14<h2 dir="ltr">Conclusion</h2>The integration of IoT marks a shift in environmental monitoring and disaster response, offering a promising horizon for safeguarding our planet. The M-Series’ unique multi-radio connectivity ensures seamless and reliable data transmission across diverse environments, enabling proactive and informed decision-making in critical situations. Embracing such technological advancements is paramount for enhancing our resilience against the escalating threats of climate change and natural disasters.&nbsp;By harnessing the capabilities of the M-Series and similar IoT innovations, we can significantly improve our environmental sustainability and strengthen community responses to emergencies, moving towards a more secure future.<h2 dir="ltr">References</h2><ol><li dir="ltr"><a href="https://www.ignitec.com/insights/environmental-monitoring-and-natural-disaster-management/" target="_blank">https://www.ignitec.com/insights/environmental-monitoring-and-natural-disaster-management/</a></li><li dir="ltr"><a href="https://www.digi.com/blog/post/iot-based-environmental-monitoring" target="_blank">https://www.digi.com/blog/post/iot-based-environmental-monitoring</a></li><li dir="ltr"><a href="https://www.heavy.ai/technical-glossary/environmental-monitoring" target="_blank">https://www.heavy.ai/technical-glossary/environmental-monitoring</a></li><li dir="ltr"><a href="https://www.ctc-n.org/technologies/monitoring-technologies" target="_blank">https://www.ctc-n.org/technologies/monitoring-technologies</a></li><li dir="ltr"><a href="https://earth-perspectives.springeropen.com/articles/10.1186/2194-6434-1-16" target="_blank">https://earth-perspectives.springeropen.com/articles/10.1186/2194-6434-1-16</a></li><li dir="ltr"><a href="https://infisim.com/blog/iot-in-environmental-monitoring" target="_blank">https://infisim.com/blog/iot-in-environmental-monitoring</a></li><li dir="ltr"><a href="https://www.link-labs.com/blog/iot-environmental-monitoring" target="_blank">https://www.link-labs.com/blog/iot-environmental-monitoring</a></li><li dir="ltr"><a href="https://tele2iot.com/article/the-role-of-iot-in-disaster-management-emergency-planning/" target="_blank">https://tele2iot.com/article/the-role-of-iot-in-disaster-management-emergency-planning/</a></li><li dir="ltr"><a href="https://statetechmagazine.com/article/2021/10/bringing-iot-and-analytics-forefront-disaster-preparedness-and-response" target="_blank">https://statetechmagazine.com/article/2021/10/bringing-iot-and-analytics-forefront-disaster-preparedness-and-response</a></li><li dir="ltr"><a href="https://azure.microsoft.com/en-us/blog/using-ai-and-iot-for-disaster-management/" target="_blank">https://azure.microsoft.com/en-us/blog/using-ai-and-iot-for-disaster-management/</a></li><li dir="ltr"><a href="https://www.particle.io/blog/connect-anywhere-introducing-the-m-series/" target="_blank">https://www.particle.io/blog/connect-anywhere-introducing-the-m-series/</a></li><li dir="ltr"><a href="https://makezine.com/article/technology/iot/particles-new-m-series-connects-everything-everywhere-all-at-once/" target="_blank">https://makezine.com/article/technology/iot/particles-new-m-series-connects-everything-everywhere-all-at-once/</a></li><li dir="ltr"><a href="https://www.particle.io/blog/connect-anywhere-introducing-the-m-series/" target="_blank">https://www.particle.io/blog/connect-anywhere-introducing-the-m-series/</a></li><li dir="ltr"><a href="https://linuxgizmos.com/particle-unveils-m-series-multi-radio-satellite-lorawan-connectivity-for-advanced-iot-solutions/" target="_blank">https://linuxgizmos.com/particle-unveils-m-series-multi-radio-satellite-lorawan-connectivity-for-advanced-iot-solutions/</a></li></ol>

The increasing importance of environmental monitoring and disaster response in the face of climate change and natural disasters has been significantly enhanced by the revolutionary impact of cutting-edge technologies like the Internet of Things (IoT).

Tech for the Planet: IoT Innovations in Environmental Monitoring and Disaster Management

<h2 dir="ltr" id="isPasted">Introduction - Tracing Past and Present Trends</h2>The way we interact with machines has undergone a remarkable transformation. Mechanical buttons and levers once defined our control over devices. Then, touchscreens revolutionised the user experience, providing a direct and intuitive way of issuing commands. Today, we stand on the cusp of another major shift—the rise of touchless human-machine interfaces (HMIs). A human-machine interface is the platform through which humans interact with machines, systems, or devices.[1] HMIs translate complex data into a user-friendly format.Why embrace this change? Touchless HMIs offer compelling advantages. They empower individuals with disabilities to interact with technology independently, opening doors to communication and control that were once inaccessible. Furthermore, they promote hygiene in public environments like hospitals and kiosks, minimising the spread of germs through shared touch surfaces.[2] Perhaps most importantly, these interfaces often provide a more natural and intuitive user experience – we instinctively communicate through speech and gestures, and these interfaces reflect those inherent patterns. In this article, we will examine how touchless HMIs enhance the user experience, explore their applications in various sectors, and discuss their potential for the future of communication between humans and machines.<h2 dir="ltr">Navigating the Shift from Traditional Interfaces</h2>Human-machine interfaces began with the simple yet enduring pushbutton and dial. For decades, these physical controls were the primary means of directing machines. While reliable, they were often cumbersome and inefficient, especially when dealing with complex systems.[1] A factory floor, for instance, might require a vast array of buttons and dials to manage its machinery, adding complexity to the operator's task.&nbsp;The advent of Programmable Logic Controllers (PLCs) brought about a significant shift. PLCs are essentially industrial computers that automate tasks based on programmed logic.[3] While revolutionising automation, direct interaction with PLCs typically involved specialised interfaces, often text-based or requiring specific code knowledge. This created a barrier between operators and the machinery they supervised, slowing down configuration and troubleshooting. Compared to the intuitive operation of pushbuttons and dials, PLCs demanded a steeper learning curve for operators.Touch panels provided a significant leap forward in HMI design. These intuitive interfaces replaced many physical controls with digital ones, offering greater flexibility and a more streamlined user experience. Operators could easily switch between control screens, monitor multiple processes at once, and access detailed diagnostics with the touch of a finger. However, touchscreens still carry limitations. They rely on direct physical contact, a hygiene concern in sensitive environments.[4] They also demand a user's proximity to the device.As touch panels matured, voice control emerged as the next frontier in HMI development. Voice-enabled interfaces allow users to issue commands and control devices hands-free. This Touchless HMI technology is transformative in various industries. A surgeon, for instance, could access patient records or adjust medical equipment during a procedure without breaking sterility. Factory workers might remotely control machinery using voice commands, enhancing productivity and safety. Moreover, voice control opens new avenues for remote monitoring and managing industrial processes. Engineers can troubleshoot issues, receive alerts, and make adjustments from anywhere, leading to faster response times and less reliance on on-site personnel.&nbsp;<h2 dir="ltr">How Touchless HMI Works and Emerging Trends</h2>Touchless HMIs seem like magic, but they rely on sophisticated technologies to bridge the gap between humans and machines. Voice control systems use natural language processing (NLP) to understand and respond to our spoken words.[5] Specialised devices track and interpret hand gestures, translating motions into commands. Meanwhile, eye-tracking systems monitor our gaze, allowing us to select items, navigate menus, or even scroll through documents simply by shifting our focus. These are just the beginnings of touchless control, and the potential for new and innovative interaction methods is as vast as our imaginations.<h3 dir="ltr">Smart Homes: Control lighting, temperature, appliances with voice or gestures</h3>These human-machine interfaces transform the way we interact with our homes. We speak a&nbsp;<iframe id="6630fcb690a5a9207458ee75" width="250" class="specs-iframe" height="440" src="https://wevolver.com/iframe/specs/microchip-technology-rnwf02-early-access-development-kit?iframe=true" frameborder="0" scrolling="no" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe> simple command to adjust the lights, change the temperature, or play our favourite music. We wave our hand to pause the smart TV or draw a gesture in the air to close our blinds. Wall-mounted interfaces, often found in high-end systems, provide comprehensive home control with visual feedback and easily complement voice and gesture commands.&nbsp;Smart home technology goes beyond individual commands. Location tracking can trigger actions automatically, like turning lights on when you arrive home or locking doors when you leave. Create personalised, pre-programmed sequences - like a "Goodnight" scene that automatically dims lights, lowers the thermostat, and arms the security system, all activated by a simple voice request or a quick gesture. Such human-machine interfaces bring convenience, flexibility, and even a touch of magic to our living spaces.&nbsp;<h3 dir="ltr">Cars: HMIs that minimise distractions while driving (voice, gesture-based)</h3>These interfaces promise to make our interactions with vehicles safer and more intuitive. Head-up displays (HUDs) exemplify this by directly projecting critical driving information (speed, navigation cues) onto the windshield.[6] This allows drivers to focus on the road ahead, minimising distractions inherent in glancing down at a traditional dashboard. Additionally, voice control and gesture recognition systems enable drivers to adjust climate settings and music or answer calls without needing to take their hands off the wheel. <img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzE1NzcwMjc4NzMyLTE3MTU3NzAyNzg3MzIucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" width="624" height="416" class="fr-fic fr-dii">A heads-up navigation display of a car showing directions, speed, and time. Image credit:&nbsp;<a href="http://www.freepik.com/" target="_blank" id="isPasted">Freepik</a> -&nbsp;<a href="https://www.freepik.com/author/rawpixel-com" target="_blank">rawpixel.com</a>Augmented reality (AR) takes the concept of HUDs even further. In AR-powered HUDs, a transparent surface called a combiner acts as a display. Information is overlaid directly onto the driver's field of view, merging with the real world. Imagine navigational arrows visually guiding you through turns or hazard warnings highlighting obstacles on the road. AR systems have vast potential for improving drivers' situational awareness and decision-making. The field of view (FOV) of an AR display is crucial, as it defines the size of the area where information can be projected.<h3 dir="ltr">Healthcare: Assistive HMIs for individuals with limited mobility</h3>Touchless HMIs offer incredible potential for those with disabilities that affect their motor function. Voice and gesture-based interfaces can empower individuals with limited mobility to operate once inaccessible devices. For instance, a patient with paralysis might control an intelligent bed to adjust its position, call for assistance through a voice-powered home system, or even operate a computer using eye-tracking technology.HMIs on some kidney dialysis machines display critical patient information, such as blood pressure and flow rates, while allowing technicians to adjust treatment parameters accurately. MRI scanners rely on sophisticated HMIs that guide the operator through the scanning process, enabling image selection and controlling imaging parameters.[2] Often cardiac defibrillators feature clear, intuitive HMIs that guide doctors through life-saving procedures, provide step-by-step instructions, and minimise the potential for errors in highly stressful emergenciesBeyond day-to-day activities, touchless HMIs open doors to communication, entertainment, and self-expression. Individuals with speech impairments could use text-to-speech systems controlled by gestures or eye movements, allowing them to interact with others. In both therapeutic and home settings, interfaces that respond to even minimal gestures can facilitate access to music, art creation tools, and games, promoting independence and improving quality of life.&nbsp;<h2 dir="ltr">Applications of HMIs in Industrial Automation</h2>HMIs integrate with key control systems such as Supervisory Control and Data Acquisition (SCADA), Enterprise Resource Planning (ERP), and Manufacturing Execution Systems (MES). This integration provides a centralised view and control point for complex manufacturing processes. Operators enjoy a visual representation of machinery status, production data, and resource management, empowering them to make informed decisions in real-time.&nbsp;<iframe id="65cdfb042e974dd551480b6b" width="250" class="specs-iframe" height="440" src="https://wevolver.com/iframe/specs/silicon-labs-xg28-pk6024a-868-915mhz-ble-14dbm-pro-kit?iframe=true" frameborder="0" scrolling="no" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe>By making process visualisation and control easy, HMIs contribute significantly to enhanced efficiency on the factory floor. Operators can quickly identify bottlenecks, fine-tune production parameters, and reduce downtime through prompt troubleshooting. The clear presentation of key performance indicators (KPIs) provided by modern interfaces drives data-backed optimisation at every stage of the manufacturing process.&nbsp;HMIs also enable remote monitoring and management. Engineers and technicians can access real-time data on production lines from anywhere, receive alerts on critical events, and take preventive measures to mitigate potential issues. This remote capability reduces the need for on-site personnel, especially in hazardous or remote locations, boosting productivity and optimising resource allocation. With secure, cloud-based interfaces, manufacturers can monitor and control operations across multiple facilities, facilitating centralised decision-making and accelerating response times.<h2 dir="ltr">The Benefits and Challenges</h2>Touchless HMIs offer significant advantages. They transcend limitations for individuals with disabilities. Voice-controlled interfaces bridge communication gaps, while gesture or eye-tracking systems can facilitate control over personal devices and augmentative technologies. Beyond accessibility, they promote improved hygiene — a vital consideration in high-traffic public areas. With such technology, self-service kiosks at airports or restaurants can be operated without direct touch, minimising the spread of germs from many users.However, challenges exist. Accuracy remains a concern, especially for voice control in noisy environments or for users with non-standard speech patterns. These HMIs collect vast amounts of data — voices, gestures, and eye movements — raising serious privacy considerations. Ensuring robust data protection and transparency on how information is used will be crucial for widespread adoption. Furthermore, for these interfaces to be truly effective, they must be compatible across various devices and platforms, as a lack of standardisation can be a barrier to integration.<h2 dir="ltr">Designing Interfaces for the Future</h2>The future of HMI design goes beyond purely functional interfaces. Medical devices, in particular, demand HMIs that are intuitive, reliable, visually appealing, and even calming. &nbsp;Smooth surfaces and clean lines can promote a sense of hygiene and sterility. At the same time, strategic use of colour and illumination in buttons and switches can quickly convey status or guide user action. Even in critical situations, well-designed HMIs should strive to reduce stress and facilitate quick, confident interactions.While touchless technologies are exciting, tactile feedback remains indispensable in high-stakes environments like healthcare. The satisfying click of an illuminated pushbutton provides instant confirmation of an action. Emergency stop buttons must be instantly recognisable and easily actuated, providing fail-safe peace of mind during urgent situations.Future HMIs must balance innovation and reliability, integrating cutting-edge technologies while preserving the essential elements that promote safety and an exceptional user experience. While still nascent, brain-computer interfaces (BCIs) are also on the horizon. Users will control devices with subtle thoughts, blurring the lines between humans and machines in unprecedented ways.[7]<h3 dir="ltr">References</h3><ol><li dir="ltr">Papcun P, Kajáti E, Koziorek J. Human-machine interface in concept of industry 4.0. 2018 World Symposium on Digital Intelligence for Systems and Machines (DISA) 2018 Aug 23 (pp. 289-296). IEEE.</li><li dir="ltr">Singh HP, Kumar P. Developments in the human-machine interface technologies and their applications: a review. Journal of medical engineering &amp; technology. 2021 Oct 3;45(7):552-73.</li><li dir="ltr">Alphonsus ER, Abdullah MO. A review of the applications of programmable logic controllers (PLCs). Renewable and Sustainable Energy Reviews. 2016 Jul 1;60:1185-205.</li><li dir="ltr">Bhardwaj N, Khatri M, Bhardwaj SK, Sonne C, Deep A, Kim KH. A review on mobile phones as bacterial reservoirs in healthcare environments and potential device decontamination approaches. Environmental research. 2020 Jul 1;186:109569.</li><li dir="ltr">Rani PJ, Bakthakumar J, Kumaar BP, Kumaar UP, Kumar S. Voice controlled home automation system using natural language processing (NLP) and internet of things (IoT). In2017 Third International Conference on Science Technology Engineering &amp; Management (ICONSTEM) 2017 Mar 23 (pp. 368-373). IEEE.</li><li dir="ltr">Ward NJ, Parkes A. Head-up displays and their automotive application: An overview of human factors issues affecting safety. Accident Analysis &amp; Prevention. 1994 Dec 1;26(6):703-17.</li><li dir="ltr">Zander TO, Gaertner M, Kothe C, Vilimek R. Combining eye gaze input with a brain-computer interface for touchless human-computer interaction. Intl. Journal of Human-Computer Interaction. 2010 Dec 30;27(1):38-51.</li></ol>

Discover the transformative shift in human-machine interaction as touchless technologies redefine how we interact with machines.

Human machine interfaces enhance user experience through touchless technology

<h2 dir="ltr" id="isPasted">Introduction</h2>Radar technology, initially developed in the early 20th century for military navigation and detection, has experienced a remarkable evolution over the years [1]. What began as a means to locate aircraft and ships has transformed into a versatile tool that permeates various aspects of modern life. Beyond its foundational use in aviation and maritime navigation, radar now finds applications in fields as diverse as automotive safety, healthcare, industrial operations, and even smart home technology. This article explores the cutting-edge uses of radar technology in areas not commonly associated with it.<h1 dir="ltr">Inside Cabin Monitoring</h1>While radar is used in automotive as a means for achieving greater levels of vehicle autonomy, it has also found major uses inside the cabin. Specifically, radar sensors have carved a niche within the automotive industry in enhancing in-cabin monitoring systems.&nbsp;In the context of inside cabin monitoring, radar sensors utilize electromagnetic waves to detect objects and movements inside the vehicle, providing real-time data about the cabin's interior environment. Combined with sophisticated software and mapping algorithms, this technology is adept at identifying the position and movement of passengers, for the purposes of occupant monitoring and safety. For example, inside-cabin monitoring can be used to ensure that airbags deploy appropriately in the event of a collision to minimize injuries. Furthermore, radar-based systems can monitor driver alertness, detecting signs of drowsiness or distraction by observing head position and movement, thereby prompting alerts to reduce the risk of accidents[2].<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzE1NTk4ODkxMDY5LWNhci1pbmNhYmluLmpwZ180NzI5MTU1NDEuanBnIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib">Radar is used for in-cabin monitoring applications in modern vehicles. Image credit: <a href="https://www.infineon.com/cms/en/applications/automotive/chassis-safety-and-adas/in-cabin-sensing/" target="_blank">Infineon</a>.One notable application of in-cabin radar is the child presence detection system. This system alerts drivers if a child is inadvertently left behind in a vehicle, thereby preventing heat-related injuries or fatalities.&nbsp;The benefits of in-cabin radar technology also extend beyond safety. Comfort is significantly enhanced through features like automatic adjustment of climate control systems based on the occupancy and positioning of passengers. This might include optimal temperature settings across different zones within the vehicle, improving the overall driving experience.<h1 dir="ltr">Contactless Health Monitoring</h1>In the health sector, radar technology offers a groundbreaking approach to monitoring vital signs without any physical contact.&nbsp;This approach uses electromagnetic waves to detect the minute movements of the chest as the heart beats and lungs expand and contract, converting these movements into digital signals that can be analyzed to monitor health metrics continuously. Unlike traditional methods that require physical contact with the body, radar-based health monitoring is non-intrusive, offering a significant advantage in various settings, from hospitals to homes.[3]There are many benefits of contactless monitoring in today's health-conscious world. For patients in critical care, it minimizes the risk of infection and discomfort associated with frequent physical check-ups. In home settings, it allows for the continuous observation of elderly or chronically ill patients without intruding on their comfort or privacy.&nbsp;One of the most noteworthy advancements in this area is the development of radar-based sleep monitors. These devices can accurately measure sleep quality, breathing rate, and even detect sleep apnea without the need for uncomfortable wearables. This technology is particularly useful for monitoring sleep patterns and detecting early signs of respiratory or cardiac conditions, enabling timely medical intervention.&nbsp;<h1 dir="ltr">Industrial Applications</h1>In the industrial sector, radar technology has become a critical tool for enhancing both safety and efficiency. Here, radar’s ability to provide accurate, real-time data in challenging environments—where dust, smoke, or extreme temperatures may impair other types of sensors—makes it extremely valuable for a wide range of applications.&nbsp;&nbsp;<iframe id="6621771b970f77c1cbd26454" width="250" class="specs-iframe" height="440" src="https://wevolver.com/iframe/specs/stmicroelectronics-sr5e1e7-stellar-e1-automotive-mcu-evaluation-board?iframe=true" frameborder="0" scrolling="no" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe>One of the key benefits of radar in industrial settings is its contribution to workplace safety. For instance, radar sensors can create invisible safety zones around dangerous machinery. When these zones are breached by an unexpected object or person, the system can automatically shut down the equipment, preventing potential injuries. In manufacturing facilities and construction sites where the interaction between heavy machinery and workers is a constant concern, these safety zones can be a huge step toward worker safety. [4]Furthermore, radar technology is instrumental in improving operational efficiency. In large warehouses or ports, radar-based systems can track the movement of goods and vehicles, optimizing logistics and reducing the time it takes to load and unload cargo. This helps to speed up operations as well as minimize the risk of accidents by providing operators with better awareness of their surroundings.<h1 dir="ltr">Smart Home and IoT Applications</h1>The integration of radar technology into smart home devices and the broader Internet of Things (IoT) ecosystem is ushering in a new era of enhanced functionality and intuitive user experiences. Radar sensors, with their ability to detect motion, presence, and even the breathing patterns of individuals, are becoming key components in making smart homes more responsive and personalized.One of the primary advantages of radar in smart homes is its precision and reliability. Unlike&nbsp;<iframe id="65d73b975a2c0eb706a8d3f0" width="250" class="specs-iframe" height="440" src="https://wevolver.com/iframe/specs/microchip-technology-pic32cz-ca90-curiosity-ultra-development-board?iframe=true" frameborder="0" scrolling="no" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe> traditional motion sensors that might be triggered by irrelevant movements, radar can discern between different types of motion, distinguishing between a person walking into a room and minor movements like curtains fluttering. This capability allows for smarter automation of lighting, heating, cooling, and security systems, ensuring they operate more efficiently and only when needed. [5]For instance, smart thermostats equipped with radar can adjust the temperature based on the number of people in a room and their level of activity, optimizing comfort and energy use. Similarly, security systems can use radar to monitor the surroundings of a property without the need for cameras, offering peace of mind without the intrusion of visual surveillance.Products equipped with radar are already on the market. Google's second-generation Nest Hub uses radar for sleep tracking, allowing users to monitor their sleep patterns without wearing any devices.[6] As radar technology continues to evolve, its integration into smart home devices and IoT ecosystems is expected to grow, offering even more sophisticated and user-friendly solutions.&nbsp;<h1 dir="ltr">Conclusion</h1>From its inception as a military tool in the 1930s, radar has undergone a significant transformation in the past century. As radar technology and related software algorithms become more advanced, various industries—from automotive safety and healthcare to industrial operations and smart homes—are now adopting the technology to adopt it. Whether it's in developing safer vehicles, supporting health monitoring, optimizing industrial processes, or enriching smart home experiences, it's clear that radar technology is poised a significant contributor to many of the world’s most important industries.<h3>References</h3><ol><li dir="ltr"><a href="https://www.radarmuseum.co.uk/history/world-war-two/#:~:text=In%20May%201935%20Watson%2DWatt,for%20the%20crossed%20receiving%20antennas" target="_blank">https://www.radarmuseum.co.uk/history/world-war-two/#:~:text=In%20May%201935%20Watson%2DWatt,for%20the%20crossed%20receiving%20antennas</a>.</li><li dir="ltr"><a href="https://www.ti.com/document-viewer/lit/html/SSZT307#:~:text=A%20radar%20sensor%20can%20also,event%20of%20a%20medical%20issue" target="_blank">https://www.ti.com/document-viewer/lit/html/SSZT307#:~:text=A%20radar%20sensor%20can%20also,event%20of%20a%20medical%20issue</a>.</li><li dir="ltr"><a href="https://ieeexplore.ieee.org/document/9289952" target="_blank">https://ieeexplore.ieee.org/document/9289952</a></li><li dir="ltr"><a href="https://sickconnect.com/safety-technology-radar-2d-lidar-3d-tof-use/" target="_blank">https://sickconnect.com/safety-technology-radar-2d-lidar-3d-tof-use/</a></li><li dir="ltr"><a href="https://www.innosent.de/en/sector/building-automation-smart-home/" target="_blank">https://www.innosent.de/en/sector/building-automation-smart-home/</a></li><li dir="ltr">https://support.google.com/googlenest/answer/10357288?hl=en&amp;co=GENIE.Platform%3DAndroid</li></ol>

From its beginnings as a military technology, radar has found its way into many of the world’s most important industries. 


Exploring the Emerging Uses of Radar Technology

Explore the transformative power of precision agriculture, highlighting innovations like Particle's M-Series and the future of sustainable farming. Dive into the evolution, technologies, and trends shaping tomorrow's agriculture.

Unearthing the Potential of Precision Agriculture

The architectures of embedded systems continue to evolve as newer technologies become available to design engineers. What used to be a single central processing unit surrounded by interface and logic circuitry is now a multiprocessor multi-core design with advanced integrated peripheral functionality—many with their own dedicated microcontrollers and resources to contend with.The once clearly delineated computer edge is now a much vaster and more distributed architecture. Computers that were islands to themselves are now a brick in the wall as they integrate into larger global high-speed connectivity. The hierarchal nature of globally and locally distributed microcontrollers means dedicated processing can occur closer to where data is being generated. The network is the computer.As higher-resolution data is sensed and processed, chunks of information extraction at each level often result in huge data sets that require a massive pool of immediate and virtual low-latency storage. Smart houses integrate into a higher level of the distributed processing hierarchy to behave in a city management process domain. Eventually, the need for our power grid to become a dynamically intelligent entity will be more apparent as electric vehicles and charges become the norm.In all cases, the Internet of Things (IoT) is central. Everything is connected: from handheld devices to cars and homes, traffic lights to biohazard sensors, factories to cities. This results in each system having multiple edges—some secure, some less so. In this evolving landscape of connectivity, machine learning is crucial as security concerns continually increase with hostile forces trying to wreak havoc.<h2>Machine Learning Is Key</h2>Designers of modern factories, appliances, and more seek machine learning (ML) solutions to tackle new challenges and allow companies to advance and compete. However, low latencies are required to allow useful data integration from extensive and varied sources. As a result, data must be accessed and transported globally very quickly to make these higher-level "thinking machines" respond in an effective and reasonable amount of time.&nbsp;This poses a challenge. Process-intensive security schemes and algorithms can add latency, meaning hardware security acceleration is needed and must be robust enough to protect against threats. Often, vital infrastructure is online and requires high-security protection.To meet these processing and security requirements, this new generation of designs calls for highly integrated MCUs. Communications data rates have grown from 50 bits per second (bps) to 10 gigabits per second (Gbps). Software-controlled bit banging will not work at these higher rates, so very high-speed communications hardware must be incorporated into modern microcontrollers.Additionally, wireless options like Wi-Fi® and Bluetooth®, as well as wired technologies like Ethernet and USB 3.x communications, must peacefully coexist in one system. Intelligent edge devices like facility routers can implement each of these simultaneously. Modern microcontrollers house several encapsulated protocol standards using dedicated accelerated hardware to further unburden CPUs.Analog and digital signal processing (DSP) requirements must also be addressed, especially with the many IoT devices that include sensor systems as part of their functional requirements. DSP functionality is critical to meet response times for industrial IoT control loops, whether it be simple thermostats or complex high-speed analog data streams from real-time factories. All this increased performance and functionality must be low power and feature power management techniques, as server farms already use tremendous amounts of energy.<h2>Meet the MCX N Series</h2>NXP Semiconductors' new <a href="https://www.mouser.com/new/nxp-semiconductors/nxp-mcx-n-mcus/" target="_blank">MCX N</a> Series advanced processor engines are general-purpose and application-specific microcontrollers based on Arm® Cortex®-M33 CPUs. The MCX N Series devices feature a rich mix of hardware-accelerated peripherals, communications, and signal processing, focusing on scalability and ease of development (Figure 1).<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzE0OTg2MjY2ODM1LU1DWF9CbG9ja19EaWFncmFtLndlYnAiLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjk1MCwiZml0IjoiY292ZXIifX19" style="width: 100%px;" class="fr-fic fr-dib">Figure 1: The high-speed Arm processing cores are surrounded by advanced memory interfaces and controllers, analog converters and DSP accelerators, communications interfaces, and security. (Source: NXP Semiconductors)At the heart of the microcontroller is a pair of 150MHz Cortex-M33 processors with up to 2MB of flash memory (code and data) and 512kB of SRAM. Additional dedicated hardware for DSP and CORDIC (pseudo multiplication and division) acceleration functions allows fast implementation of math-intensive algorithm control loops. One of the key components of this microcontroller is a hardware accelerator, eIQ® Neutron Neural Processing Unit (NPU).The MCX N Series features a plethora of communications interfaces, including Ethernet, USB FS (12Mbits/sec), USB HS (480Mbits/sec), I³C, CAN FD, and UART, as well as advanced mixed-signal interfaces like four single-ended or two differential 16-bit analog-to-digital converter (ADC) channels, 12- and 14-bit digital-to-analog converters (DACs), op amps, comparators, and stable temperature voltage references. A digital Synchronous Audio Interface (SAI) can generate waveforms and levels, and touch-sensing interfaces reduce form factors for handheld and space-constrained designs.The microcontrollers also feature NXP’s EdgeLock® Secure Enclave, Core Profile to ensure device-wide security intelligence, run time attestation, silicon root trust, and key management. Other security features include extensive cryptographic services, trust provisioning, and simplified path certifications. A high-performance crypto engine is also built in to perform on-the-fly encryption and decryption that provides a secure boot.<h3>Machine Learning with the MCX N Series</h3>An important feature of the NXP MCX N microcontrollers is the elQ® Neutron NPU (Figure 2). The NPU's scalability to billions or trillions of operations per cycle has the power to implement different learning techniques. One technique, the convolutional neural network (CNN) architecture, is a feed-forward neural network that learns feature engineering through filters. Also supported are recurrent neural networks (RNN), which are well suited for sequential time series data sets as part of the deep learning algorithms. Temporal convolution networks (TCN), which employ casual convolutions and dilations, provide adaptive learning and are also supported by the NXP elQ Neutron NPU.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzE0OTg2Mjg3NTg0LU5YUCBlbFEgTmV1dHJvbiBOUFUud2VicCIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 100%px;" class="fr-fic fr-dib">Figure 2: The MCX N microcontrollers’ scalable eIQ NPU is a dedicated controller core with in-line dequantization, activation, and pooling. It boasts learning times that are 30 times faster than conventional computational cores. (Source: NXP Semiconductors)<h2 id="isPasted">The Road to Development</h2>Unified software tools are essential for design engineers and software developers. The NXP MCUXpresso suite of development software and tools can help designers with a variety of tasks, including RTOS development.A choice of integrated development environments (IDEs), including MCUXpresso for VS Code, MCUXpresso IDE, IAR Embedded Workbench and Arm Keil MDK, work with a configuration tool to configure peripherals and multifunction pins. Bootables and utilities work with debug tools like Segger, NXP MCU-Link, FreeMASTER, and PEmicro to provide breakpoint, trace, and control/monitor functions that aid in software and firmware development. &nbsp;GUI Guider helps design HMI graphics libraries and displays.The elQ machine learning software development environment is essential, leveraging inference engines, neural network compilers, optimized libraries, and deep learning toolkits. The hardware abstraction layers support importing Pytorch, TensorFlow and ONNX models and running inference with TensorFlow Lite for Microcontrollers. These neural nets help learn and output useful information for sensor data in anomaly detection and predictive maintenance, voice and keyword recognition response, as well as image and video processing for object detection and recognition.The eIQ Toolkit provides a machine learning workflow and tools that enable graphical or command line interface to build, profile, and deploy your machine learning models with runtime insights. The eIQ portal is a graphic tool that lets designers create, optimize, debug, and export machine learning models. It can also import models from TensorFlow.NXP offers a wide range of application software, examples, reference designs, application notes, articles, and blogs on their website for applications such as audio, cloud connectivity, machine learning, motor control, RTOS, security, voice processing, touch sensing, and both wired and wireless connectivity.<h2>Conclusion</h2>Finding the right processor solution can take time and research. Not every design needs high-end supercomputing horsepower, but many applications in the Industrial and IoT edge require a significant amount of processing power and high-end peripherals to perform.The NXP MCX N Series is designed to meet these needs and more as it addresses the challenges of modern intelligent edge applications, such as IoT, security, power constraints, machine learning, and cost. With a mature and comprehensive development environment, the MCX N Series is ready to help engineers develop their designs, including newer technologies like neural networking and machine learning.

NXP Semiconductors' new MCX N Series advanced processor engines are general-purpose and application-specific microcontrollers based on Arm® Cortex®-M33 CPUs. 

The Evolving Edge: Transformation Is Now

The globalization of supply chains is being formed on production lines that are able to supply only the required quantity of products at the time required. This means that an obstacle arising in one place in the production line may strike a major blow to the entire supply chain.The causes of production delays and stoppages include conflicts, disasters, raw material shortages, and equipment and device failures. In particular, production stoppages and the outflow of defective products due to equipment and device failures may lead to major problems for manufacturers. These problems include the expense required to recover those defective products and opportunity losses due to product supply stoppages. Therefore, equipment maintenance, which bears responsibility for the stable operation of the production line, is an important issue that holds the key to the life of manufacturers.The importance of equipment maintenance has been strongly expressed up to now. The techniques of equipment maintenance have also been advancing from breakdown maintenance to preventive maintenance and then onto predictive maintenance as well in recent years.We introduce in an easy-to-understand manner equipment maintenance that is continuing to evolve in this way—from basic knowledge such as the types of equipment maintenance and their advantages and disadvantages to the technologies to realize the predictive maintenance that is considered the ideal form of equipment maintenance.<h2>What Is Equipment Maintenance?</h2>Equipment maintenance refers to the activities to keep various production equipment in factories functioning normally. It is also called “machine maintenance.” The purposes of equipment maintenance are cited as being, for example, to prolong the life of machine components used in equipment, to shorten machine and device downtime, and to prevent unexpected failures in addition to repairing equipment that has failed.Moreover, equipment maintenance up to now has mainly focused on machines and devices. Now, the focus is also on the software that controls the Programmable Logic Controllers (PLCs) and machines and devices with the conversion of regular factories into smart factories using industrial robots, machine vision, and other technologies.There are other terms similar to maintenance such as “upkeep” and “care,” but these are the same as equipment maintenance. The reason is that they all involve inspecting equipment and then servicing or repairing it as necessary so that it does not fail.<h2>Types of Equipment Maintenance and Their Advantages and Disadvantages</h2>Equipment maintenance includes breakdown maintenance and preventive maintenance. Preventive maintenance is further broken down into time-based maintenance and condition-based maintenance (Figure 1). We explain here the features and the advantages and disadvantages of each type.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1714985901545-predictive-maintenance-img0001_en.png" style="width: 100%px;" class="fr-fic fr-dib">Fig. 1: Types of Equipment Maintenance<h3 id="isPasted">What Is Breakdown Maintenance?</h3>This is maintenance that is performed after a piece of equipment’s functions have declined or after it has stopped functioning (Fig. 2).<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1714985917150-predictive-maintenance-img0002_en.png" style="width: 100%px;" class="fr-fic fr-dib">Fig. 2: Breakdown MaintenanceAdvantages: The advantages of breakdown maintenance include the fact that the burden on maintenance work is low because the condition of the equipment is not checked until it fails or a malfunction is discovered. Another advantage is that it keeps the costs involved in maintenance low in the case of minor failures. Disadvantages: Failures and malfunctions occur unexpectedly. Therefore, there may be delays in obtaining repair components, and so it may take some time to carry out repairs. In addition, there are risks such as major disruptions to production plans if the failure or malfunction occurs in a core piece of equipment. Furthermore, if there is a delay in discovering the failure or malfunction in the equipment, it may lead to defective products and their flowing out of the factory. Dealing with such issues may require a considerable amount of expense and time.<h3>What is Preventive Maintenance?</h3>This is maintenance that is performed based on a piece of equipment’s service life, the number of times it is used, its condition, or other factors. It is also called “time-based maintenance” (Fig. 3).<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1714985934940-predictive-maintenance-img0003_en.png" style="width: 100%px;" class="fr-fic fr-dib">Fig. 3: Preventive MaintenanceAdvantages: The maintenance work is performed once a certain period has been reached. Therefore, it is possible to prevent failures and malfunctions from occurring in equipment. It is an effective maintenance method when the service life of each component used in equipment or the number of times those components are used can be grasped accurately. Disadvantages: It is necessary to establish criteria to ascertain as accurately as possible the life of components. Maintenance may be performed after a failure if the criteria is not accurate. Conversely, component and time losses may arise such as from the replacement of components that can still be used.<h3>What Is Predictive Maintenance?</h3>This is maintenance that is performed in line with extent of a piece of equipment’s deterioration by constantly monitoring its condition. It is also called “condition-based maintenance” (Fig. 4).<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1714985956264-predictive-maintenance-img0004_en.png" style="width: 100%px;" class="fr-fic fr-dib">Fig. 4: Predictive MaintenanceAdvantages: The maintenance work is performed when the equipment deteriorates. Therefore, it is possible to reduce component and time losses such as from the periodic stoppage of equipment for maintenance and the replacement of components that can still be used. Of course, it is also possible to prevent failures and malfunctions that would lead to the equipment stopping unexpectedly. Disadvantages: It is essential to have equipment to constantly monitor the condition of equipment and to store the collected data. Specifically, the constant monitoring of equipment requires a large number of various types of sensors. In addition, data loggers and similar recording devices are needed to store data. Furthermore, it is necessary to have equipment and other technologies to connect to those recording devices to communicate the data.<h2>Four Technologies to Turn Preventive Maintenance into Predictive Maintenance</h2>The most common method of maintenance currently is preventive maintenance whereby equipment is periodically maintained by determining the inspection timing based on the service life of each component used in equipment or the number of times those components can be used. Furthermore, there are an increasing number of cases in which semi-predictive maintenance is being adopted. This is when a large number of sensors that measure vibrations, temperature, current, voltage, and other elements are attached to equipment and thresholds are then set for each of them with maintenance being performed when those upper or lower limits are exceeded. In fact, a survey conducted on companies engaged in converting regular factories into smart factories produced results showing that over 96% of them cited “equipment maintenance utilizing sensors and AI” as the reason they are continuing to convert their factories into smart factories (Fig. 5).<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1714985974057-predictive-maintenance-img0005_en.png" style="width: 100%px;" class="fr-fic fr-dib">Fig. 5: Reasons Why Companies Want to Continue Converting Regular Factories into Smart Factories* About the survey:&nbsp; Surveying entity: Murata Manufacturing Co., Ltd. Survey focus: 11,084 workers in the manufacturing industry in Japan (screening survey) / 500 workers in the manufacturing industry involved in converting their company’s regular factories into smart factories (main survey) Survey method: Internet survey Survey period: 3 days from January 25 (Wed.) to 27 (Fri.), 2023 * The total values may not necessarily match due to rounding.In this way, equipment maintenance is currently undergoing a switch from preventive maintenance to predictive maintenance. We explain here the four technologies that can help with this switch from preventive maintenance to predictive maintenance.<h3>1. Introduction of Sensors into Equipment Maintenance</h3>Predictive maintenance begins with constant monitoring of the condition of equipment. There are individual differences in judgment when this monitoring is performed with the eyes and touch of people. This means it is not possible to respond accurately. We can quantify the condition of equipment by introducing sensors. Visualizing and analyzing the data collected from those sensors then enables us to respond more accurately. However, this requires installing many types and a large number of sensors in large factories. Accordingly, routing and connecting the sensor wiring requires many man-hours when changing the setup. Therefore, it is best to have noise-resistant sensors capable of wireless communication with a long transmission distance.Moreover, devices have been developed that can keep a log of the actions taken by workers on manufacturing lines in recent years. It is also possible to record how those workers respond when trouble occurs. Utilizing these records allows various matters to be saved as data, including the deterioration of equipment that occurs on the manufacturing line and the actions taken by workers in response. This data can be used to give hints to improving processes in addition to maintenance.<h3>2. Visualization of the Condition of Complex Equipment: Sensor Fusion</h3>Sensor fusion is a technology that realizes cognitive functions that cannot be obtained with a single sensor on an engineering basis. Specifically, sensor fusion has already been introduced into Advanced Driving Assistant Systems (ADAS). For instance, examples include reading the shapes of people, obstacles, and other objects with an image sensor and temperature sensor and then measuring the distance with a radar sensor utilizing milliwaves and microwaves to grasp the situation in the direction in which those objects are moving. It has also become possible to display warning messages on monitors in vehicles and to apply brakes automatically. This utilizes sensor fusion as a technology to, for example, automatically determine the situation with data collected from multiple sensors such as image sensors and radars and to then convey those results to the driver. When we use this technology in equipment maintenance, we can analyze the measurement data from vibration sensors, temperature sensors, current sensors, and voltage sensors on an integrated basis. For example, if a current or voltage value is abnormal despite the motor vibrations and temperature being normal, we can determine that there has been a problematic change to the load on the part where the motor is operating. In addition, if an abnormal value is seen only in a vibration sensor, it is likely to be bearing wear, shaft deformation, level abnormality, or similar (Fig. 6).<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1714986016706-predictive-maintenance-img0006_en.png" style="width: 100%px;" class="fr-fic fr-dib">Fig. 6: Introduction of Sensor Fusion into Equipment MaintenanceConventionally, such abnormalities were grasped and determined by workers reading each sensor value and then comparing those values with their past experiences.&nbsp; However, if we use the technology of sensor fusion, we can aggregate data collected by many sensors and display it on monitors or other devices as results that indicate the condition of equipment. This allows even inexperienced workers to accurately grasp the condition of equipment.<h3>3. Introduction of AI into Equipment Maintenance</h3>Sensor fusion is an outstanding technology. However, as the number of sensors increases and measurements become more precise, the amount of data increases. This leads to calculations becoming complex. It also becomes difficult to output data that indicates accurate results. Accordingly, the introduction of deep learning into equipment maintenance has come to be seen as important. Introducing the AI technology of deep learning into equipment maintenance enables data collected from multiple sensors to be integrated and analyzed by AI. If there is an error in the output results, it is corrected through machine learning. Furthermore, accurate results are produced. When we utilize AI in equipment maintenance, we become able to respond correctly to the condition of equipment that is constantly changing with self-learning such as by comparing the data collected during normal times and data collected from sensors to extract the difference in addition to simply detecting abnormalities that are determined by establishing a threshold (Fig. 7).<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1714986035251-predictive-maintenance-img0007_en.png" style="width: 100%px;" class="fr-fic fr-dib">Fig. 7: Introduction of AI into Equipment MaintenanceIn this way, introducing AI into equipment maintenance doesn’t just reduce the differences in judgments due to differences in the proficiency level of the workers; we can also solve issues in conventional maintenance activities that rely on manpower, which involves investing a lot of personnel and hours in work, including monitoring and inspections.&nbsp;<h3>4. Introduction of Edge AI Cameras and Other Edge AI Devices</h3>Edge AI is a technology that applies edge computing to AI. In edge AI, AI processing is performed with various sensors, cameras, mobile terminals, and other edge devices at the end of networks (Fig. 8). On the other hand, in contrast to edge AI, there is a technology called “cloud AI.” This is a technology that applies cloud computing to AI. This means AI processing is performed on the cloud server connected to the network and the results are then returned to the edge devices. If we compare edge AI and cloud AI, we find that there are advantages to edge AI. These advantages include outstanding response speed and data confidentiality because the AI processing is performed on edge devices without involving a network. This also means edge AI is not impacted by the quality of the network. High data confidentiality is an absolute requirement especially for equipment maintenance that handles data in factories. Moreover, a high response speed is sought in vibration and acceleration calculations, which require data collection at high sampling cycles. Therefore, we can say that edge AI is an attractive technology for predictive maintenance involving the handling of large volumes of data.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1714986052981-predictive-maintenance-img0008_en.png" style="width: 100%px;" class="fr-fic fr-dib">Fig. 8: Introduction to Edge AI DevicesHowever, edge devices equipped with edge AI are small. This means they have disadvantages such as inferior memory size and calculating capacity compared to cloud AI. Accordingly, it is necessary to select either cloud AI, edge AI, or to use both together according to your purpose.<h2>Summary</h2>The importance of equipment maintenance for the stable operation of manufacturing lines has long been recognized. Nevertheless, on the other hand, it is also true that too much emphasis on production has led to daily maintenance activities being neglected. Nowadays, with the globalization of manufacturing having long since progressed, manufacturing lines are continuing to constantly supply products to supply chains. In particular, supply chain management has been built based on production output during normal operations in regular factories that are being converted into smart factories. Under these circumstances, unexpected equipment failures on the manufacturing line can deal a major blow to the supply chain and cause damage to a company’s image. Moreover, the introduction of sensor fusion, AI, and other technologies into equipment management is not just about optimizing equipment maintenance, reducing personnel expenses, and solving labor shortages. It is a cutting-edge approach with many advantages including the continuing maintenance of high productivity, the optimization of energy usage, and the effective utilization of personnel. It is no exaggeration to say that realizing predictive maintenance by introducing sensor fusion, AI, and other technologies into equipment maintenance is the key to future corporate management for the manufacturing industry, which is surrounded by a complex economic environment such as the widening of supply chains.&nbsp;<hr><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1714986081243-1714986081243.png" class="fr-fic fr-dii">If you have any questions based on this article that you would like to discuss with an expert at Murata, don't hesitate to reach out. There's an entire team ready to support you with your question.<a href="https://www.murata.com/en-eu/contactform?&Detail=Wevolver%20request" target="_blank" rel="nofollow" class="button-main-action">GET IN TOUCH</a>

The importance of equipment maintenance is clear. In recent years, equipment maintenance techniques have also advanced from breakdown maintenance to preventive maintenance and now focus on predictive maintenance.

The Technology That Realizes Predictive Maintenance

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