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As IoT technology progresses, the question of how to power these devices, particularly in locations where reliable electrical sources are scarce, presents a significant challenge. Researchers at the University of Utah’s College of Engineering have pioneered a new form of battery that could help solve this dilemma. The solution, which is at the proof of concept stage, comes in the form of a pyroelectrochemical cell (PEC). Developed by associate professors of mechanical engineering Roseanne Warren and Shad Roundy, the integrated device harvests ambient thermal energy and converts it into stored electrochemical energy. This effectively creates a supercapacitor or battery, which could be ideal for IoT and sensor applications. Low levels of energy The device works by charging with changes in its surrounding temperatures, whether located inside a vehicle, an aircraft, or even underneath soil in an agricultural environment. “We’re talking very low levels of energy harvesting," Warren said, "but the ability to have sensors that can be distributed and not need to be recharged in the field is the main advantage. We explored the basic physics of it and found that it could generate a charge with an increase in temperature or a decrease in temperature.” Whilst solar cells can provide an alternative power source of IoT devices, the practicalities often present issues. “In a lot of environments, you run into two problems,” said Roundy. “One is that it gets dirty over time. Solar cells have to be kept clean. So in these types of applications, they get dirty and their power degrades. And then there are a lot of applications where you just don’t have sunlight available. For example, we work on soil sensors that we put just under the top surface of the soil. You’re not going to get any sunlight.” With the use of a pyroelectric composite material made of porous polyvinylidene fluoride (PVDF) and barium titanate nanoparticles as the separator in an electrochemical cell, the device’s electrical properties change as it's heated or cooled. This action modifies the polarization of the pyroelectric separator. This shifting of temperatures in turn creates an electric field within the cell, moving ions around and allowing the cell to store energy. Despite only producing up to 100 microjoules per square centimeter from a single heating/cooling cycle, this could be enough for the needs of some IoT applications. The study, funded by the National Science Foundation, is the cover feature in the March 21 edition of the journal Energy & Environmental Science, published by the Royal Society of Chemistry. More from TechRadar Pro Microsoft AI finds new material that could replace lithium batteriesHow to keep your IoT devices secureTwo sides of AI in the Industrial Internet of Things View the full article

Authors/Presenters: Binbin Zhao, Shouling Ji, Xuhong Zhang, Yuan Tian, Qinying Wang, Yuwen Pu, Chenyang Lyu, Raheem Beyah Many thanks to USENIX for publishing their outstanding USENIX Security ’23 Presenter’s content, and the organizations strong commitment to Open Access. Originating from the conference’s events situated at the Anaheim Marriott; and via the organizations YouTube channel. Permalink The post USENIX Security ’23 – UVSCAN: Detecting Third-Party Component Usage Violations in IoT Firmware appeared first on Security Boulevard. View the full article

Today, AWS IoT Core for LoRaWAN announced the expansion of the public network support in the Spain region. With this expansion, Internet of Things (IoT) customers that offer LoRaWAN-based systems and solutions in Spain can seamlessly connect their LoRaWAN-powered devices to AWS over a public network infrastructure. This public infrastructure is provided as a service and supported by Everynet - a global LoRaWAN network operator offering networks in the United States, United Kingdom, and Spain. Thanks to the publicly available network infrastructure, customers in Spain can realize improved savings in time and costs associated with managing a private network infrastructure for LoRaWAN-based solutions. View the full article

Running and transforming a successful enterprise is like being the coach of a championship-winning sports team. To win the trophy, you need a strategy, game plans, and the ability to bring all the players together. In the early days of training, coaches relied on basic drills, manual strategies, and simple equipment. But as technology advanced, so did the art of coaching. Today, coaches use data-driven training programs, performance tracking technology, and sophisticated game strategies to achieve unimaginable performance and secure victories. We see a similar change happening in industrial production management and performance and we are excited to showcase how we are innovating with our products and services to help you succeed in the modern era. Microsoft recently launched two accelerators for industrial transformation: Azure’s adaptive cloud approach—a new strategy Azure IoT Operations (preview)—a new product Our adaptive cloud approach connects teams, systems, and sites through consistent management tools, development patterns, and insight generation. Putting the adaptive cloud approach into practice, IoT Operations leverages open standards and works with Microsoft Fabric to create a common data foundation for IT and operational technology (OT) collaboration. Azure IoT Operations Build interoperable IoT solutions that transform physical operations at scale Discover solutions accelerating industrial transformation with azure iot operations Read the blog We will be demonstrating these accelerators in the Microsoft booth at Hannover Messe 2024, presenting the new approach on the Microsoft stage, and will be ready to share exciting partnership announcements that enable interoperability in the industry. Here’s a preview of what you can look forward to at the event from Azure IoT. Experience the future of automation with IoT Operations Using our adaptive cloud approach, we’ve built a robotic assembly line demonstration that puts together car battery parts for attendees of the event. This production line is partner-enabled and features a standard OT environment, including solutions from Rockwell Automation and PTC. IoT Operations was used to build a monitoring solution for the robots because it embraces industry standards, like Open Platform Communications Unified Architecture (OPC UA), and integrates with existing infrastructure to connect data from an array of OT devices and systems, and flow it to the right places and people. IoT Operations processes data at the edge for local use by multiple applications and sends insights to the cloud for use by multiple applications there too, reducing data fragmentation. For those attending Hannover Messe 2024, head to the center of the Microsoft booth and look for the station “Achieve industrial transformation across the value chain.” Watch this video to see how IoT Operations and the adaptive cloud approach build a common data foundation for an industrial equipment manufacturer. Consult with Azure experts on IT and OT collaboration tools Find out how Microsoft Azure’s open and standardized strategy, an adaptive cloud approach, can help you reach the next stage of industrial transformation. Our experts will help your team collect data from assets and systems on the shop floor, compute at the edge, integrate that data into multiple solutions, and create production analytics on a global scale. Whether you’re just starting to connect and digitize your operations, or you’re ready to analyze and reason with your data, make predictions, and apply AI, we’re here to assist. For those attending Hannover Messe 2024, these experts are located at the demonstration called “Scale solutions and interoperate with IoT, edge, and cloud innovation.” Check out Jumpstart to get your collaboration environment up and running. In May 2024, Jumpstart will have a comprehensive scenario designed for manufacturing. Attend a presentation on modernizing the shop floor We will share the results of a survey on the latest trends, technologies, and priorities for manufacturing companies wanting to efficiently manage their data to prepare for AI and accelerate industrial transformation. 73% of manufacturers agreed that a scalable technology stack is an important paradigm for the future of factories.1 To make that a reality, manufacturers are making changes to modernize, such as adopting containerization, shifting to central management of devices, and emphasizing IT and OT collaboration tools. These modernization trends can maximize the ROI of existing infrastructure and solutions, enhance security, and apply AI at the edge. This presentation “How manufacturers prepare shopfloors for a future with AI,” will take place in the Microsoft theater at our booth, Hall 17, on Monday, April 22, 2024, at 2:00 PM CEST at Hannover Messe 2024. For those who cannot attend, you can sign up to receive a notification when the full report is out. Learn about actions and initiatives driving interoperability Microsoft is strengthening and supporting the industrial ecosystem to enable at-scale transformation and interoperate solutions. Our adaptive cloud approach both incorporates existing investments in partner technology and builds a foundation for consistent deployment patterns and repeatability for scale. Our ecosystem of partners Microsoft is building an ecosystem of connectivity partners to modernize industrial systems and devices. These partners provide data translation and normalization services across heterogeneous environments for a seamless and secure data flow on the shop floor, and from the shop floor to the cloud. We leverage open standards and provide consistent control and management capabilities for OT and IT assets. To date, we have established integrations with Advantech, Softing, and PTC. Siemens and Microsoft have announced the convergence of the Digital Twin Definition Language (DTDL) with the W3C Web of Things standard. This convergence will help consolidate digital twin definitions for assets in the industry and enable new technology innovation like automatic asset onboarding with the help of generative AI technologies. Microsoft embraces open standards and interoperability. Our adaptive cloud approach is based on those principles. We are thrilled to join project Margo, a new ecosystem-led initiative, that will help industrial customers achieve their digital transformation goals with greater speed and efficiency. Margo will define how edge applications, edge devices, and edge orchestration software interoperate with each other with increased flexibility. Read more about this important initiative. Discover solutions with Microsoft Visit our booth and speak with our experts to reach new heights of industrial transformation and prepare the shop floor for AI. Together, we will maximize your existing investments and drive scale in the industry. We look forward to working with you. Azure IoT Operations Azure IoT Hannover Messe 2024 1 IoT Analytics, “Accelerate industrial transformation: How manufacturers prepare shopfloor for AI”, May 2023. The post Azure IoT’s industrial transformation strategy on display at Hannover Messe 2024 appeared first on Microsoft Azure Blog. View the full article

Take advantage of this limited time opportunity, and get the All-In-One Raspberry Pi & Arduino Developer Bundle at $59.97. Only through April 21st.View the full article

The highly anticipated IoT Tech Expo North America is set to return to the Santa Clara Convention Center on June 5-6, 2024.View the full article

Advancements in Internet of Things (IoT) technologies are paving the way for a smarter, more interconnected future. They’re taking down communication barriers among consumers and businesses across different industries. According to Global Data, the global IoT market could be worth $1.1 trillion in 2024, potentially growing at a 13% compound annual growth rate (CAGR). Enterprise […] The post Expert Insights on IoT Security Challenges in 2024 appeared first on TuxCare. The post Expert Insights on IoT Security Challenges in 2024 appeared first on Security Boulevard. View the full article

5G technology impacts not just our daily lifestyle but the Internet of Things (IoT) as well. The world of 5G is not only transformed by hyper-connectivity but is also involved in the future hinges on a critical element: IoT security. While 5G has remarkable speed and capacity, it also provides a large attack surface. Unlike […] The post Impact of IoT Security for 5G Technology appeared first on Kratikal Blogs. The post Impact of IoT Security for 5G Technology appeared first on Security Boulevard. View the full article

Industry 4.0 has been a bedrock of innovation for at least the last decade. Now, as generative AI, advanced Machine Learning, and modelling algorithms become more accessible with “off-the-shelf” technologies, questions are being raised about the value – and risks – artificial intelligence might bring to the sector. As industries embrace the Internet of Things (IoT), AI has emerged as a transformative force, enhancing operational efficiencies, offering predictive capabilities, and paving the way for easier strategic decision-making in unprecedented ways. In manufacturing alone, spend on AI is predicted to reach $9.8 billion by 2027 – a CAGR of almost 25% during the forecast period. Industries obviously see the value of AI when it comes to harnessing IoT effectively. However, this advancement also brings with it complex security challenges and ethical dilemmas. Let us delve into these dual perspectives of AI in industrial IoT, exploring how its integration is reshaping the industry while simultaneously raising crucial questions about cybersecurity and ethical considerations. The Upside of AI on Industrial IoT The transformative impact of AI in the industrial IoT space extends across a variety of use cases, each demonstrating its power to streamline and innovate. For instance, in manufacturing, AI-driven predictive maintenance is not just about early fault detection; it is about understanding patterns that lead to wear and tear, extending the overall lifespan of machinery. In supply chain management, AI algorithms move beyond basic stock control, offering real-time tracking and predictive analytics for efficient inventory management and a responsive approach to demand fluctuations. Quality control, another crucial area, is also revolutionized by AI's ability to perform high-precision inspections at speeds unattainable by human workers. These implementations showcase AI's capacity not only to optimize existing processes but also to open new avenues for operational excellence and strategic foresight in the industrial sector. Yet, for all these groundbreaking advantages, businesses owe it to themselves to tread carefully before deploying AI as part of their IoT ecosystems. Security Challenges in AI-Enhanced Industrial IoT As AI propels the industrial IoT into new frontiers, it simultaneously broadens the attack surface, introducing unique security challenges. The complexity of IoT ecosystems, combined with AI's data-intensive nature, creates vulnerabilities that can be exploited by cyber threats. These vulnerabilities range from unauthorized access to sensitive data, to potential hijacking of networked industrial systems. The interconnectedness inherent in IoT means that a breach in one node can have cascading effects, compromising the integrity of entire networks. This was evidenced at the Taiwan Semiconductor Manufacturing Company (TSMC) whose operations had to be shutdown following a WannaCry attack, hitting their $255m revenue. Addressing these security challenges requires a multifaceted approach. First, it is crucial to implement robust cybersecurity protocols specifically tailored for the IoT environment. This includes regular updates to security algorithms, secure data encryption methods, and vigilant network monitoring for any signs of intrusion. Additionally, there is an urgent need for a proactive strategy that anticipates potential threats and mitigates risks before they materialize. This involves not only advanced technological solutions but also a strong emphasis on training personnel to recognize and respond to security threats, creating a comprehensive defense against the multifaceted risks presented by AI in industrial IoT. Navigating the Risks Navigating the risks and challenges associated with AI in industrial IoT environments involves addressing both technical and ethical concerns. Technically, AI can become a target for cyberattacks, with the potential to cause significant disruptions in operational technology environments. Ensuring the reliability of AI systems in the face of corrupted data is also critical, as false positives or negatives in decision-making can have far-reaching consequences. Ethical challenges include managing the privacy concerns associated with the vast amounts of data processed by AI systems and addressing potential biases in AI algorithms. To effectively manage these challenges, a comprehensive approach is required. Cybersecurity measures need to focus on protecting AI systems from attacks and ensuring their reliable operation. This involves developing robust security protocols that can adapt to the evolving nature of cyber threats. On the ethical front, regulations and guidelines should be established to promote transparency, accountability, and fairness in AI applications. This includes addressing data protection, mitigating biases, and ensuring that AI systems operate within ethical boundaries. Such measures will be crucial in maintaining trust in AI systems and ensuring their beneficial use in industrial IoT environments. Strategies for mitigating risk To effectively mitigate the risks associated with AI in industrial IoT, it is essential to adopt a proactive and comprehensive security strategy. This involves implementing security controls based on principles of zero trust and zero tolerance, ensuring that every component within the IoT ecosystem is verified and secure. Additionally, integrating good cyber hygiene practices across the board is crucial to safeguard the integrity of AI systems and the data they handle. These practices include regular system updates, thorough risk assessments, and diligent monitoring for potential vulnerabilities. Beyond technical measures, regulatory frameworks such as the EU AI Act play a pivotal role in addressing the broader implications of AI in industrial IoT. These regulations should focus on critical aspects such as data protection, bias prevention, transparency, and accountability in AI applications. The development of ethical guidelines for AI is also necessary to ensure that its deployment aligns with societal values and privacy concerns. By combining robust security measures with thoughtful regulation, industries can harness the full potential of AI in IoT while maintaining a secure and ethical operational environment. As AI continues to evolve within the industrial IoT landscape, its potential to revolutionize the sector is boundless. The future could see AI not just as a tool for efficiency and security, but as a collaborator in innovation, shaping the very fabric of industrial processes. This synergy of AI and IoT is poised to unlock new levels of creativity and efficiency, heralding an era where technology and human ingenuity converge to redefine the possibilities in industrial operations – but only if businesses can walk the line between value and risk effectively. We've listed the best patch management software. This article was produced as part of TechRadarPro's Expert Insights channel where we feature the best and brightest minds in the technology industry today. The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/news/submit-your-story-to-techradar-pro View the full article

Automotive companies leverage IoT to optimize manufacturing processes, improve vehicle management, and enhance transportationView the full article

Today, AWS IoT Core for LoRaWAN announces a new fleet monitoring application that enables developers capture and visualize critical operational and health parameters related to the functioning of LoRaWAN-based gateways and devices. AWS IoT Core for LoRaWAN is a fully managed LoRaWAN Network Server that supports cloud connectivity for LoRaWAN-based wireless devices. Using the new metrics feature, developers can now quickly capture system health data, such as connection signal strength, data rate, and gateway latency and analyze their fleet’s performance. View the full article

In a modern, rapidly changing world, technology is fast-growing and it is pushing the progress of humanity in a whole new direction. One of the most striking technology trends in the past year is the integration of Artificial Intelligence (AI) and the Internet of Things (IoT). The two champions of the tech revolution are AI and Internet of Things and the combination of them has resulted in smart systems that are much more sophisticated and creative. Integration of AI in IoT systems AI integration into the IoT system maximizes the potential of the smart devices. The joining of AI to the big network of interrelated devices in the Internet of Things allows us to create intelligent systems that will act and think like a human being. The AI technology drives these devices and they can instantly analyze and interpret data, producing useful information that makes them more efficient and productive. IoT machine learning allows devices to learn from data, and improve their performance without hard coding. This makes IoT devices more personalized and practical since they learn and improve their performance according to the actions and preferences of people who use them. A typical example is a smart speaker that can recognize and respond to various voices in a family thus giving a special experience to every user. One more essential feature of AI IoT is predictive analytics, when AI algorithms are applied for big data analysis of IoT devices, to find patterns and anomalies. The process of prediction in the situations where possible problems or failures occur let companies make proactive steps to prevent them which leads to saving time and loss of resources of businesses. When it is so, AI IoT predictive maintenance in the manufacturing industry can cut downtime and prolong the life of the equipment. In addition, AI IoT also facilitates the improvement of business decision-making as it provides real-time data and insights. This is particularly beneficial in sectors such as retail where data from IoT devices is employed in consumer behavior monitoring and analysis, a process that leads to improved marketing initiatives and greater sales. AI IoT could also play a role in supply chain optimization by ensuring an optimal stock level and route optimization enhancing cost efficiencies. However, AI integration into IoT systems comes with its share of issues. Privacy and security gees are the biggest concern. Because of the volumes of data that are collected and processed, there is the danger of data leaks and personal data misuse. The security protocols should be adhered to by organizations so that sensitive information is protected. In addition, the AI IoT application may be difficult and resource intensive to implement. These are the smaller enterprises or the people who would want to embrace this technology limitation. Moreover, rapid changes in technology may lead to compatibility issues between different devices and platforms, which would hinder the integration of AI and Internet of Things. The integration of AI & IoT has shown success in many industries in spite of these difficulties. The pace of technological development allows AI IoT to be utilized in more spectacular ways within a short period of time. Thus, the synergy and symbiosis is dynamic, and in this situation both companies and individuals must realize the dynamic symbiosis and find the possible ways to integrate them into their lives. Benefits of AIoT The fusion of AI and Internet of Things has huge advantages for both business and individual clients. Some of the key advantages include: 1. Increased efficiency and productivity: The automation of processes and AI for data analysis, makes IoT devices run faster and more efficiently creating a productive environment. 2. Cost savings: smart IoT devices improve energy management, cut maintenance costs, and prolong the life of machines, and this leads to savings for both business and individual users. 3. Improved decision-making: AI-driven IoT equipment allows companies to gather and process live data that is essential for the making of pertinent decisions. 4. Personalization: AIoT allows devices to learn from the activities and preferences of users, providing users with personalized experiences. Challenges of AIoT The AI and Internet of Things mix have its own set of challenges despite the advantages it offers. Some of the key challenges include: 1. Data privacy and security: Big data means that touch data is collected and analyzed making it a danger of a data leak and privacy concerns. Organizations have to ensure that the given security systems are implemented so that the sensitive data is secured. 2. Complex implementation: Internet of Things AI integration task is unaffordable for most companies due to the enormous resource and human requirements. 3. Compatibility issues: The pace of technological changes is rapid and it is rather hard to combine AI and IoT, since devices and platforms remain incompatible. An overview of real-world AI and IoT integration success stories Despite challenges, some organizations were able to deploy AI and Internet of Things to develop innovative solutions. Tesla represents how self-driving features powered by AI are merged with IoT sensors that create a smart, safer, and more efficient driving process. This combination enables Tesla vehicles to process real-time data and react to the change in road conditions which lowers the probability of accidents. The health industry is an example of successful implementation of AI and Internet of Things. Smart pills from companies such as Proteus and WellDoc, on the other hand, are equipped with sensors and AI algorithms to collect patient health data to provide personalized treatment prescriptions and reminders. Future Perspectives of AIoT The IoT artificial intelligence would revolutionize many sectors such as healthcare, transportation, manufacturing and agriculture, among others. As the number of IoT devices grows exponentially and AI capabilities can do more, we expect more advanced and sophisticated applications in the future. For example, smart homes integrated with AIoT can be a fully connected and automated living environment, and in the healthcare industry, AIoT will make patient care and disease management better. The integration of AI and Internet of Things is changing the mode of interaction with technology and our environment. Moreover, it is capable of improving efficiency, productivity, and decision-making and offers a personalized experience for users. However, it also has its own challenges which need to be dealt with for it to be successfully implemented. The rapid progress of the technology will take AIoT to yet another level in the future, hence it is important to engage artificial intelligence consultancy for your daily operations and understand how you can integrate the two for your efficient operations. The post The Integration of AI and IoT: Enhancing Smart Systems appeared first on DevOpsSchool.com. View the full article

London, 20 March 2024. Canonical has announced that Ubuntu Core, its operating system optimised for the Internet of Things (IoT) and edge, has received Microsoft Azure IoT Edge Tier 1 supported platform status from Microsoft. This collaboration brings computation, storage, and artificial intelligence (AI) capabilities in the cloud closer to the edge of the network. The power of the cloud on the edge Azure IoT Edge enables businesses to remotely and securely deploy and manage cloud-native workloads directly on their IoT devices, at scale, and with robust observability. With the ability to deploy and manage containerised applications on devices, teams can process data, run machine learning models, perform analytics, and carry out other tasks right at the edge of the network. This approach helps reduce latency, conserve bandwidth, and it provides more immediate insights from data near to where it is generated. It is especially useful in scenarios where real-time decision-making is crucial, where network connectivity might be unreliable, or where data privacy and security concerns demand local data processing. The security of Ubuntu Core Ubuntu Core is an operating system designed specifically for the IoT and embedded devices. Its range of features make it ideal for secure, reliable, and scalable deployments. Built on the power of Snaps, Ubuntu Core provides a minimal core with support for multiple architectures and types of devices. Security is baked-in with secure boot and full disk encryption, and over-the-air (OTA) transactional updates to ensure that devices are always up to date. Coupled with Canonical’s Long Term Support, which offers up to 10 years of maintenance and security updates, Ubuntu Core provides long-term peace of mind for IoT implementations. With the introduction of the Azure IoT Edge Snaps suite, the process of deploying edge workloads to the extensive array of devices and architectures supported by Ubuntu Core has become a streamlined, seamless, experience. Combined with the ability to remotely manage and configure both the processing and system components of fleets of devices directly from Azure, teams benefit from robust security and optimised performance. “With Microsoft committing their support for Ubuntu Core with the release of the Microsoft Azure IoT Edge Snaps we see another example of the industry’s enthusiasm to adopt the operating system to fulfil all of their IoT needs. We look forward to growing this relationship further with Microsoft in the future”. – Michael Croft-White, Engineering Director. “In collaboration with Canonical, we are making it simpler to reliably connect devices to Microsoft Azure IoT services. Snap support in Azure IoT Edge helps ensure consistent performance, enhanced security, and efficient updates across Linux distributions that support Snaps.” Kam VedBrat, GM, Azure IoT Further reading More information on Ubuntu Core can be found at ubuntu.com/core. Our “Intro to Ubuntu Core 22” webinar is a comprehensive resource for everything you need to know about Ubuntu Core. If you are not already familiar with Microsoft’s Azure IoT Edge, more information can be found here. Are you interested in running Ubuntu Core with Azure IoT on your devices and are working on a commercial project? Get in touch About Canonical Canonical, the publisher of Ubuntu, provides open-source security, support and services. Our portfolio covers critical systems, from the smallest devices to the largest clouds, from the kernel to containers, from databases to AI. With customers that include top tech brands, emerging startups, governments and home users, Canonical delivers trusted open source for everyone. View the full article

In today's fast-evolving technology landscape, the integration of Artificial Intelligence (AI) into Internet of Things (IoT) systems has become increasingly prevalent. AI-enhanced IoT systems have the potential to revolutionize industries such as healthcare, manufacturing, and smart cities. However, deploying and maintaining these systems can be challenging due to the complexity of the AI models and the need for seamless updates and deployments. This article is tailored for software engineers and explores best practices for implementing Continuous Integration and Continuous Deployment (CI/CD) pipelines for AI-enabled IoT systems, ensuring smooth and efficient operations. View the full article

Today, we’re announcing the general availability of extended industrial protocol support for AWS IoT SiteWise. Through a new integration with AWS Partner Domatica, customers can now ingest data from 10 additional industrial protocols including Modbus (TCP & RTU), Ethernet/IP, Siemens S7, KNX, LoRaWAN, MQTT, Profinet, Profibus BACnet, and Rest interfaces, in addition to native OPC UA support. Previously, ingesting data from these protocols required acquiring, provisioning, and configuring infrastructure and middleware for data collection resulting in additional cost and time to value. View the full article

In the rapidly evolving landscape of the Internet of Things (IoT), achieving seamless interoperability among a myriad of devices and systems is paramount. To tackle this challenge head-on, software-based architectures are emerging as powerful solutions. In this article, we explore the synergy between software-based architecture and the development of interoperability solutions for IoT to provide insights relevant to software developers and data engineers... View the full article

Today, AWS IoT Core for LoRaWAN announces the general availability of public network support for LoRaWAN-based Internet of Things (IoT) devices. With this update, you can now connect your LoRaWAN devices to the cloud using publicly available LoRaWAN networks provided by Everynet, a LoRaWAN network operator, without deploying and operating a private LoRaWAN network. The public LoRaWAN network is provided as a service and operated by Everynet, and by adding this public network support, customers can choose from within the AWS console to use Everynet's network. View the full article

Internet-of-things (IoT) is a term used to describe the network of physical devices—from everyday household items to sophisticated industrial tools—connected to the internet, sharing and collecting data. With the advent of cheap computer chips and the ubiquity of wireless networks, it’s possible to make anything a part of the IoT. Add to that the exponential […] View the full article

AWS IoT Core announces General Availability of the capability to send device logs from Internet of Things (IoT) devices to Amazon CloudWatch Logs in batches, enabling you to optimize the cost of using CloudWatch Log Action in IoT Rules. View the full article

Starting today, AWS IoT TwinMaker will support asset synchronization with AWS IoT SiteWise, making it easier for AWS IoT SiteWise customers to bring their assets and asset models into AWS IoT TwinMaker. View the full article

Welcome to the August edition of the monthly State of IoT series. Let’s dive straight into the most prominent news across the IoT landscape from the last month. Google kills Cloud IoT Core Google introduced Cloud IoT Core, a fully managed service for securely connecting and managing devices, at the Google I/O conference in May 2017. In September of that year, Google revealed the public availability of the solution to all users in beta. Cloud IoT Core fell short of its ambition to make enterprise IoT app development easy. This month, Google decided to kill the project. “Google Cloud IoT Core is being retired on August 16, 2023. Contact your Google Cloud account team for more information”, reads the only public statement on Google Cloud’s web page. According to a Hackernews post, the Google Cloud IoT Core Product Team shared an email to existing users, clarifying their access to the IoT Core Device Manager APIs will no longer be available after August 16, 2023. As of that date, devices will be unable to connect to the Google Cloud IoT Core MQTT and HTTP bridges, and Google Cloud will shut down existing connections. Before being shut down by Google, Cloud IoT Core promised to build and train ML models for IoT devices in the cloud Google hasn’t been shy about retiring products from the IoT landscape. In 2015, Google introduced Brillo, an IoT OS allegedly capable of running on 32MB RAM at Google I/O. After renaming Brillo to Android Things the following year, Google released the first non-preview version of Android Things 1.0, promising three years of updates for every device. In 2019, Google decided to ‘refocus’ Android Things for OEMs building speakers and displays, giving up on its vision as a general-purpose OS for IoT devices. A couple of years later, Google killed Android Things. It’s not uncommon to see projects come and go in the fast-moving world of IoT. Luckily there are some options for Google Cloud IoT Core users. You can learn more about how to build and deploy a central IoT management solution in our Secure IoT Device Management whitepaper. Privacy concerns over Amazon’s acquisition of iRobot iRobot is known for introducing the Roomba, one of the best-selling robot vacuums on Amazon, in 2002. Last month, Amazon and iRobot signed a definitive merger agreement under which Amazon will acquire the makers of the Roomba vacuum. A team of MIT roboticists co-founded iRobot in 1990 and unveiled their first product, Genghis, a robot designed for space exploration, a year later. After pivoting toward detecting and eliminating mines in surf zones with Ariel, iRobot won the DARPA contract to build a tactical mobile robot in 1998. The contract led to the development of the PackBot and its deployment at the World Trade Center in September 2001. From innovative robots for military and rescue operations, iRobot went through quite a journey to ship what is now one of the most popular household appliances. iRobot reached product-market fit with the launch of the Roomba floor vacuuming robot in 2002. Since then, iRobot bolstered its product lines with a series of launches, including the Scooba for floor washing, the Dirt Dog for shop sweeping and the Verro pool cleaning robot. To this day, the award-winning Roomba series of vacuum cleaning robots remains their most profitable achievement. “We believe humans have more fulfilling things to do than cleaning. iRobot, so you can human” reads the Roomba’s maker slogan With the latest acquisition, Amazon keeps expanding its home technology portfolio after acquiring video doorbell firm Ring and text-to-speech technology company IVONA Software, key for developing what is now Amazon Alexa. Amazon’s access to consumer data raised several concerns regarding collecting and processing personal information for the millions of worldwide Roomba users. In response, Colin Angle, iRobot’s CEO and one of the MIT technologists who founded the company more than two decades ago, emphasised protecting customer data and privacy is of the utmost importance for iRobot. In a statement, the CEO reassured its customers that iRobot does not and will not sell their personal information. Ubuntu runs out-of-the-box on RISC-V boards In the past decade, open-source software and open standards have reshaped the world of technology and produced long-lasting results. The time is now ripe for Open Hardware to Meet Open Software. RISC-V is a new paradigm for Open Source hardware, developing a free and open Instruction Set Architecture (ISA). The ISA holds the promise of increasingly rapid processor innovation through open standard collaboration. Thanks to its availability on a wide range of processors, from low-end microcontrollers to high-end server-grade processors, RISC-V is poised to empower a new era of processor innovation with rapid industry-wide adoption. Combining the best open-source architecture with the best open-source operating system, porting Ubuntu on RISC-V further facilitates the adoption of novel computing architectures. According to StarFive, VisionFive is the world’s first generation of affordable RISC-V boards designed to run Linux As part of a vibrant ecosystem driving innovation at the edge, Canonical and its IoT technology partners work together to promote the deployment of high-performance devices. Within a few days, Canonical announced it enabled Ubuntu on Allwinner’s Nezha RISC-V and StarFive’s VisionFive board. As Ubuntu and open-source software are already accelerating the adoption of IoT innovations, support for the RISC-V ISA reflects Canonical’s commitment to continued investments in open standards and collaboration. VisionFive 2: a RISC-V alternative to the Pi? Another great release will please those wishing to see the rise of RISC-V as a dominant ISA alongside x86 and ARM. Just a few days after Canonical announced it enabled Ubuntu on the VisionFive board, StarFive released its VisionFive 2 single-board computer (SBC). StarFive made significant strides to feature a wide range of interfaces with powerful performance. The VisionFive 2 is a pioneering board that combines performance with a low-cost, open-source RISC-V SBC. The board is significantly more powerful than its previous iteration, with more than double the performance per watt. The VisionFive 2 boasts a JH7110 quad-core CPU running at 1.5 GHz, up from 1.0 GHz in the JH7100. Compared to the original VisionFive, it further integrates the Imagination Technologies IMG BXE GPU, supporting OpenGL, OpenCL and Vulkan. The latest SBC by StarFive drops onboard Wi-Fi and Bluetooth in favour of an M.2 M-key expansion module. Also, the newest version of the VisionFive series adds a 4-lane MIPI DSI display port that supports up to 2K at 30FPS, whereas the HDMI port now supports 4K up to 30FPS. The VisionFive 2 development board supports a wide range of peripherals designed for mainstream SBCs Priced at $55 for its 2GB model and $85 for the 8GB model, the VisionFive 2 is a great entry into the RISC-V computing ecosystem. RISC-V isn’t at Raspberry Pi prices yet, but it’s now at parity with non-Pi ARM boards. By releasing its second generation of the first cost-effective Linux-based RISC-V SBC, StarFive will help usher in a new era of open-source hardware and software computing. The company also launched a Kickstarter campaign to fund the board’s production. Bosch to build digital twin of manufacturing plant Bosch aims to create a digital twin of the machinery and process flow at one of its plants in Madrid. To accelerate the digitisation of its industrial facilities and work on the simulation, Bosch is partnering with Multiverse Computing. Open collaboration to further industrial automation is not new. Just last month, Siemens and NVIDIA revealed their joint work on advancing digital twins for manufacturing. By connecting the NVIDIA Omniverse and the Siemens Xcelerator ecosystem, the two companies aim to expand the use of digital twin technologies to bring a new level of speed and efficiency to solve design, production and operational challenges. The partnership will help manufacturers respond to customer demands, reduce downtime and adapt to supply chain uncertainties while achieving sustainability and production targets. Bosch plans to build an industrial factory digital twin using quantum algorithms The announcement is interesting because Multiverse Computing will work with Bosch on creating a quantum computing model for Madrid’s manufacturing facility. Multiverse Computing works on developing quantum-inspired algorithms deployed on supercomputers and quantum hardware. Bosch aims to enhance quality control and production efficiencies by bringing quantum computing into Madrid’s manufacturing facility. Whereas the industrial pioneer’s current digitisation efforts in 240 plants resulted in 120,000 connected machines and more than 250,000 devices, it remains to be seen whether quantum technologies are mature enough to bring substantive benefits to industrial computing. Stay tuned for more IoT news We will soon be back with next month’s summary of IoT news. Meanwhile, join the conversation on IoT Discourse to discuss everything related to IoT and tightly connected, embedded devices. Further reading Why is Linux the OS of choice for IoT devices? Find out with the official guide to Linux for embedded applications. Choosing a distribution for your IoT device: Yocto or Ubuntu Core? Learn about the trade-offs between a community-maintained built system and a commercial-grade distribution in our webinar. Discover how open standards and interfaces are accelerating the world’s move towards Industry 4.0 in our upcoming webinar on IT/OT convergence. View the full article

The AWS IoT Device Client is a free, open-source, and modular device-side reference implementation written in C++ that you can compile and install on IoT devices. It allows device developers to access AWS IoT Core, AWS IoT Device Management, and AWS IoT Device Defender features with minimal device side code. The Device Client works on devices with common microprocessors (x86_64 and ARM architectures), and common Embedded Linux software environments (e.g. Debian, Ubuntu, and RHEL). View the full article

AWS IoT Device Management Fleet Indexing now provides integration with two additional data sources, AWS IoT Core named shadows and AWS IoT Device Defender detect violations. Customers can now select specific named shadows to index only the data that is required for search queries. Also, detected violations can be indexed to target devices for troubleshooting or monitor the fleet-level anomalies trends with Fleet Metrics. These two additional data sources will help IoT customers who store IoT fleet data across different services and systems and regularly access the data for fleet monitoring, health checks, over-the-air (OTA) updates, and troubleshooting. With this release, supported data sources for Fleet Indexing increased to 5 from 3 (AWS IoT Core registry, shadows, and connectivity lifecycle events). View the full article

Today, AWS announced the general availability of a new feature of AWS IoT Core that simplifies the registration of certificate authorities (CAs) necessary for device provisioning and makes it easier to move devices between customers' multiple AWS accounts within the same AWS region and between different regions. This reduces the complexity of registering devices to AWS IoT Core and helps customers accelerate the development lifecycle for their IoT implementations when using AWS IoT Core Just-in-Time Provisioning (JITP) and Just-in-Time Registration (JITR) device provisioning methods of AWS IoT Core. View the full article

AWS IoT Greengrass is an Internet of Things (IoT) edge runtime and cloud service that helps customers build, deploy, and manage device software. We are excited to announce our version 2.6 release, which adds edge support for MQTT version 5, an updated device-to-device communication specification that includes many additional feature improvements over the MQTT version 3.1.1 protocol. View the full article