Ovidiu Vermesan – författare

The book''s aim is to define the Internet of Things (IoT) in a global view, present the research agenda for Internet of Things technologies by addressing the new technological developments and providing a global balanced coverage of the challenges and the technical and industrial trends.Energy consumption by the data, communication and networking devices and global CO2 emission is increasing exponentially. ICT has a dual role in this process: it accounts for about two percent of global CO2 emissions and at the same the ICT including IoT technologies and applications have a direct effect on lowering CO2 emissions, increasing energy efficiency, reducing power consumption, and achieving efficient waste recycling.The book builds on the ideas put forward by the European research Cluster on the Internet of Things Strategic Research Agenda and presents global views and state of the art results on the challenges facing the research, development and deployment of IoT at the global level.IoT together with the other emerging Internet developments such as Internet of Energy, Media, People, Services, Business/Enterprises are the backbone of the digital economy, the digital society and the foundation for the future knowledge based economy and innovation society. IoT developments show that we will have 16 billion connected devices by the year 2020 , which will average out to six devices per person on earth and to many more per person in digital societies.Devices like smart phones and machine to machine or thing to thing communication will be the main drivers for further IoT development.

The book aims to provide a broad overview of various topics of the Internet of Things (IoT) from the research and development priorities to enabling technologies, architecture, security, privacy, interoperability and industrial applications. It is intended to be a standalone book in a series that covers the Internet of Things activities of the IERC ? Internet of Things European Research Cluster from technology to international cooperation and the global state of play. The book builds on the ideas put forward by the European research Cluster on the Internet of Things Strategic Research Agenda and presents global views and state of the art results on the challenges facing the research, development and deployment of IoT at the global level.Today we see the integration of Industrial, Business and Consumer Internet which is bringing together the Internet of People, Internet of Things, Internet of Energy, Internet of Vehicles, Internet of Media, Services and Enterprises in forming the backbone of the digital economy, the digital society and the foundation for the future knowledge and innovation based economy in supporting solutions for the emerging challenges of public health, aging population, environmental protection and climate change, the conservation of energy and scarce materials, enhancements to safety and security and the continuation and growth of economic prosperity.Penetration of smartphones and advances in machine to machine and wireless communication technology will be the main drivers for IoT development. The IoT contribution is in the increased value of information created by the number of interconnections among things and the transformation of the processed information into knowledge shared into the Internet of Everything.

The book''s aim is to define the Internet of Things (IoT) in a global view, present the research agenda for Internet of Things technologies by addressing the new technological developments and providing a global balanced coverage of the challenges and the technical and industrial trends.Energy consumption by the data, communication and networking devices and global CO2 emission is increasing exponentially. ICT has a dual role in this process: it accounts for about two percent of global CO2 emissions and at the same the ICT including IoT technologies and applications have a direct effect on lowering CO2 emissions, increasing energy efficiency, reducing power consumption, and achieving efficient waste recycling.The book builds on the ideas put forward by the European research Cluster on the Internet of Things Strategic Research Agenda and presents global views and state of the art results on the challenges facing the research, development and deployment of IoT at the global level.IoT together with the other emerging Internet developments such as Internet of Energy, Media, People, Services, Business/Enterprises are the backbone of the digital economy, the digital society and the foundation for the future knowledge based economy and innovation society. IoT developments show that we will have 16 billion connected devices by the year 2020 , which will average out to six devices per person on earth and to many more per person in digital societies.Devices like smart phones and machine to machine or thing to thing communication will be the main drivers for further IoT development.

The book aims to provide a broad overview of various topics of the Internet of Things (IoT) from the research and development priorities to enabling technologies, architecture, security, privacy, interoperability and industrial applications. It is intended to be a standalone book in a series that covers the Internet of Things activities of the IERC ? Internet of Things European Research Cluster from technology to international cooperation and the global state of play. The book builds on the ideas put forward by the European research Cluster on the Internet of Things Strategic Research Agenda and presents global views and state of the art results on the challenges facing the research, development and deployment of IoT at the global level.Today we see the integration of Industrial, Business and Consumer Internet which is bringing together the Internet of People, Internet of Things, Internet of Energy, Internet of Vehicles, Internet of Media, Services and Enterprises in forming the backbone of the digital economy, the digital society and the foundation for the future knowledge and innovation based economy in supporting solutions for the emerging challenges of public health, aging population, environmental protection and climate change, the conservation of energy and scarce materials, enhancements to safety and security and the continuation and growth of economic prosperity.Penetration of smartphones and advances in machine to machine and wireless communication technology will be the main drivers for IoT development. The IoT contribution is in the increased value of information created by the number of interconnections among things and the transformation of the processed information into knowledge shared into the Internet of Everything.

Welcome to the cutting edge of innovation, where intelligent processing is migrating to every device that interacts with the physical world. The convergence of edge computing, artificial intelligence (AI), and the Internet of Things (IoT) drives a shift in the computing continuum, giving rise to the dynamic and transformative field of edge AI.This book, a curated collection of research work presented at the European Conference on EDGE AI Technologies and Applications (EEAI), serves as both a ledger and a beacon for this exciting new era of edge intelligence-driven technologies.The EEAI stands as a vital European forum, bringing together interested minds from academia and industry to explore the entire edge AI technology stack. From silicon circuits, AI accelerators, and specialised hardware platforms to the complexities of advanced algorithms and the architecture of next-generation edge AI systems, the conference fosters a vibrant exchange of ideas that propel the field of edge AI forward.The research presented in these pages captures the spirit of that collaboration, offering a panoramic view of the challenges being addressed and the groundbreaking solutions being developed.The book is more than a collection of papers, it is a synopsis presenting the real-world impact of edge AI. It moves beyond theoretical discussions to showcase how these technologies are being applied to solve some of the most pressing challenges. The chapters of the book navigate from the complex urban landscapes of last-mile delivery to the fertile fields of smart agriculture, discovering how intelligent systems are creating new efficiencies, enhancing security, and redefining what is possible at the network's edge.We invite you to immerse yourself in these chapters, not just as a reader but as a participant in the ongoing dialogue that is shaping the future of edge intelligence. Whether you are a curious and creative researcher, an innovative engineer, or a student eager to understand the next wave of edge AI processing, the insights shared here provide a comprehensive and deep understanding of the technologies and applications that are bringing intelligence to the edge.The Open Access version of this book, available at http://www.taylorfrancis.com, has been made available under a Creative Commons Attribution-NonCommercial (CC BY-NC) 4.0 license.

We are witnessing a fundamental shift in the computing landscape, a paradigm shift where intelligence is rapidly migrating to the very edges of the network. This is the era of edge AI, which embeds decision-making, perception, and control directly into devices that shape our physical world. This book is a selected collection of the presented work from the European Conference on EDGE AI Technologies and Applications (EEAI) held on 21–23 October 2024 in Cagliari, Sardinia, Italy.The conference is part of a series of annual conferences that delve into the expanding continuum of micro-, deep-, and meta-edge architectures, which form the backbone of emerging intelligent autonomous systems across numerous sectors. From the complexities of advanced algorithms and the design of novel edge AI hardware accelerators to the architecture of next-generation communication networks, AI frameworks and software systems, the EEAI fosters a vibrant exchange of ideas that are following the future and actively defining it. From industrial automation to environmental monitoring, from manufacturing to smart mobility, the expansion of micro-, deep-, and meta-edge AI processing is propelling a new class of autonomous systems. These systems thrive on distributed intelligence, leveraging advancements in edge AI hardware architectures, accelerators, performant algorithms, and advanced software frameworks. The chapters in this volume celebrate this paradigm shift and offer a glimpse into the vibrant ecosystem shaping the future of edge AI technologies and applications. The numerous chapters describe novel solutions and rigorous investigations spanning verification and validation, federated learning, neuromorphic design, scalable architectures, sensor fusion, and human–machine collaboration, each chapter demonstrating the innovation wave fuelling Europe's edge AI landscape.Together, these twenty chapters provide a rich, multi-layered, and deeply insightful perspective on the state of edge AI. Each chapter documents the achievements made and highlights the path forward, offering a compelling vision of a future where intelligence is seamlessly and securely integrated into the fabric of the real world. This book is an essential guide for navigating, understanding, and contributing to the dynamic and rapidly evolving field of edge AI.The real value of this book lies in its innovative, forward-looking perspective, offering a guided exploration of the latest scientific breakthroughs and practical advancements shaping intelligent systems at the edge. For researchers, students, practitioners, and visionaries, this book provides a comprehensive roadmap for the next stage in the evolution of intelligent, connected systems at the edge.

We are witnessing a fundamental shift in the computing landscape, a paradigm shift where intelligence is rapidly migrating to the very edges of the network. This is the era of edge AI, which embeds decision-making, perception, and control directly into devices that shape our physical world. This book is a selected collection of the presented work from the European Conference on EDGE AI Technologies and Applications (EEAI) held on 21-23 October 2024 in Cagliari, Sardinia, Italy.The conference is part of a series of annual conferences that delve into the expanding continuum of micro-, deep-, and meta-edge architectures, which form the backbone of emerging intelligent autonomous systems across numerous sectors. From the complexities of advanced algorithms and the design of novel edge AI hardware accelerators to the architecture of next-generation communication networks, AI frameworks and software systems, the EEAI fosters a vibrant exchange of ideas that are following the future and actively defining it. From industrial automation to environmental monitoring, from manufacturing to smart mobility, the expansion of micro-, deep-, and meta-edge AI processing is propelling a new class of autonomous systems. These systems thrive on distributed intelligence, leveraging advancements in edge AI hardware architectures, accelerators, performant algorithms, and advanced software frameworks. The chapters in this volume celebrate this paradigm shift and offer a glimpse into the vibrant ecosystem shaping the future of edge AI technologies and applications. The numerous chapters describe novel solutions and rigorous investigations spanning verification and validation, federated learning, neuromorphic design, scalable architectures, sensor fusion, and human-machine collaboration, each chapter demonstrating the innovation wave fuelling Europe's edge AI landscape.Together, these twenty chapters provide a rich, multi-layered, and deeply insightful perspective on the state of edge AI. Each chapter documents the achievements made and highlights the path forward, offering a compelling vision of a future where intelligence is seamlessly and securely integrated into the fabric of the real world. This book is an essential guide for navigating, understanding, and contributing to the dynamic and rapidly evolving field of edge AI.The real value of this book lies in its innovative, forward-looking perspective, offering a guided exploration of the latest scientific breakthroughs and practical advancements shaping intelligent systems at the edge. For researchers, students, practitioners, and visionaries, this book provides a comprehensive roadmap for the next stage in the evolution of intelligent, connected systems at the edge.

We are witnessing a fundamental shift in the computing landscape, a paradigm shift where intelligence is rapidly migrating to the very edges of the network. This is the era of edge AI, which embeds decision-making, perception, and control directly into devices that shape our physical world. This book is a selected collection of the presented work from the European Conference on EDGE AI Technologies and Applications (EEAI) held on 21-23 October 2024 in Cagliari, Sardinia, Italy.The conference is part of a series of annual conferences that delve into the expanding continuum of micro-, deep-, and meta-edge architectures, which form the backbone of emerging intelligent autonomous systems across numerous sectors. From the complexities of advanced algorithms and the design of novel edge AI hardware accelerators to the architecture of next-generation communication networks, AI frameworks and software systems, the EEAI fosters a vibrant exchange of ideas that are following the future and actively defining it. From industrial automation to environmental monitoring, from manufacturing to smart mobility, the expansion of micro-, deep-, and meta-edge AI processing is propelling a new class of autonomous systems. These systems thrive on distributed intelligence, leveraging advancements in edge AI hardware architectures, accelerators, performant algorithms, and advanced software frameworks. The chapters in this volume celebrate this paradigm shift and offer a glimpse into the vibrant ecosystem shaping the future of edge AI technologies and applications. The numerous chapters describe novel solutions and rigorous investigations spanning verification and validation, federated learning, neuromorphic design, scalable architectures, sensor fusion, and human-machine collaboration, each chapter demonstrating the innovation wave fuelling Europe's edge AI landscape.Together, these twenty chapters provide a rich, multi-layered, and deeply insightful perspective on the state of edge AI. Each chapter documents the achievements made and highlights the path forward, offering a compelling vision of a future where intelligence is seamlessly and securely integrated into the fabric of the real world. This book is an essential guide for navigating, understanding, and contributing to the dynamic and rapidly evolving field of edge AI.The real value of this book lies in its innovative, forward-looking perspective, offering a guided exploration of the latest scientific breakthroughs and practical advancements shaping intelligent systems at the edge. For researchers, students, practitioners, and visionaries, this book provides a comprehensive roadmap for the next stage in the evolution of intelligent, connected systems at the edge.

This book presents a comprehensive exploration of the functional and non-functional requirements that define edge AI systems, including technical, ethical, legal, and regulatory dimensions. It offers a holistic perspective that spans hardware, software, the AI technology stack, and the data pipelines supporting applications across the micro-, deep-, and meta-edge continuum.Edge AI systems are evaluated through their key properties—functionality, performance, cost, dependability, and trustworthiness. The book closely interlinks these requirements with the concepts of system dependability and trust. Dependability is presented as the backbone of real-time edge AI performance, where services must be delivered reliably within strict timeframes. Trustworthiness is defined as the system’s ability to meet both functional and non-functional requirements in a verifiable manner—ensuring transparency, correctness, and alignment with human oversight.The chapters emphasize how building trust in edge AI is not merely a technical task, but a collaborative process across technical, ethical, and legal/regulatory domains. Establishing trustworthiness requires the careful definition of requirements, measurement of key performance indicators (KPIs), continuous monitoring, transparent processes, and alignment with broader societal values.Written for researchers, engineers, and students eager to understand the next frontier of edge intelligence, the book invites readers to engage with cutting-edge discussions on performance, accountability, and responsibility in AI at the edge. It is both an academic resource and a practical guide for those seeking to design, validate, and deploy edge AI systems that are not only high-performing but also dependable, trustworthy, and socially aligned.

This book presents a comprehensive exploration of the functional and non-functional requirements that define edge AI systems, including technical, ethical, legal, and regulatory dimensions. It offers a holistic perspective that spans hardware, software, the AI technology stack, and the data pipelines supporting applications across the micro-, deep-, and meta-edge continuum. Edge AI systems are evaluated through their key properties-functionality, performance, cost, dependability, and trustworthiness. The book closely interlinks these requirements with the concepts of system dependability and trust. Dependability is presented as the backbone of real-time edge AI performance, where services must be delivered reliably within strict timeframes. Trustworthiness is defined as the system's ability to meet both functional and non-functional requirements in a verifiable manner-ensuring transparency, correctness, and alignment with human oversight. The chapters emphasize how building trust in edge AI is not merely a technical task, but a collaborative process across technical, ethical, and legal/regulatory domains. Establishing trustworthiness requires the careful definition of requirements, measurement of key performance indicators (KPIs), continuous monitoring, transparent processes, and alignment with broader societal values. Written for researchers, engineers, and students eager to understand the next frontier of edge intelligence, the book invites readers to engage with cutting-edge discussions on performance, accountability, and responsibility in AI at the edge. It is both an academic resource and a practical guide for those seeking to design, validate, and deploy edge AI systems that are not only high-performing but also dependable, trustworthy, and socially aligned.

This book presents a comprehensive exploration of the functional and non-functional requirements that define edge AI systems, including technical, ethical, legal, and regulatory dimensions. It offers a holistic perspective that spans hardware, software, the AI technology stack, and the data pipelines supporting applications across the micro-, deep-, and meta-edge continuum. Edge AI systems are evaluated through their key properties-functionality, performance, cost, dependability, and trustworthiness. The book closely interlinks these requirements with the concepts of system dependability and trust. Dependability is presented as the backbone of real-time edge AI performance, where services must be delivered reliably within strict timeframes. Trustworthiness is defined as the system's ability to meet both functional and non-functional requirements in a verifiable manner-ensuring transparency, correctness, and alignment with human oversight. The chapters emphasize how building trust in edge AI is not merely a technical task, but a collaborative process across technical, ethical, and legal/regulatory domains. Establishing trustworthiness requires the careful definition of requirements, measurement of key performance indicators (KPIs), continuous monitoring, transparent processes, and alignment with broader societal values. Written for researchers, engineers, and students eager to understand the next frontier of edge intelligence, the book invites readers to engage with cutting-edge discussions on performance, accountability, and responsibility in AI at the edge. It is both an academic resource and a practical guide for those seeking to design, validate, and deploy edge AI systems that are not only high-performing but also dependable, trustworthy, and socially aligned.

Artificial intelligence is rapidly moving beyond centralized cloud computing into distributed edge environments, creating a new generation of intelligent systems that are autonomous, adaptive, efficient, and sustainable. Pervasive Intelligence: From Architectures to Sustainable Edge AI Systems-of-Systems explores the technologies, architectures, and engineering methodologies driving this transformation.Written by leading researchers and industry experts, the book provides a comprehensive examination of edge AI, covering topics such as embedded AI acceleration, active inference agents, hardware-software co-design, distributed orchestration, privacy-preserving intelligence, and sustainable computing. It bridges theory and practice by addressing key deployment challenges, including real-time speech enhancement, neural network optimization for embedded devices, AI benchmarking on ARM processors, FPGA-based acceleration, and trustworthy AI systems operating at the edge.A recurring theme is the emergence of edge AI systems-of-systems, in which intelligent agents, sensors, devices, and computing resources collaborate seamlessly across the edge-to-cloud continuum. The book highlights the importance of interoperability, resilience, trustworthiness, adaptive autonomy, and energy efficiency in building next-generation intelligent infrastructures.Drawing on practical applications in robotics, autonomous systems, surveillance, smart agriculture, environmental forecasting, and cyber-physical systems, the contributors demonstrate how pervasive intelligence is transforming industries and enabling more responsive, data-driven decision-making. By combining advances in artificial intelligence with systems engineering, control theory, and physics-informed modeling, this volume offers both a strategic vision and a technical framework for the future of sustainable edge intelligence.An essential resource for researchers, engineers, system architects, and advanced students, this book provides the knowledge and tools needed to design, deploy, and manage intelligent systems operating at the edge.

The intersection of AI, the Internet of Things (IoT) and edge computing has kindled the edge AI revolution that promises to redefine how we perceive and interact with the physical world through intelligent devices. Edge AI moves intelligence from the network centre to the devices at its edge, entrusting these endpoints to analyse data locally, make decisions, and provide real-time responses.Recent advances in power-efficient high-performance embedded silicon make edge AI a viable proposition, albeit one requiring new distributed architectures and novel design concepts. Moving decision-making closer to the edge makes responses faster and systems more reliable, while the constant pressure to reduce network bandwidth demand and the need to contain spiralling data storage and operations costs help justify the engineering investment necessary to embrace this new paradigm. Moving to decentralised operation opens the door to a multitude of novel applications, covering immersive technologies and autonomous systems across fields as diverse as healthcare and industrial automation, personal assistance and prognostics, surgery, and process control. In the best tradition of systems engineering, the first stage of this transition process is understanding the application domain for edge AI deployment, the ""system context"".This book presents some key topics and early thinking from the EdgeAI* project, covering data backhaul technologies, lifecycle management, mechanisms for developing AIs at the edge and techniques for interacting with those AIs. It provides examples of application domains before concluding with a review of how edge AI systems can be understood by their users. It also examines and presents new results based on current investigations and activities in edge AI technologies, considering the future trends in autonomic systems, hyperautomation, AI engineering, generative AI, connectivity, and cybersecurity mesh.This book aims to empower the reader with the knowledge and insights needed to understand and embrace the transformative power of edge AI technology. The extensively referenced chapters, contributed by experts and thought leaders in the field, are recommended to anyone interested in developing edge AI systems.*Edge AI Technologies for Optimised Performance Embedded Processing" (EdgeAI) Key Digital Technologies (KDT) Joint Undertaking (JU) European research project. https://https://edge-ai-tech.eu/

This book provides in-depth insights into use cases implementing artificial intelligence (AI) applications at the edge. It covers new ideas, concepts, research, and innovation to enable the development and deployment of AI, the industrial internet of things (IIoT), edge computing, and digital twin technologies in industrial environments. The work is based on the research results and activities of the AI4DI project, including an overview of industrial use cases, research, technological innovation, validation, and deployment.This book’s sections build on the research, development, and innovative ideas elaborated for applications in five industries: automotive, semiconductor, industrial machinery, food and beverage, and transportation.The articles included under each of these five industrial sectors discuss AI-based methods, techniques, models, algorithms, and supporting technologies, such as IIoT, edge computing, digital twins, collaborative robots, silicon-born AI circuit concepts, neuromorphic architectures, and augmented intelligence, that are anticipating the development of Industry 5.0. Automotive applications cover use cases addressing AI-based solutions for inbound logistics and assembly process optimisation, autonomous reconfigurable battery systems, virtual AI training platforms for robot learning, autonomous mobile robotic agents, and predictive maintenance for machines on the level of a digital twin.AI-based technologies and applications in the semiconductor manufacturing industry address use cases related to AI-based failure modes and effects analysis assistants, neural networks for predicting critical 3D dimensions in MEMS inertial sensors, machine vision systems developed in the wafer inspection production line, semiconductor wafer fault classifications, automatic inspection of scanning electron microscope cross-section images for technology verification, anomaly detection on wire bond process trace data, and optical inspection.The use cases presented for machinery and industrial equipment industry applications cover topics related to wood machinery, with the perception of the surrounding environment and intelligent robot applications. AI, IIoT, and robotics solutions are highlighted for the food and beverage industry, presenting use cases addressing novel AI-based environmental monitoring; autonomous environment-aware, quality control systems for Champagne production; and production process optimisation and predictive maintenance for soybeans manufacturing. For the transportation sector, the use cases presented cover the mobility-as-a-service development of AI-based fleet management for supporting multimodal transport.This book highlights the significant technological challenges that AI application developments in industrial sectors are facing, presenting several research challenges and open issues that should guide future development for evolution towards an environment-friendly Industry 5.0. The challenges presented for AI-based applications in industrial environments include issues related to complexity, multidisciplinary and heterogeneity, convergence of AI with other technologies, energy consumption and efficiency, knowledge acquisition, reasoning with limited data, fusion of heterogeneous data, availability of reliable data sets, verification, validation, and testing for decision-making processes.

This book provides an overview of the next generation Internet of Things (IoT), ranging from research, innovation, development priorities, to enabling technologies in a global context. It is intended as a standalone in a series covering the activities of the Internet of Things European Research Cluster (IERC), including research, technological innovation, validation, and deployment.The following chapters build on the ideas put forward by the European Research Cluster, the IoT European Platform Initiative (IoT–EPI), the IoT European Large-Scale Pilots Programme and the IoT European Security and Privacy Projects, presenting global views and state-of-the-art results regarding the next generation of IoT research, innovation, development, and deployment.The IoT and Industrial Internet of Things (IIoT) are evolving towards the next generation of Tactile IoT/IIoT, bringing together hyperconnectivity (5G and beyond), edge computing, Distributed Ledger Technologies (DLTs), virtual/ andaugmented reality (VR/AR), and artificial intelligence (AI) transformation.Following the wider adoption of consumer IoT, the next generation of IoT/IIoT innovation for business is driven by industries, addressing interoperability issues and providing new end-to-end security solutions to face continuous treats.The advances of AI technology in vision, speech recognition, natural language processing and dialog are enabling the development of end-to-end intelligent systems encapsulating multiple technologies, delivering services in real-time using limited resources. These developments are focusing on designing and delivering embedded and hierarchical AI solutions in IoT/IIoT, edge computing, using distributed architectures, DLTs platforms and distributed end-to-end security, which provide real-time decisions using less data and computational resources, while accessing each type of resource in a way that enhances the accuracy and performance of models in the various IoT/IIoT applications.The convergence and combination of IoT, AI and other related technologies to derive insights, decisions and revenue from sensor data provide new business models and sources of monetization. Meanwhile, scalable, IoT-enabled applications have become part of larger business objectives, enabling digital transformation with a focus on new services and applications.Serving the next generation of Tactile IoT/IIoT real-time use cases over 5G and Network Slicing technology is essential for consumer and industrial applications and support reducing operational costs, increasing efficiency and leveraging additional capabilities for real-time autonomous systems.New IoT distributed architectures, combined with system-level architectures for edge/fog computing, are evolving IoT platforms, including AI and DLTs, with embedded intelligence into the hyperconnectivity infrastructure.The next generation of IoT/IIoT technologies are highly transformational, enabling innovation at scale, and autonomous decision-making in various application domains such as healthcare, smart homes, smart buildings, smart cities, energy, agriculture, transportation and autonomous vehicles, the military, logistics and supply chain, retail and wholesale, manufacturing, mining and oil and gas.

The IoT European Platforms Initiative (IoT-EPI) projects are addressing the topic of Internet of Things and Platforms for Connected Smart Objects and aim to deliver an IoT extended into a web of platforms for connected devices and objects that supports smart environments, businesses, services and persons with dynamic and adaptive configuration capabilities. The specific areas of focus of the research activities are architectures and semantic interoperability, which reliably cover multiple use cases. The goal is to deliver dynamically-configured infrastructure and integration platforms for connected smart objects covering multiple technologies and multiple intelligent artefacts. The IoT-EPI ecosystem has been created with the objective of increasing the impact of the IoT-related European research and innovation, including seven European promising projects on IoT platforms: AGILE, BIG IoT, INTER-IoT, VICINITY, SymbIoTe, bIoTope, and TagItSmart.This white paper provides an insight regarding interoperability in the IoT platforms and ecosystems created and used by IoT-EPI. The scope of this document covers the interoperability aspects, challenges and approaches that cope with interoperability in the current existing IoT platforms and presents some insights regarding the future of interoperability in this context. It presents possible solutions, and a possible IoT interoperability platform architecture.

This book provides an overview of the current Internet of Things (IoT) landscape, ranging from the research, innovation and development priorities to enabling technologies in a global context. A successful deployment of IoT technologies requires integration on all layers, be it cognitive and semantic aspects, middleware components, services, edge devices/machines and infrastructures. It is intended to be a standalone book in a series that covers the Internet of Things activities of the IERC - Internet of Things European Research Cluster from research to technological innovation, validation and deployment. The book builds on the ideas put forward by the European Research Cluster and the IoT European Platform Initiative (IoT-EPI) and presents global views and state of the art results on the challenges facing the research, innovation, development and deployment of IoT in the next years. The IoT is bridging the physical world with virtual world and requires sound information processing capabilities for the "digital shadows" of these real things. The research and innovation in nanoelectronics, semiconductor, sensors/actuators, communication, analytics technologies, cyber-physical systems, software, swarm intelligent and deep learning systems are essential for the successful deployment of IoT applications. The emergence of IoT platforms with multiple functionalities enables rapid development and lower costs by offering standardised components that can be shared across multiple solutions in many industry verticals. The IoT applications will gradually move from vertical, single purpose solutions to multi-purpose and collaborative applications interacting across industry verticals, organisations and people, being one of the essential paradigms of the digital economy. Many of those applications still have to be identified and involvement of end-users including the creative sector in this innovation is crucial. The IoT applications and deployments as integrated building blocks of the new digital economy are part of the accompanying IoT policy framework to address issues of horizontal nature and common interest (i.e. privacy, end-to-end security, user acceptance, societal, ethical aspects and legal issues) for providing trusted IoT solutions in a coordinated and consolidated manner across the IoT activities and pilots. In this, context IoT ecosystems offer solutions beyond a platform and solve important technical challenges in the different verticals and across verticals. These IoT technology ecosystems are instrumental for the deployment of large pilots and can easily be connected to or build upon the core IoT solutions for different applications in order to expand the system of use and allow new and even unanticipated IoT end uses. Technical topics discussed in the book include: • Introduction• Digitising industry and IoT as key enabler in the new era of Digital Economy• IoT Strategic Research and Innovation Agenda• IoT in the digital industrial context: Digital Single Market• Integration of heterogeneous systems and bridging the virtual, digital and physical worlds• Federated IoT platforms and interoperability• Evolution from intelligent devices to connected systems of systems by adding new layers of cognitive behaviour, artificial intelligence and user interfaces.• Innovation through IoT ecosystems• Trust-based IoT end-to-end security, privacy framework• User acceptance, societal, ethical aspects and legal issues• Internet of Things Applications

This book aims to provide a broad overview of various topics of Internet of Things (IoT), ranging from research, innovation and development priorities to enabling technologies, nanoelectronics, cyber-physical systems, architecture, interoperability and industrial applications. All this is happening in a global context, building towards intelligent, interconnected decision making as an essential driver for new growth and co-competition across a wider set of markets. It is intended to be a standalone book in a series that covers the Internet of Things activities of the IERC – Internet of Things European Research Cluster from research to technological innovation, validation and deployment.The book builds on the ideas put forward by the European Research Cluster on the Internet of Things Strategic Research and Innovation Agenda, and presents global views and state of the art results on the challenges facing the research, innovation, development and deployment of IoT in future years. The concept of IoT could disrupt consumer and industrial product markets generating new revenues and serving as a growth driver for semiconductor, networking equipment, and service provider end-markets globally. This will create new application and product end-markets, change the value chain of companies that creates the IoT technology and deploy it in various end sectors, while impacting the business models of semiconductor, software, device, communication and service provider stakeholders. The proliferation of intelligent devices at the edge of the network with the introduction of embedded software and app-driven hardware into manufactured devices, and the ability, through embedded software/hardware developments, to monetize those device functions and features by offering novel solutions, could generate completely new types of revenue streams. Intelligent and IoT devices leverage software, software licensing, entitlement management, and Internet connectivity in ways that address many of the societal challenges that we will face in the next decade.

The book aims to provide a broad overview of various topics of Internet of Things from the research, innovation and development priorities to enabling technologies, nanoelectronics, cyber physical systems, architecture, interoperability and industrial applications. It is intended to be a standalone book in a series that covers the Internet of Things activities of the IERC – Internet of Things European Research Cluster from technology to international cooperation and the global state of play.The book builds on the ideas put forward by the European research Cluster on the Internet of Things Strategic Research Agenda and presents global views and state of the art results.

The book aims to provide a broad overview of various topics of the Internet of Things (IoT) from the research and development priorities to enabling technologies, architecture, security, privacy, interoperability and industrial applications. It is intended to be a standalone book in a series that covers the Internet of Things activities of the IERC ? Internet of Things European Research Cluster from technology to international cooperation and the global state of play. The book builds on the ideas put forward by the European research Cluster on the Internet of Things Strategic Research Agenda and presents global views and state of the art results on the challenges facing the research, development and deployment of IoT at the global level.Today we see the integration of Industrial, Business and Consumer Internet which is bringing together the Internet of People, Internet of Things, Internet of Energy, Internet of Vehicles, Internet of Media, Services and Enterprises in forming the backbone of the digital economy, the digital society and the foundation for the future knowledge and innovation based economy in supporting solutions for the emerging challenges of public health, aging population, environmental protection and climate change, the conservation of energy and scarce materials, enhancements to safety and security and the continuation and growth of economic prosperity.Penetration of smartphones and advances in machine to machine and wireless communication technology will be the main drivers for IoT development. The IoT contribution is in the increased value of information created by the number of interconnections among things and the transformation of the processed information into knowledge shared into the Internet of Everything.

The IoT European Platforms Initiative (IoT-EPI) projects are addressing the topic of Internet of Things and Platforms for Connected Smart Objects and aim to deliver an IoT extended into a web of platforms for connected devices and objects that supports smart environments, businesses, services and persons with dynamic and adaptive configuration capabilities. The specific areas of focus of the research activities are architectures and semantic interoperability, which reliably cover multiple use cases. The goal is to deliver dynamically-configured infrastructure and integration platforms for connected smart objects covering multiple technologies and multiple intelligent artefacts. The IoT-EPI ecosystem has been created with the objective of increasing the impact of the IoT-related European research and innovation, including seven European promising projects on IoT platforms: AGILE, BIG IoT, INTER-IoT, VICINITY, SymbIoTe, bIoTope, and TagItSmart.This white paper provides an insight regarding interoperability in the IoT platforms and ecosystems created and used by IoT-EPI. The scope of this document covers the interoperability aspects, challenges and approaches that cope with interoperability in the current existing IoT platforms and presents some insights regarding the future of interoperability in this context. It presents possible solutions, and a possible IoT interoperability platform architecture.

This book provides an overview of the next generation Internet of Things (IoT), ranging from research, innovation, development priorities, to enabling technologies in a global context. It is intended as a standalone in a series covering the activities of the Internet of Things European Research Cluster (IERC), including research, technological innovation, validation, and deployment.The following chapters build on the ideas put forward by the European Research Cluster, the IoT European Platform Initiative (IoT–EPI), the IoT European Large-Scale Pilots Programme and the IoT European Security and Privacy Projects, presenting global views and state-of-the-art results regarding the next generation of IoT research, innovation, development, and deployment.The IoT and Industrial Internet of Things (IIoT) are evolving towards the next generation of Tactile IoT/IIoT, bringing together hyperconnectivity (5G and beyond), edge computing, Distributed Ledger Technologies (DLTs), virtual/ andaugmented reality (VR/AR), and artificial intelligence (AI) transformation.Following the wider adoption of consumer IoT, the next generation of IoT/IIoT innovation for business is driven by industries, addressing interoperability issues and providing new end-to-end security solutions to face continuous treats.The advances of AI technology in vision, speech recognition, natural language processing and dialog are enabling the development of end-to-end intelligent systems encapsulating multiple technologies, delivering services in real-time using limited resources. These developments are focusing on designing and delivering embedded and hierarchical AI solutions in IoT/IIoT, edge computing, using distributed architectures, DLTs platforms and distributed end-to-end security, which provide real-time decisions using less data and computational resources, while accessing each type of resource in a way that enhances the accuracy and performance of models in the various IoT/IIoT applications.The convergence and combination of IoT, AI and other related technologies to derive insights, decisions and revenue from sensor data provide new business models and sources of monetization. Meanwhile, scalable, IoT-enabled applications have become part of larger business objectives, enabling digital transformation with a focus on new services and applications.Serving the next generation of Tactile IoT/IIoT real-time use cases over 5G and Network Slicing technology is essential for consumer and industrial applications and support reducing operational costs, increasing efficiency and leveraging additional capabilities for real-time autonomous systems.New IoT distributed architectures, combined with system-level architectures for edge/fog computing, are evolving IoT platforms, including AI and DLTs, with embedded intelligence into the hyperconnectivity infrastructure.The next generation of IoT/IIoT technologies are highly transformational, enabling innovation at scale, and autonomous decision-making in various application domains such as healthcare, smart homes, smart buildings, smart cities, energy, agriculture, transportation and autonomous vehicles, the military, logistics and supply chain, retail and wholesale, manufacturing, mining and oil and gas.

This book provides an overview of the Internet of Things (IoT) – covering new ideas, concepts, research and innovation to enable the development of IoT technologies in a global context. The work is intended as a standalone book in a series covering the activities of the Internet of Things European Research Cluster (IERC) – including research, technological innovation, validation, and deployment.The book chapters build on the developments and innovative ideas put forward by the IERC, the IoT European Large-Scale Pilots Programme and the IoT European Security and Privacy Projects – presenting new concepts, ideas and future IoT trends and ways of integrating open data frameworks and IoT marketplaces into larger deployment ecosystems.The IoT and Industrial Internet of Things technologies are moving towards hyperautomated solutions – combining hyperconnectivity, artificial intelligence (AI), distributed ledger technologies and virtual/augmented extended reality, with edge computing and deep edge processing becoming an assertive factor across industries for implementing intelligent distributed computing resources and data to keep the efficient data exchange and processing local to reduce latency, exploit the sensing/actuating capabilities and enable greater autonomy.Expanding the adoption of consumer, business, industrial and tactile IoT requires further development of hyperautomated IoT concepts for collaborative solutions involving machines and humans to expand augmented creativity at the application level using AI to optimise the industrial processes and progress towards a symbiotic economy based on distributed federated cloud/edge infrastructure allowing resource sharing in the form of computing, memory and analytics capabilities.The advances of autonomous IoT applications delivering services in real-time encompasses development in servitisation, robotisation, automation and hyperconnectivity, which are essential for the rapid evolution of industrial enterprises in the new digital era. The rise of digital twins integrated into IoT platforms as fully interactive elements embedded into the simulation and optimisation environment, as well as the embedment of AI techniques and methods, enhances the accuracy and performance of models in the various IoT and Industrial Internet of Things applications.The convergence of technologies to provide scalable, interoperable IoT-enabled applications pushed the requirements for high bandwidth, low latency and robust and dependable connectivity to support the industry’s demand for deeper integration and improved analytics to deliver sustainable competitive advantage products and services, enabling digital transformation with a focus on new business models.Safety and security are interlinked for the next wave of IoT technologies and applications and combined, prove a greater value for rapid adoption.The new IoT technologies are essential for facilitating sustainable development, reducing energy consumption and, by supporting the optimisation of products and processes, mitigating unnecessary carbon emissions – thereby reducing the environmental impact through real-time data collection, analysis, exchange, and processing.

This book provides in-depth insights into use cases implementing artificial intelligence (AI) applications at the edge. It covers new ideas, concepts, research, and innovation to enable the development and deployment of AI, the industrial internet of things (IIoT), edge computing, and digital twin technologies in industrial environments. The work is based on the research results and activities of the AI4DI project, including an overview of industrial use cases, research, technological innovation, validation, and deployment.This book’s sections build on the research, development, and innovative ideas elaborated for applications in five industries: automotive, semiconductor, industrial machinery, food and beverage, and transportation.The articles included under each of these five industrial sectors discuss AI-based methods, techniques, models, algorithms, and supporting technologies, such as IIoT, edge computing, digital twins, collaborative robots, silicon-born AI circuit concepts, neuromorphic architectures, and augmented intelligence, that are anticipating the development of Industry 5.0. Automotive applications cover use cases addressing AI-based solutions for inbound logistics and assembly process optimisation, autonomous reconfigurable battery systems, virtual AI training platforms for robot learning, autonomous mobile robotic agents, and predictive maintenance for machines on the level of a digital twin.AI-based technologies and applications in the semiconductor manufacturing industry address use cases related to AI-based failure modes and effects analysis assistants, neural networks for predicting critical 3D dimensions in MEMS inertial sensors, machine vision systems developed in the wafer inspection production line, semiconductor wafer fault classifications, automatic inspection of scanning electron microscope cross-section images for technology verification, anomaly detection on wire bond process trace data, and optical inspection.The use cases presented for machinery and industrial equipment industry applications cover topics related to wood machinery, with the perception of the surrounding environment and intelligent robot applications. AI, IIoT, and robotics solutions are highlighted for the food and beverage industry, presenting use cases addressing novel AI-based environmental monitoring; autonomous environment-aware, quality control systems for Champagne production; and production process optimisation and predictive maintenance for soybeans manufacturing. For the transportation sector, the use cases presented cover the mobility-as-a-service development of AI-based fleet management for supporting multimodal transport.This book highlights the significant technological challenges that AI application developments in industrial sectors are facing, presenting several research challenges and open issues that should guide future development for evolution towards an environment-friendly Industry 5.0. The challenges presented for AI-based applications in industrial environments include issues related to complexity, multidisciplinary and heterogeneity, convergence of AI with other technologies, energy consumption and efficiency, knowledge acquisition, reasoning with limited data, fusion of heterogeneous data, availability of reliable data sets, verification, validation, and testing for decision-making processes.

The advances in industrial edge artificial intelligence (AI) are transforming the way industrial equipment and machines interact with the real world, with other machines and humans during manufacturing processes. These advances allow Industrial Internet of Things (IIoT) and edge devices to make decisions during the manufacturing processes using sensors and actuators.Digital transformation is reshaping the manufacturing industry, and industrial edge AI aims to combine the potential advantages of edge computing (low latency times, reduced bandwidth, distributed architecture, improved trustworthiness, etc.) with the benefits of AI (intelligent processing, predictive solutions, classification, reasoning, etc.).The industrial environments allow the deployment of highly distributed intelligent industrial applications in remote sites that require reliable connectivity over wireless and cellular connections. Intelligent connectivity combines IIoT, wireless/cellular and AI technologies to support new autonomous industrial applications by enabling AI capabilities at the edge and allowing manufacturing companies to improve operational efficiency and reduce risks and costs for industrial applications.There are several critical issues to consider when introducing AI to industrial IoT applications considering training AI models at the edge, the deployment of the AI-trained inferencing models on the target edge hardware platforms, and the benchmarking of solutions compared to other implementations.Next-generation trustworthy industrial AI systems offer dependability in terms of their design, transparency, explainability, verifiability, and standardised industrial solutions can be implemented in various applications across different industrial sectors.New AI techniques such as embedded machine learning (ML) and deep learning (DL), capture edge data, employ AI models, and deploy these in hardware target edge devices, from ultra-low-power microcontrollers to embedded devices, gateways, and on-premises servers for industrial applications. These techniques reduce latency, increase scalability, reliability, and resilience; and optimise wireless connectivity, greatly expanding the capabilities of the IIoT.This book provides an overview of the latest research results and activities in industrial AI technologies and applications, based on the innovative research, developments and ideas generated by the ECSEL JU AI4DI, ANDANTE and TEMPO projects.The authors describe industrial AI's challenges, the approaches adopted, and the main industrial systems and applications to give the reader extensive insight into the technical nature of this field. The chapters provide insightful material on industrial AI technologies and applications.This book is a valuable resource for researchers, post-graduate students, practitioners, and technoloyg developers interested in gaining insight into industrial edge AI, the IIoT, embedded machine and deep learning, new technologies, and solutions to advance intelligent processing at the edge.The Open Access version of this book, available at http://www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non-Commercial (CC-BY-NC) 4.0 International License.

Recent technological developments in sensors, edge computing, connectivity, and artificial intelligence (AI) technologies have accelerated the integration of data analysis based on embedded AI capabilities into resource-constrained, energy-efficient hardware devices for processing information at the network edge.Embedded AI combines embedded machine learning (ML) and deep learning (DL) based on neural networks (NN) architectures such as convolutional NN (CNN), or spiking neural network (SNN) and algorithms on edge devices and implements edge computing capabilities that enable data processing and analysis without optimised connectivity and integration, allowing users to access data from various sources.Embedded AI efficiently implements edge computing and AI processes on resource-constrained devices to mitigate downtime and service latency, and it successfully merges AI processes as a pivotal component in edge computing and embedded system devices. Embedded AI also enables users to reduce costs, communication, and processing time by assembling data and by supporting user requirements without the need for continuous interaction with physical locations.This book provides an overview of the latest research results and activities in industrial embedded AI technologies and applications, based on close cooperation between three large-scale ECSEL JU projects, AI4DI, ANDANTE, and TEMPO. The book’s content targets researchers, designers, developers, academics, post-graduate students and practitioners seeking recent research on embedded AI. It combines the latest developments in embedded AI, addressing methodologies, tools, and techniques to offer insight into technological trends and their use across different industries.

The book aim is to define the Internet of Things (IoT) in a global view, present the research agenda for Internet of Things technologies by addressing the new technological developments and providing a global balanced coverage of the challenges and the technical and industrial trends.Energy consumption by the data, communication and networking devices and global CO2 emission is increasing exponentially. ICT has a dual role in this process: it accounts for about two percent of global CO2 emissions and at the same the ICT including IoT technologies and applications have a direct effect on lowering CO2 emissions, increasing energy efficiency, reducing power consumption, and achieving efficient waste recycling.The book builds on the ideas put forward by the European research Cluster on the Internet of Things Strategic Research Agenda and presents global views and state of the art results on the challenges facing the research, development and deployment of IoT at the global level.IoT together with the other emerging Internet developments such as Internet of Energy, Media, People, Services, Business/Enterprises are the backbone of the digital economy, the digital society and the foundation for the future knowledge based economy and innovation society. IoT developments show that we will have 16 billion connected devices by the year 2020 , which will average out to six devices per person on earth and to many more per person in digital societies.Devices like smart phones and machine to machine or thing to thing communication will be the main drivers for further IoT development. The first direct consequence of the IoT is the generation of huge quantities of data, where every physical or virtual object may have a digital twin in the cloud, which could be generating regular updates. The IoT contribution is in the increased value of information created by the number of interconnections among things and the transformation of the processed information into knowledge for the benefit of mankind and society. The Internet of Things market is connected to industrial machine to machine (M2M) systems, smart meters and enabling technologies such as nanoelectronics, communications, sensors, smart phones, embedded systems, cloud computing and software technologies that will create new products, new services, new interfaces by creating smart environments and smart spaces with applications ranging from smart transport, cities, buildings, energy, grid, to smart health and life.Technical topics discussed in the book include:• The Internet of Things: The Way Ahead• Internet of Things Strategic Research Agenda• Challenges of a Sustainable Roadmap for the Internet of Things• Technologies behind Internet of Things: From Nanoelectronics and Embedded Systems to Cloud Computing and Cognitive Systems• Machine to machine (M2M) communication and the emerging Internet of Things applications• The "Internet of Things" based on IPv6. Paving the way to Smart IPv6 Buildings• "Internet of Things - from Ubiquitous Computing to Ubiquitous Intelligence Applications"• Virtualization of network resources and Physical devices in Internet of Things applications• Validation and Interoperability challenges for IoT• Mobile devices enable IoT evolution from industrial applications to mass consumer applications• Interoperability, Standardisation and Governance in the era of Internet of Things (IoT)• Technologies, Applications, and Governance in the Internet of Things• Opportunities, Challenges for Internet of Things Technologies