Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This open access book provides an overview about results of the InSecTT project. Artificial Intelligence of Things (AIoT) is the natural evolution for both Artificial Intelligence (AI) and Internet of Things (IoT) because they are mutually beneficial. AI increases the value of the IoT through machine learning by transforming the data into useful information, while the IoT increases the value of AI through connectivity and data exchange. Therefore, InSecTT—Intelligent Secure Trustable Things, a pan-European effort with over 50 key partners from 12 countries (EU and Turkey), provides intelligent, secure and trustworthy systems for industrial applications to provide comprehensive cost-efficient solutions of intelligent, end-to-end secure, trustworthy connectivity and interoperability to bring the Internet of Things and Artificial Intelligence together. InSecTT creates trust in AI-based intelligent systems and solutions as a major part of the AIoT. InSecTT fosters cooperation between big industrial players from various domains, a number of highly innovative SMEs distributed all over Europe and cutting-edge research organizations and universities. The project features a big variety of industry-driven use cases embedded into various application domains where Europe is in a leading position, i.e., smart infrastructure, building, manufacturing, automotive, aeronautics, railway, urban public transport, maritime as well as health. The demonstration of InSecTT solutions in well-known real-world environments like airports, trains, ports and the health sector shows their applicability on both high and broad level, going from citizens to European stakeholders. The first part of the book provides an introduction into the main topics of the InSecTT project: How to bring Internet of Things and Artificial Intelligence together to form the Artificial Intelligence of Things, a reference architecture for such kind of systems and how to develop trustworthy, ethical AI systems. In the second part, we show the development of essential technologies for creating trustworthy AIoT systems. The third part of the book is composed of a broad variety of examples on how to design, develop and validate trustworthy AIoT systems for industrial applications (including automotive, avionics, smart infrastructure, health care, manufacturing and railway).

Computational intelligence. --- Artificial intelligence. --- Cooperating objects (Computer systems). --- Computational Intelligence. --- Artificial Intelligence. --- Cyber-Physical Systems.

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This Open Access book introduces readers to many new techniques for enhancing and optimizing reliability in embedded systems, which have emerged particularly within the last five years. This book introduces the most prominent reliability concerns from today’s points of view and roughly recapitulates the progress in the community so far. Unlike other books that focus on a single abstraction level such circuit level or system level alone, the focus of this book is to deal with the different reliability challenges across different levels starting from the physical level all the way to the system level (cross-layer approaches). The book aims at demonstrating how new hardware/software co-design solution can be proposed to ef-fectively mitigate reliability degradation such as transistor aging, processor variation, temperature effects, soft errors, etc. Provides readers with latest insights into novel, cross-layer methods and models with respect to dependability of embedded systems; Describes cross-layer approaches that can leverage reliability through techniques that are pro-actively designed with respect to techniques at other layers; Explains run-time adaptation and concepts/means of self-organization, in order to achieve error resiliency in complex, future many core systems.

Electronic circuits. --- Computer engineering. --- Internet of things. --- Embedded computer systems. --- Microprocessors. --- Circuits and Systems. --- Cyber-physical systems, IoT. --- Processor Architectures. --- Minicomputers --- Embedded systems (Computer systems) --- Computer systems --- Architecture Analysis and Design Language --- IoT (Computer networks) --- Things, Internet of --- Computer networks --- Embedded Internet devices --- Machine-to-machine communications --- Computers --- Electron-tube circuits --- Electric circuits --- Electron tubes --- Electronics --- Design and construction --- Circuits and Systems --- Cyber-physical systems, IoT --- Processor Architectures --- Electronic Circuits and Systems --- Cyber-Physical Systems --- Fault-Tolerant Computing --- Reliability Enhancers in Embedded Systems --- SoCs based on cross-layer-reliability --- System-Level Reliability Analysis --- Dependable Software Execution --- Open access --- Electronics: circuits & components --- Electrical engineering --- Cybernetics & systems theory --- Computer architecture & logic design

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact

complexity --- fractality --- non-stationarity --- fractional calculus --- homeostasis --- smart medical devices --- critical phenomena and its implications --- emergence --- self-organization --- robustness --- physiological resiliency --- quality-of-life physiological control --- cyber-physical systems

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This open access proceedings presents new approaches to Machine Learning for Cyber-Physical Systems, experiences and visions. It contains some selected papers from the international Conference ML4CPS – Machine Learning for Cyber- Physical Systems, which was held in Hamburg (Germany), March 29th to 31st, 2023. Cyber-Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments. The Editors Prof. Dr. Oliver Niggemann held the professorship at the Institute for Industrial Information Technologies (inIT) in Lemgo (Germany) from 2008 to 2019 and was also deputy head of the Fraunhofer IOSB-INA until 2019. In 2019, he took over the university professorship "Computer Science in Mechanical Engineering" at the Helmut Schmidt University in Hamburg. His research at the Institute for Automation Technology is in the field of artificial intelligence and machine learning for cyber-physical systems. Prof. Dr.-Ing. Jürgen Beyerer is a full professor for informatics at the Institute for Anthropomatics and Robotics at the Karlsruhe Institute of Technology KIT and director of the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB. Research interests include automated visual inspection, signal and image processing, active vision, metrology, information theory, fusion of data and information from heterogeneous sources, system theory, autonomous systems and automation. Dr. Maria Krantz is a Postdoc at the Helmut Schmidt University in Hamburg. Her main research interests are causality in Cyber-Physical Systems and applications of diagnosis algorithms in production systems. Dr. Christian Kühnert is senior scientist at the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB. His research interests are in the field of machine-learning, data-fusion and data analytics for cyber-physical systems.

Cooperating objects (Computer systems). --- Computer engineering. --- Computer networks. --- Artificial intelligence. --- Neural networks (Computer science). --- Cyber-Physical Systems. --- Computer Engineering and Networks. --- Artificial Intelligence. --- Mathematical Models of Cognitive Processes and Neural Networks.

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This open access book reports on cutting-edge electrical engineering and microelectronics solutions to foster and support digitalization in the semiconductor industry. Based on the outcomes of the European project iDev40, which were presented at the two first conference editions of the European Advances in Digital Transformation Conference (EADCT 2018 and EADTC 2019), the book covers different, multidisciplinary aspects related to digital transformation, including technological and industrial developments, as well as human factors research and applications. Topics include modeling and simulation methods in semiconductor operations, supply chain management issues, employee training methods and workplaces optimization, as well as smart software and hardware solutions for semiconductor manufacturing. By highlighting industrially relevant developments and discussing open issues related to digital transformation, the book offers a timely, practice-oriented guide to graduate students, researchers and professionals interested in the digital transformation of manufacturing domains and work environments. .

Computer engineering. --- Internet of things. --- Embedded computer systems. --- Engineering economics. --- Engineering economy. --- Robotics. --- Automation. --- Cyber-physical systems, IoT. --- Engineering Economics, Organization, Logistics, Marketing. --- Robotics and Automation. --- Automatic factories --- Automatic production --- Computer control --- Engineering cybernetics --- Factories --- Industrial engineering --- Mechanization --- Assembly-line methods --- Automatic control --- Automatic machinery --- CAD/CAM systems --- Robotics --- Automation --- Machine theory --- Economy, Engineering --- Engineering economics --- Embedded systems (Computer systems) --- Computer systems --- Architecture Analysis and Design Language --- IoT (Computer networks) --- Things, Internet of --- Computer networks --- Embedded Internet devices --- Machine-to-machine communications --- Computers --- Design and construction --- Cyber-physical systems, IoT --- Engineering Economics, Organization, Logistics, Marketing --- Robotics and Automation --- Cyber-Physical Systems --- Industrial Management --- Industrial Automation --- Open Access --- Semantic Web Technologies --- Simulation-based Decision Making --- Cycle Time Modeling --- Automated Material Handling system --- Material Flow Simulation --- Digitalized Workplaces --- Automated Decision-making --- Cross Factory Decision-making --- Mixed Criticality Systems --- Digital twin --- Rapid Prototyping --- System dynamic simulation --- Return on quality --- iDev40 --- EADTC 2018 --- EADTC 2019 --- Electrical engineering --- Cybernetics & systems theory --- Engineering: general --- Management of specific areas