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Welcome to IET Digital Library

The IET Digital Library holds more than 190,000 technical papers from 1994 onwards for all IET journals, magazines, books, conference publications and seminar digests, the IET's member magazine Engineering & Technology, plus seminar digests and conference publications. Find out more about the Digital Library.

Latest Books

image of Antenna Booster Technology for Wireless Communications
  • Antenna Booster Technology for Wireless Communications
  • Being surface-mounted and chip-like in nature, the antenna booster fits seamlessly in an electronic printed circuit board the same way as any other electronic component such as an amplifier, filter or switch. It can be assembled with a conventional pick-and-place machine, making the manufacture and design of the new generation of IoT and mobile or wireless devices much simpler, faster and more effective.

    Starting with the theory and fundamentals behind the design of antenna boosters and matching networks, the authors present several architectures and show the readers how to put the theory into practice to design antenna systems on wireless platforms and multiband design for wireless device operations with optimized matching networks either passive or active.

    Written by two experts in the field, Antenna Booster Technology for Wireless Communications offers key insights into the principles and applications of antenna boosters for researchers from academia and industry, as well as lecturers and advanced students, engineers involved in antenna and electronics design, and developers of antenna, radio frequency, wireless and microwave technologies.

image of AI for Power Electronics and Renewable Energy Systems
  • AI for Power Electronics and Renewable Energy Systems
  • Rising shares of renewable energy are needed to stave off catastrophic climate change, but also bring about the challenge of intermittency, jeopardizing power quality. Instead of large central generation units, many distributed generators and loads need to be managed in order to integrate renewable energy with power systems.

    Artificial intelligence (AI) can meet this challenge with adaptive control and demand side management. When managing distributed and changing network components, AI can give control computers human-level performance, helping to solve key issues with intermittency, power quality and distributed generation and loads including EV. Use of AI for power systems has therefore become a research hotspot.

    This reference book systematically treats the applications of AI in power electronics and renewable energy systems. The book begins with an introduction to AI in power systems, then subsequent chapters cover the use of AI for electric machine fault diagnosis, for power electronic reliability, design, and control, in dual-active-bridge converters; AI for distribution network voltage control, signal stability control, and energy management of hybrid systems as well as for renewable energy systems with AI. The book ends with conclusions and an outlook for AI in power systems. Numerous worked examples throughout the text help readers understand the operating and controlling guidelines.

    Written by a team of well-known scientists and power system experts, AI for Power Electronics and Renewable Energy Systems is a valuable resource for researchers and PhD students, as well as experts in industry and utilities involved with electric power systems.

image of Agrivoltaics: Technical, ecological, commercial and legal aspects
  • Agrivoltaics: Technical, ecological, commercial and legal aspects
  • Agrivoltaics, also called agricultural-photovoltaics (Agri-PV or APV), integrates solar power generation into an agricultural activity on farmland.

    The PV modules not only generate clean energy, but also shield crops from intense sun, drought or wind erosion. The market potential in EU-27, UK, and Switzerland alone is estimated to be 968 GWp if only 1 % of the utilized agricultural area is used for Agri-PV. Interest is swiftly growing amongst scientists, policy makers, and within the farming and energy industries. The challenges lie in the construction of the PV system, choice and ecology of crops, and sowing and harvesting techniques.

    Agrivoltaics: Technical, ecological, commercial and legal aspects provides an overview of agrivoltaics, covering existing technical solutions both on system level as well as on the module level. Chapters cover the principles and definition, technological aspects of the PV and the agricultural system, yield prediction, light management, operations and management, ecological and social aspects, commercial, and legal considerations. Legal frameworks in different countries are explained. A short outlook describes how the future of Agri-PV could develop.

    The book provides systematic coverage of this emerging topic for researchers, scientists, and engineers involved with PV, farmers, decision makers in PV and agricultural sector, as well as policy makers.

image of Self-Organizing Dynamic Agents for the Operation of Decentralized Smart Grids
  • Self-Organizing Dynamic Agents for the Operation of Decentralized Smart Grids
  • Integrating intermittent distributed generation, distributed storage systems, electric vehicles, and flexible loads will present security, stability, and power quality challenges in future smart grids. The amount of data to be processed to face these issues can overwhelm grid operation tools and conventional IT-based applications, limiting situational awareness and decision support. Decentralized and self-organizing technologies can help with that problem. In a self-organizing system, information processing is based on local interactions of its elementary parts (dynamic agents), enabling the cooperative solution of complex decision-making problems by only requiring local information exchange without needing a fusion center for data collection and processing.

    Self-Organizing Dynamic Agents for the Operation of Decentralized Smart Grids describes the technology of cooperative sensor networks for smart grid computing, which allows for solving the fundamental power system operation problems by enabling the cooperation of dynamic agents. The resulting computing architecture is highly scalable, flexible, robust against perturbation, and able to self-repair.

    Chapters cover the needs and challenges in smart grids, cooperative and self-organizing sensor networks, self-organizing wide area measurement systems, decentralized voltage regulation and economic dispatch of distributed generators, grid monitoring estimation and control, and dynamic thermal rating assessment of overhead lines.

    Written with graduate students, researchers, and power system engineers in mind, this book offers a concise but thorough overview of the role of decentralized and self-organizing sensors in smart grids.

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image of Large Scale Grid Integration of Renewable Energy Sources: Solutions and technologies
  • Large Scale Grid Integration of Renewable Energy Sources: Solutions and technologies
  • Key to the further growth of shares of renewables is their integration with the existing grid system including EV and sector coupling. This in turn requires technical developments to enable flexibility and dispatch. Approaches to meeting these challenges include hybridization of different distributed energy resources, forecasting and control, storage and demand response, and modelling. Technological advances are also being accompanied by changes in business models.

    The first edition of this book for researchers in academia, power industry and at grid operators presented an overview of the steps on the way toward 100% clean power, covering systematically the different challenges and technologies. The 2nd edition has been substantially revised and updated.

    The book begins with an overview of the role of the power grid in a sustainable energy system. Chapters cover recent developments and future challenges for integration of renewable energy, wind energy forecasting, wind and PV integration, energy resources integration and demand response, DC distribution, distributed micro-storage and hydrogen energy systems.

    Providing an up-to-date and thorough overview of trends and developments on this essential renewable energy topic, the book is suitable for researchers in academia and industry as well as at utilities involved with renewables deployment and power grids.

image of Digital Twins for 6G: Fundamental theory, technology and applications
  • Digital Twins for 6G: Fundamental theory, technology and applications
  • Digital twin (DT) technology is a real-time evolving digital duplicate of a physical object or process that contains all its history. It is enabled by massive real-time multi-source data collection and analysis. While 6G is considered as an enabler of digital twins, DT can also be a facilitator for integrating AI and 6G towards reliable, pervasive and efficient intelligent technologies.

    While the DT concept is familiar among aerospace and industrial engineers, it is a relatively new topic among electronic, electrical, computer, communications and networking engineers. For future massive-scale industrial internet-of-things (IoT) applications facilitated by DTs, a 6G network will be much more advantageous than its 5G counterpart.

    Digital Twins for 6G: Fundamental theory, technology and applications aims to bring together knowledge from industrial practitioners and researchers, and to introduce novel concepts that can help address the challenges associated with this interdisciplinary topic. The authors will cover fundamentals, enabling technologies, standards and advanced topics of DT and 6G to demystify the DT concept and its networking requirements and benefits, support a broader understanding of DT and its relationship with 6G to a larger audience, support learning and understanding for researchers and professionals working on 5G and 6G, and create a foundation on DT and 6G for the international research community.

    This book is intended to be both a tutorial of the important topics around digital twin and advanced wireless communications technologies, including 6G, as well as an advanced overview for technical professionals in the communications industry, technical managers, and researchers in both academia and industry.

image of Affective Computing Applications using Artificial Intelligence in Healthcare: Methods, approaches and challenges in system design
  • Affective Computing Applications using Artificial Intelligence in Healthcare: Methods, approaches and challenges in system design
  • Affective computing is the study and development of systems and devices that can recognise human emotions. This can be done using sensing technologies and AI algorithms to process biological signals or facial images to identify the different affective states, such as happiness, anger, fear, surprise, sadness and disgust. This non-invasive technique has applications in healthcare such as emotional impairment detection, mental health assessment, emotional stress assessment, cognitive decline detection, attention deficit disorders, neurodegenerative diseases, neurological disorders, autism spectrum disorder, stress, anxiety or other behavioural assessment.

    This edited book provides an overview of the ongoing research on affective computing applications in healthcare using AI and IoT. This book covers recent advancements in computing technology, modelling methods, frameworks, and algorithms used for human affect detection using bio-signal and image processing methods.

    The book explores the use of EEG signals, thermal imaging, eye-movement patterns, gesture recognition systems and IoT systems to gather information and discusses the use of deep learning, CNN and RNN-LSTM models of how this information can be usefully processed to detect emotional states.

    Discussing the latest trends and developments in research in the field, this book is a useful resource for researchers in affective computing, affective neuroscience, cognitive neuroscience, computer vision, signal and image processing, cybersecurity, AI/ML/DL, data science, HCI, sensing and robotics.

    Practicing physicians, clinical experts or researchers in experimental and applied cognitive psychology who wish to understand the emotional wellbeing (pain and stress level analysis) of patients may also find this book of interest.

image of Managing Internet of Things Applications across Edge and Cloud Data Centres
  • Managing Internet of Things Applications across Edge and Cloud Data Centres
  • Cloud computing has been a game changer for internet-based applications such as content delivery networks, social networking and multi-tier enterprise applications. However, the requirements for low-latency data access, security, bandwidth, mobility, and cost have challenged centralized data center-based cloud computing models, which is driving the need for the novel computing paradigms of edge and fog computing. The internet of things (IoT) focuses on discovery, aggregation, management, and acting on data originating from internet-connected devices via programmable sensors, actuators, mobile phones, surveillance cameras, routers, gateways and switches. But the aggregation of this data is expensive and can be time consuming.

    Traditional cloud-centric resource management models need to move towards more distributed and decentralized models so that they can cope with the challenges posed by the evolution of IoT smart devices and network solutions. However, supporting IoT data processing across cloud and edge data centers is not a trivial challenge. IoT sensing devices must be configured as a collection of data-analytics driven workflows where each node in the process can essentially run on multiple heterogeneous cloud and edge data centers.

    This book presents state-of-the-art interdisciplinary computing research in the application lifecycle management for internet of things in edge and cloud computing. The book addresses challenges from a distributed system perspective that includes both cyber and physical aspects. The authors aim to bring together the four paradigms of cloud and edge computing, cyber physical systems, internet of things and big data for future ICT systems.

    Written and edited by an international team of experts in the field, this book offers key insights to researchers, engineers, IT professionals, advanced students, postgraduate students and lecturers working in the fields of parallel and distributed computing, data mining, information retrieval, cloud, edge and fog computing, and the IoT.

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