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
High-Level Synthesis based Methodologies for Hardware Security, Trust and IP Protection
High-Level Synthesis based Methodologies for Hardware Security, Trust and IP Protection presents state-of-the art high-level synthesis methodologies for hardware security and trust, including IP protection through synthesis-based watermarking and structural obfuscation.
All modern electronic gadgets have complex system-on-chips (SoCs) that rely heavily on data intensive application specific processors, for digital signal processing (DSP), machine learning, and image processing applications. These data-intensive cores, in the form of intellectual property (IP), form an integral part of various modern equipment and consumer applications, such as smart phones, smart watches, and tablets.
High level synthesis (HLS) frameworks play a pivotal role in designing these application specific processors. However, the design of such processors can be exposed to several trust issues and hardware security threats, such as IP piracy, fraud IP ownership, and reverse engineering.
Written by an expert author, this book is a source of information for readers on HLS solutions for hardware security. It covers topics such as HLS-based watermarking using retinal biometrics, HLS-based structural obfuscation, and detective countermeasure against HLS-based hardware Trojan attacks.
This book is a useful resource for researchers, graduate students, and practising engineers working in electronics and chip design.
Cybersecurity in Emerging Healthcare Systems
Emerging healthcare networks are interconnected physical systems that use cyber technologies for interaction and functionality. The proliferation of massive internet-of-things (IoT) devices enables remote and distributed access to cutting-edge diagnostics and treatment options in modern healthcare systems. New security vulnerabilities are emerging due to the increasing complexity of the healthcare architecture, in particular, threats to medical devices and critical infrastructure pose significant concerns owing to their potential risks to patient health and safety. In recent times, patients have been exposed to high risks from attacks capable of disrupting critical medical infrastructure, communications facilities, and services, interfering with medical devices, or compromising sensitive user data.
This book seeks to present cyber risk and vulnerability models, considering a number of threats and examining how effective regulations could help guarantee medical device fidelity and trust. The book discusses the application of artificial intelligence and machine learning to provide practical learning-based solutions to address cyberattacks in emerging healthcare systems. The book focuses on the technical considerations, potential opportunities, critical cybersecurity challenges, the prospects and potential benefits of cybersecurity in emerging healthcare systems. Finally, the book presents case studies, highlighting critical lessons, and providing recommendations for designing AI-based cybersecurity architectures for emerging healthcare systems.
Written by an international team of authors, this book is suitable for an audience of industry-based and academic researchers, scientists, and computer engineers working in data science, cybersecurity and wireless communications particularly those specialising in healthcare data science and those in related fields.
Clean Energy for Low-Income Communities: Technology, deployment and challenges
Energy provision for low income or remote communities is a difficult challenge, with many still depending on polluting and costly fossil fuels. Transporting energy is a further problem since some communities are only accessible during brief periods of the year. Local energy generation is a key solution, but technical challenges need to be overcome.
This hands-on treatise explores technologies and approaches for accelerating deployment of accessible clean energy and discusses obstacles hindering that deployment. The primary focus is on engineering topics, although contributions from non-engineering application experts are also included. Chapters cover principal aspects of energy provision for low-income communities, low cost and energy-efficient housing designs, solar energy for low-income communities, solar PV integration in residential buildings, rural electrification in low-income communities and in remote communities using wind and solar energy, advances in biofuels production, and as a case study, modelling and forecasting energy mix scenarios for Turkey.
Clean Energy for Low Income Communities: Technology, deployment and challenges offers in-depth discussion of this multidisciplinary topic for an audience of researchers in academia, renewable energy and utilities experts in industry, technology manufacturers and advanced students, as well as energy experts in think tanks and development banks.
Fuzzy Logic Control in Energy Systems: With design examples in MATLAB®/Simulink®
Fuzzy models have the capability of recognising, representing, and working with data that is vague or lacks certainty, making them suitable for managing electrical energy systems involving intermittent distributed generation and varying distributed loads.
The second edition of Fuzzy Logic Control in Energy Systems has been revised and updated with new topics including shade and integration issues in PV, microgrids, cybersecurity in power systems, and day-ahead estimation of sun and wind data. Starting with a review of fuzzy logic, chapters cover fuzzy sets and partitioning, fuzzy decision making, fuzzy logic controllers (FLC), and system modelling and control. The application of FLC in power systems, wind energy, PV energy systems and microgrids is then explored.
Several examples of fuzzy logic control and management are discussed including DC motor control, multi area load-frequency control, and wind and PV energy management. The book presents a fuzzy logic controller design in Matlab-Simulink enabling the reader to study every step and to develop their own fuzzy processor library and toolbox.
Providing thorough and logical coverage of fuzzy logic control and its use in energy systems, this book provides valuable insights for researchers and practicing engineers involved with power system design and control, grid operators, PV and wind turbine manufacturers, as well as advanced students in EE.
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.
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.
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.
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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