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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.

  • Transforming research for an Open Science world

  • Supporting each step of the research journal

  • From trusted content to precision analytics

Latest Books

image of Interactions of Wind Turbines with Aviation Radio and Radar Systems
  • Interactions of Wind Turbines with Aviation Radio and Radar Systems
  • Wind farms and wind turbines are strong reflectors of radio waves, which can affect radar and radio systems used by civil and military aviation. The speeds of turbine blades and aircraft are comparable, and it can be difficult to discriminate between them using existing radar systems. Wind turbines may also affect communications, navigation and instrument landing systems. This situation is a brake to wind farm development slowing or stopping exploitation of many giga watts of wind capacity in many countries. Therefore, developing approaches and technologies for the mitigation of the impacts of wind farms on aviation systems is of great importance. These technologies have the potential to increase renewable energy generation and promote energy independence but, and this is critically important, they must do so without compromising safety or national defense.

    Interactions of Wind Turbines with Aviation Radio and Radar Systems introduces the basic principles of aviation and aviation radio systems, of wind, wind turbines and the planning and development processes of wind farms. The operating principles, antenna systems, beam patterns and frequencies of potentially affected aviation systems are described to facilitate analysis of the problems. General analytical techniques are explored. For systems amenable to mitigation, older techniques and their pitfalls are described, and useful modern concepts are introduced. There are still matters that require basic and applied research; suggestions for topics including future enhancements to mitigation are provided. Guidance is offered on where to find additional information.

    The issues are multi-disciplinary and a key consideration addressed by the book is explaining the terminology to help all the stakeholders communicate with each other. For example, the book provides the wind power community with an understanding of the aviation problem, and it explains how wind power extraction is developing for the aviation community to understand what the future has in hold. Researchers and experts in the wind farm development community will find this book to be a valuable resource, as will aviation radio and radar experts, legal counsels and other specialist consultants in the field.

image of AI Techniques in EV Motor and Inverter Fault Detection and Diagnosis
  • AI Techniques in EV Motor and Inverter Fault Detection and Diagnosis
  • The motor drive system plays a significant role in the safety and function of electric vehicles as a bridge for power transmission. In order to enhance the efficiency and stability of the drive system, more and more studies based on AI technology are devoted to the fault detection and diagnosis of the motor drive system.

    AI Techniques in EV Motor and Inverter Fault Detection and Diagnosis comprehensively covers the recently-developed AI applications for solving condition monitoring and fault detection issues in EV electrical conversion systems. AI-based fault detection and diagnosis (FDD) is divided into two main steps: feature extraction and fault classification. The application of different signal processing methods in feature extraction is discussed. In particular, the application of traditional machine learning and deep learning algorithms for fault classification is presented in detail. In addition, the characteristics of all techniques reviewed are summarised.

    Chapters systematically address condition monitoring and fault detection in EV motors and inverters. Four case studies are including, covering AI based electric motor fault diagnosis, AI based inverter/IGBT fault diagnosis, AI based bearing fault diagnosis, and AI based gearbox fault diagnosis. Alongside each case study, the authors discuss the differences between conventional methods and AI-based methods in EV applications, and the motivation, advantages, shortcomings and challenges of AI-based methods. Finally, the latest developments, research gaps and future challenges in fault monitoring and diagnosis of motor faults are explored.

    Providing a systematic and thorough exploration of its field, this book is a valuable resource for researchers and students with an interest in the applications of AI in electric vehicles, and for engineers and research and development professionals in the electric automotive industry.

image of The Role of 6G and Beyond on the Road to Net-Zero Carbon
  • The Role of 6G and Beyond on the Road to Net-Zero Carbon
  • In the race against climate change, the focus has turned towards achieving the 2050 net-zero carbon target. Achieving net-zero means balancing between the amount of greenhouse gas removed from the atmosphere and those produced and released. Efforts are needed on both sides to find suitable solutions to reduce released emissions and to remove current emissions from the atmosphere. A collective effort revolving around the utilisation of new technologies, particularly in wireless and mobile communications, is needed to achieve the net-zero carbon target.

    The previous generations of mobile connectivity have already played a crucial role in reducing emissions through such means as smart metering and remote working. Numerous studies have highlighted how vital 5G technology is in mitigating climate change and accelerating the way to net-zero. This is due to the potential 5G technology has in bringing increasing data rates, massive machine type communication, and ultra-low latency. As 5G is rolling out, researchers are researching how the 6th generation of mobile networks (6G) will take the advantages of 5G even further.

    This book focuses on the potential of 6G to further expedite the achievement of net-zero. The authors cover the latest research efforts made in utilising 6G technology to solve real societal problems and to thought provoke researchers and scientists in proposing innovative ideas on how 6G can help with the fight against climate change.

    The book is geared towards researchers, engineers, scientists, technology professionals and advanced students in the fields of wireless communication, energy management, green tech and sustainability with a focus on net-zero carbon. It will also serve as an advanced textbook for postgraduate students in mobile communications and energy-related disciplines, and it will be useful to policy makers, 5G and 6G stakeholders, regulators, institutional actors and research agencies to support them in incorporating green sustainable mobile communication networks in their plans for net-zero targets.

image of Explainable Artificial Intelligence (XAI): Concepts, enabling tools, technologies and applications
  • Explainable Artificial Intelligence (XAI): Concepts, enabling tools, technologies and applications
  • The world is keen to leverage multi-faceted AI techniques and tools to deploy and deliver the next generation of business and IT applications. Resource-intensive gadgets, machines, instruments, appliances, and equipment spread across a variety of environments are empowered with AI competencies. Connected products are collectively or individually enabled to be intelligent in their operations, offering and output.

    AI is being touted as the next-generation technology to visualize and realize a bevy of intelligent systems, networks and environments. However, there are challenges associated with the huge adoption of AI methods. As we give full control to AI systems, we need to know how these AI models reach their decisions. Trust and transparency of AI systems are being seen as a critical challenge. Building knowledge graphs and linking them with AI systems are being recommended as a viable solution for overcoming this trust issue and the way forward to fulfil the ideals of explainable AI.

    The authors focus on explainable AI concepts, tools, frameworks and techniques. To make the working of AI more transparent, they introduce knowledge graphs (KG) to support the need for trust and transparency into the functioning of AI systems. They show how these technologies can be used towards explaining data fabric solutions and how intelligent applications can be used to greater effect in finance and healthcare.

    Explainable Artificial Intelligence (XAI): Concepts, enabling tools, technologies and applications is aimed primarily at industry and academic researchers, scientists, engineers, lecturers and advanced students in the fields of IT and computer science, soft computing, AI/ML/DL, data science, semantic web, knowledge engineering and IoT. It will also prove a useful resource for software, product and project managers and developers in these fields.

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image of Intelligent Multimedia Processing and Computer Vision: Techniques and applications
  • Intelligent Multimedia Processing and Computer Vision: Techniques and applications
  • Intelligent multimedia involves the computer processing and understanding of perceptual input from speech, text, videos and images. Reacting to these inputs is complex and involves research from engineering, computer science and cognitive science. Intelligent multimedia processing deals with the analysis of images and videos to extract useful information for numerous applications including medical imaging, robotics, remote sensing, autonomous driving, AR/VR, law enforcement, biometrics, multimedia enhancement and reconstruction, agriculture, and security. Intelligent multimedia processing and computer vision have seen an upsurge over the last few years. With the increasing use of intelligent multimedia processing techniques in various sectors, the requirement for fast and reliable techniques to analyse and process multimedia content is increasing day by day.

    Intelligent Multimedia Processing and Computer Vision: Techniques and applications reviews cutting edge research in the areas of intelligent multimedia processing and computer vision techniques and applications with a particular emphasis on interdisciplinary approaches and novel solutions. The book is aimed at practicing engineers, scientists, technology professionals, researchers and advanced students in the fields of multimedia processing and security, image processing, computer vision, biometrics, intelligent and smart technologies, machine learning and deep learning, and autonomous systems.

image of Personal Knowledge Graphs (PKGs): Methodology, tools and applications
  • Personal Knowledge Graphs (PKGs): Methodology, tools and applications
  • Since the development of the semantic web, knowledge graphs (KGs) have been used by search engines, knowledge-engines and question-answering services as well as social networks. A knowledge graph, also known as a semantic network, represents and illustrates a network of real-world entities such as objects, events, situations, or concepts and the relationships between them. This information is usually stored in a graph database and visualized as a graph structure, prompting the term "knowledge graph". Knowledge graphs structure the information of entities, their properties and the relation between them.

    Personal knowledge graphs (PKG) encode the same information at an individual level and therefore vary widely. PKGs require the processing of each person's individual information and is constructed in an automated fashion. Once a PKG is constructed, it will be integrated in broader purpose KGs. A PKG is a representation of all relevant common-sense knowledge and personal data for a user and can support the development of innovative applications such as a digitalized personalized coach. It empowers stakeholders to make more effective decisions.

    This book explores in a structured manner the global advanced research around PKGs to support the development of innovative digitalized personalized applications such as personal banking, personalized book-keeping, daily health-related activities monitoring and goal management tracking. The authors present methodologies, tools and applications including innovative topics tailored for PKGs such as named entity recognition and linking, construction approaches, modelling of personalization and context-awareness, evaluation approaches, relation extraction techniques, query answering in user specific knowledge graphs, knowledge representation and reasoning (KRR), visualization tools, integration tools and techniques, and fact summarization.

    The book provides systematic coverage of this complex topic for researchers, scientists and engineers in both industry and academia working in data science, ICTs, knowledge engineering, semantic web, reasoning, information retrieval, and machine and deep learning with a focus on knowledge graphs. Advanced students with an interest in the field will also find this to be a useful resource.

image of Multistatic Passive Radar Target Detection: A detection theory framework
  • Multistatic Passive Radar Target Detection: A detection theory framework
  • This book is devoted to target detection in a class of radar systems referred to as passive multistatic radar. This system is of great interest in both civilian and military scenarios due to many advantages. First, this system is substantially smaller and less expensive compared to an active radar system. Second, the multistatic configuration improves its detection and classification capabilities. Finally, there are many signals available for passive sensing making them hard to avoid.

    Multistatic Passive Radar Target Detection: A detection theory framework focuses on examining the multistatic passive radar target detection problem using the detection-theory framework, with the aim of presenting the latest research developments in this field. Early methods were based on intuition and lacked optimality, however, more recent methods with a clear theoretical basis have emerged, based on detection theory. The book offers timely and useful information to advanced students, researchers, and designers of passive radar (PR) systems.

    The book is organized into four parts, with each part addressing a specific aspect of target detection in various radar systems. The first part, consisting of two chapters, covers the fundamentals of PR and traditional target detection algorithms. Part two comprises seven chapters and deals with the target detection issue in passive bistatic radar (PBR) with a reliable reference channel. Part three includes two chapters and focuses on the detection of targets in multistatic PR systems in the presence of noisy reference channels. Finally, part four, which consists of two chapters, discusses the target detection problem in multistatic and MIMO PRs when no reliable reference channel is available.

image of Energy Harvesting for Wireless Sensing and Flexible Electronics through Hybrid Technologies
  • Energy Harvesting for Wireless Sensing and Flexible Electronics through Hybrid Technologies
  • As wearable microelectronics are becoming ubiquitous, there is a growing interest in replacing batteries with a means of harnessing power from the user's environment via embedded systems. Efforts have been made to prolong the harvester's operational lifetime, overcoming energy dissipation, lowering resonant frequency, attaining multi-resonant states, and widening the operating frequency bandwidth of the biomechanical energy harvesters. Such technological advances mean harvesting energy is a viable solution for sustainably powering wearable electronics for health and wellbeing applications, such as continuous medical health monitoring, remote sensing, and motion tracking.

    The book introduces the concepts of vibration-based piezoelectric, electromagnetic and hybrid energy harvesters, and addresses their modelling, fabrication and characterization. It covers the fundamental principles and details the most advanced functions, including biomechanical and space applications. Detailed descriptions and explanations of a wide range of related concepts are provided, such as multi-degrees of freedom hybrid piezo-electromagnetic insole energy harvesters, non-linear 3D printed electromagnetic vibration energy harvesters, and finite element analysis of hybrid piezoelectric and electromagnetic energy harvesting. Also included are trends towards design, modelling, fabrication, and characterization of nonlinear multimodal electromagnetic and hybrid piezo-electromagnetic insole energy harvesters, as well as describing and explaining electromagnetic and hybrid piezo-electromagnetic energy harvesting technologies. The book provides an extensive and up-dated survey of the published scientific and technical articles and conference reports, covering more than 340 references. The book concludes with an outlook from the authors on likely future developments and applications.

    Energy Harvesting for Wireless Sensing and Flexible Electronics through Hybrid Technologies provides in-depth coverage of the topic for researchers from academia and industry, as well as advanced students with an interest in the field.

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