Edge-of-Things in Personalized Healthcare Support Systems discusses and explores state-of-the-art technology developments in storage and sharing of personal healthcare records in a secure manner that is globally distributed to incorporate best healthcare practices. The book presents research into the identification of specialization and expertise among healthcare professionals, the sharing of records over the cloud, access controls and rights of shared documents, document privacy, as well as edge computing techniques which help to identify causes and develop treatments for human disease. The book aims to advance personal healthcare, medical diagnosis, and treatment by applying IoT, cloud, and edge computing technologies in association with effective data analytics. Provides an in-depth analysis of how to model and design applications for state-of-the-art healthcare systems Discusses and explores the social impact of the intertwined use of emerging IT technologies for healthcare Covers system design and software building principles for healthcare using IoT, cloud, and edge computing technologies with the support of effective and efficient data analytics strategies Explores the latest algorithms using machine and deep learning in the areas of cloud, edge computing, IoT, and healthcare analytics

This book highlights the issues and challenges in personalised healthcare systems. The individual chapters address different aspects of such systems, including the novel Internet of Things (IoT) system architectures in healthcare and emerging e-health based IoT applications. Moreover, the book investigates the impact of cutting-edge innovations on the IoT.

This book highlights recent research on intelligent systems and nature-inspired computing. It presents 223 selected papers from the 22nd International Conference on Intelligent Systems Design and Applications (ISDA 2022), which was held online. The ISDA is a premier conference in the field of computational intelligence, and the latest installment brought together researchers, engineers, and practitioners whose work involves intelligent systems and their applications in industry. Including contributions by authors from 65 countries, the book offers a valuable reference guide for all researchers, students, and practitioners in the fields of computer science and engineering.

In this book, recent developments, the future outlook, and advanced and analytical modeling techniques of smart electric and hybrid vehicles are explained with examples backed by experimental and numerical data. It also discusses the integration of newer developments like digital twin, artificial intelligence, nature-inspired algorithms, Internet of Things, and the role of Industry 4.0 in advancements in vehicle engineering. It compiles overall aspects of advancements in smart electric and hybrid vehicles by bringing the latest research and development by comprehensive range of mathematical, numerical, and simulation modeling, and management techniques to strengthen the engineering science and technological developments for the future. Features: • This book focuses on contemporary aspects of smart electric and hybrid vehicles techniques for new means and models for green environment. • Discusses the role of artificial intelligence, machine learning, and machine vision tools in smart electric and hybrid vehicles. • Presents design and analysis of charging stations and their sustainability roadmap for smart electric vehicles. • Highlights the cyber and functional security of intelligent and hybrid vehicles. • Explains diagnostics, prognostics, reliability, and durability issues in smart electric and hybrid vehicles. • Covers the Internet of Things-based battery and charging management approach and effect of voltage drop in charging capacity of smart electric vehicles. It is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and automotive engineering.

This book divides edge intelligence into AI for edge (intelligence-enabled edge computing) and AI on edge (artificial intelligence on edge). It focuses on providing optimal solutions to the key concerns in edge computing through effective AI technologies, and it discusses how to build AI models, i.e., model training and inference, on edge. This book provides insights into this new inter-disciplinary field of edge computing from a broader vision and perspective. The authors discuss machine learning algorithms for edge computing as well as the future needs and potential of the technology. The authors also explain the core concepts, frameworks, patterns, and research roadmap, which offer the necessary background for potential future research programs in edge intelligence. The target audience of this book includes academics, research scholars, industrial experts, scientists, and postgraduate students who are working in the field of Internet of Things (IoT) or edge computing and would like to add machine learning to enhance the capabilities of their work. This book explores the following topics: Edge computing, hardware for edge computing AI, and edge virtualization techniques Edge intelligence and deep learning applications, training, and optimization Machine learning algorithms used for edge computing Reviews AI on IoT Discusses future edge computing needs Amitoj Singh is an Associate Professor at the School of Sciences of Emerging Technologies, Jagat Guru Nanak Dev Punjab State Open University, Punjab, India. Vinay Kukreja is a Professor at the Chitkara Institute of Engineering and Technology, Chitkara University, Punjab, India. Taghi Javdani Gandomani is an Assistant Professor at Shahrekord University, Shahrekord, Iran.

This book presents the state of the art of Internet of Things (IoT) from the perspective of healthcare and Ambient Assisted Living (AAL). It discusses the emerging technologies in healthcare services used for healthcare professionals and patients for enhanced living environments and public health. The topics covered in this book include emerging eHealth IoT applications, Internet of Medical Things, health sensors, and wearable sensors for pervasive and personalized healthcare, and smart homes applications for enhanced health and well-being. The book also presents various ideas for the design and development of IoT solutions for healthcare and AAL. It will be useful for bioengineers and professionals working in the areas of healthcare as well as health informatics.

Precision Medicine and Artificial Intelligence: The Perfect Fit for Autoimmunity covers background on artificial intelligence (AI), its link to precision medicine (PM), and examples of AI in healthcare, especially autoimmunity. The book highlights future perspectives and potential directions as AI has gained significant attention during the past decade. Autoimmune diseases are complex and heterogeneous conditions, but exciting new developments and implementation tactics surrounding automated systems have enabled the generation of large datasets, making autoimmunity an ideal target for AI and precision medicine. More and more diagnostic products utilize AI, which is also starting to be supported by regulatory agencies such as the Food and Drug Administration (FDA). Knowledge generation by leveraging large datasets including demographic, environmental, clinical and biomarker data has the potential to not only impact the diagnosis of patients, but also disease prediction, prognosis and treatment options. Allows the readers to gain an overview on precision medicine for autoimmune diseases leveraging AI solutions Provides background, milestone and examples of precision medicine Outlines the paradigm shift towards precision medicine driven by value-based systems Discusses future applications of precision medicine research using AI Other aspects covered in the book include regulatory insights, data analytics and visualization, types of biomarkers as well as the role of the patient in precision medicine