This book focuses on recent advances and different research areas in multi-modal data fusion under healthcare informatics and seeks out theoretical, methodological, well-established and validated empirical work dealing with these different topics. This book brings together the latest industrial and academic progress, research, and development efforts within the rapidly maturing health informatics ecosystem. Contributions highlight emerging data fusion topics that support prospective healthcare applications. The book also presents various technologies and concerns regarding energy aware and secure sensors and how they can reduce energy consumption in health care applications. It also discusses the life cycle of sensor devices and protocols with the help of energy-aware design, production, and utilization, as well as the Internet of Things technologies such as tags, sensors, sensing networks, and Internet technologies. In a nutshell, this book gives a comprehensive overview of the state-of-the-art theories and techniques for massive data handling and access in medical data and smart health in IoT, and provides useful guidelines for the design of massive Internet of Medical Things.

Big data and the Internet of Things (IoT) play a vital role in prediction systems used in biological and medical applications, particularly for resolving issues related to disease biology at different scales. Modelling and integrating medical big data with the IoT helps in building effective prediction systems for automatic recommendations of diagnosis and treatment. The ability to mine, process, analyse, characterize, classify and cluster a variety and wide volume of medical data is a challenging task. There is a great demand for the design and development of methods dealing with capturing and automatically analysing medical data from imaging systems and IoT sensors. Addressing analytical and legal issues, and research on integration of big data analytics with respect to clinical practice and clinical utility, architectures and clustering techniques for IoT data processing, effective frameworks for removal of misclassified instances, practicality of big data analytics, methodological and technical issues, potential of Hadoop in managing healthcare data is the need of the hour. This book integrates different aspects used in the field of healthcare such as big data, IoT, soft computing, machine learning, augmented reality, organs on chip, personalized drugs, implantable electronics, integration of bio-interfaces, and wearable sensors, devices, practical body area network (BAN) and architectures of web systems. Key Features: Addresses various applications of Medical Big Data and Internet of Medical Things in real time environment Highlights recent innovations, designs, developments and topics of interest in machine learning techniques for classification of medical data Provides background and solutions to existing challenges in Medical Big Data and Internet of Medical Things Provides optimization techniques and programming models to parallelize the computationally intensive tasks in data mining of medical data Discusses interactions, advantages, limitations, challenges and future perspectives of IoT based remote healthcare monitoring systems. Includes data privacy and security analysis of cryptography methods for the Web of Medical Things (WoMT) Presents case studies on the next generation medical chair, electronic nose and pill cam are also presented.

In the field of healthcare technology, the Internet of Medical Things (IoMT) stands at the forefront of progress, revolutionizing patient care through advanced monitoring and treatment modalities. However, this digital transformation brings forth a new challenge— the vulnerability of sensitive medical data to cyber threats. Lightweight Digital Trust Architectures in the Internet of Medical Things (IoMT) examines ways to fortify IoMT against potential breaches through the exploration of these trust architectures. Delving deep into data privacy technologies, the book examines the implications of regulatory frameworks such as GDPR, HIPAA, and cybersecurity law. It assesses traditional security methods and considers innovative approaches, offering insights into certificate generation, digital identification, and the optimization of network protocols for secure data transmission.Lightweight Digital Trust Architectures in the Internet of Medical Things (IoMT) illuminates the path forward for IoMT security. Its objectives are multi-faceted: from unraveling the intricacies of the health chain to dissecting the role of lightweight cryptographic key agreement mechanisms in safeguarding medical data. The book grapples with the challenges and advantages of implementing compact cryptographic techniques in healthcare, particularly within the decentralized framework of IoMT. By exploring the potential of Federated Learning (FL) in bolstering privacy and improving healthcare outcomes, the book aims to equip researchers, healthcare professionals, and IT experts with valuable knowledge. Through real-world case studies, it endeavors to pave the way for a future where security and efficiency seamlessly integrate in IoMT.

This book provides a comprehensive exploration of the exciting intersection between technology and biology and delves into the principles, applications, and future directions of IoT in the realm of bioelectronics; it serves as both an introduction for those new to the field and as a detailed reference for experienced professionals seeking to deepen their knowledge. The rapid convergence of technology and biology heralds a new era of evolution in the Internet of Things (IoT), a transformative force enabling interconnected devices to communicate and operate with unparalleled synergy. This is particularly true in the groundbreaking field of bioelectronics, where the fusion of biological systems with electronic devices and IoT is reshaping the landscape of bioelectronics, promising to open up new frontiers in healthcare, diagnostics, and personalized medicine. This timely book explores the numerous ways in which IoT-enabled bioelectronic devices are used to monitor and enhance human health, from wearable sensors that track vital signs to implantable devices that can communicate with healthcare providers in real time. One central theme of this book is the transformative impact of IoT on healthcare. By enabling continuous, remote monitoring of patients, IoT technologies are not only improving the accuracy of diagnostics but also making healthcare more accessible and personalized. The book also addresses the critical issues of securing health records on the internet, which are of paramount importance as we increasingly rely on interconnected devices to collect and transmit sensitive health information. Additional attention is paid to the future directions of IoT in bioelectronics and the integration of innovative areas, such as artificial intelligence, machine learning, and big data analytics, in driving the development of ever more sophisticated and capable bioelectronic systems. Audience The target audience includes professionals, researchers, academics, and students involved in various fields related to bioelectronics, IoT, healthcare, biotechnology, engineering, and related disciplines.

The fast-growing number of patients suffering from various ailments has overstretched the carrying capacity of traditional healthcare systems. This handbook addresses the increased need to tackle security issues and preserve patients’ privacy concerns in Artificial Intelligence of Medical Things (AIoMT) devices and systems. Handbook of Security and Privacy of AI-Enabled Healthcare Systems and the Internet of Medical Things provides new insights into the deployment, application, management, and benefits of AIoMT by examining real-world scenarios. The handbook takes a critical look at existing security designs and offers solutions to revamp traditional security architecture, including the new design of effi cient intrusion detection algorithms, attack prevention techniques, and both cryptographic and noncryptographic solutions. The handbook goes on to discuss the critical security and privacy issues that affect all parties in the healthcare ecosystem and provides practical AI-based solutions. This handbook offers new and valuable information that will be highly beneficial to educators, researchers, and others.

IoMT Applications in Healthcare 5.0 introduces the concept of Healthcare 5.0, emphasizing the transformative potential of intelligent diagnosis, remote treatment, and smart health management. Sections define IoMT and its multi-tiered architecture, discussing its pivotal role in improving electronic device productivity in healthcare, explore IoMT applications in Healthcare 5.0, discuss remote physical therapy using IoMT in Healthcare 5.0, delve into the security and privacy considerations of IoMT in healthcare, and address how to overcome challenges and future directions in IoMT. The book concludes by summarizing key findings, providing a comprehensive overview of the discussed topics.Written by experts in the field, this is a key text for Biomedical Engineers, Data Scientists, and IoT Developers and specialists who work in the Internet of Medical Things. Graduate students of IoT engineering, biology, biostatistics, biomedical sciences, bioinformatics, health-informatics, and Interdisciplinary sciences will also find this an invaluable resource. - Provides an integrative and multidisciplinary approach to Healthcare 5.0 - Covers recent advancement in IoMT in transitioning healthcare - Discusses the evolution of healthcare and IoMT

Integrating intelligent systems and internet of things (IoT) into clinical health is crucial for enhancing patient care and operational efficiency. These technologies enable real-time data collection and analysis, facilitating personalized treatment plans and improving diagnostic accuracy. Together innovations can streamline workflows, reduce costs, and ultimately lead to better health outcomes for patients. It is essential to explore how these technologies can be implemented into healthcare. Intelligent Systems and IoT Applications in Clinical Health explores and elucidates the integration of AI, IoT, and blockchain technologies in healthcare. It advances current research by providing comprehensive insights into how these technologies can be leveraged to enhance patient care, improve operational efficiency, and ensure data security. Covering topics such as clinical healthcare, digital health experience, and monitoring systems, this book is an excellent resource for researchers, academicians, medical professionals, medical administrators, educators, graduate and postgraduate students, and more.

This book promotes and facilitates exchanges of research knowledge and findings across different disciplines on the design and investigation of machine learning-based data analytics of IoT infrastructures. This book is focused on the emerging trends, strategies, and applications of IoT in both healthcare and industry data analytics perspectives. The data analytics discussed are relevant for healthcare and industry to meet many technical challenges and issues that need to be addressed to realize this potential. The IoT discussed helps to design and develop the intelligent medical and industry solutions assisted by data analytics and machine learning. At the end of every chapter readers are encouraged to check their understanding by means of brainstorming summary, discussion, exercises and solutions. Focused on the emerging trends, strategies, and applications of IoT in both healthcare and industry data analytics perspectives; Promotes an exchange of research across disciplines on the design and investigation of machine learning-based data analytics of IoT infrastructures; Features case studies emphasizing social and research perspectives on cyber-physical systems, data analytics, intelligence and security.

This book gathers key advances in various areas related to using wireless Internet and wireless connectivity to achieve a more connected world. The world is now highly dependent on Internet connectivity. Even though some parts of the globe remain isolated, the smoothly running world all around us relies on Internet services for countless businesses and activities. During the COVID-19 pandemic, we have seen that exclusively relying on wired Internet would leave out a large part of our tech-savvy world. Hence, wireless connectivity is essential to anywhere, anytime connectivity. Further, in the event of a new pandemic or other disaster of global scale, wireless Internet offers a reliable way to keep us all connected. The contributors to this book, hailing from academia, industrial and research laboratories, report on the latest solutions, trends and technologies with the potential to make wireless Internet more reliable and secure for the years to come.