Security implementation is crucial in the Internet of Medical Things (IoMT) as it ensures the protection of sensitive medical data and prevents unauthorized access to or manipulation of devices and systems. This book covers different aspects of security implementations and challenges in IoMT and aims to bring researchers together to contribute their findings to recommend new methodologies and feasible solutions for implementing security and novel architectures in artificial intelligence, machine learning, and data science in the field of healthcare and IoT. IoMT includes a wide range of connected medical devices and systems, such as wearable devices, medical sensors, and electronic health records, that collect, store, and share sensitive medical information. Without proper security measures, this information could be compromised, leading to serious privacy breaches, financial fraud, and even physical harm to patients.

In recent years, the Medical Internet of Things (MIoT) has emerged as one of the most helpful technological gifts to mankind. With the incredible development in data science, big data technologies, IoT and embedded systems, it is now possible to collect a huge amount of sensitive and personal data, compile it and store it through cloud or edge computing techniques. However, important concerns remain about security and privacy, the preservation of sensitive and personal data, and the efficient transfer, storage and processing of MIoT-based data. Medical Internet of Things: Techniques, Practices and Applications is an attempt to explore new ideas and novel techniques in the area of MIoT. The book is composed of fifteen chapters discussing basic concepts, issues, challenges, case studies and applications in MIoT. This book offers novel advances and applications of MIoT in a precise and clear manner to the research community to achieve in-depth knowledge in the field. This book will help those interested in the field as well as researchers to gain insight into different concepts and their importance in multifaceted applications of real life. This has been done to make the book more flexible and to stimulate further interest in the topic. Features: A systematic overview of concepts in Medical Internet of Things (MIoT) is included. Recent research and some pointers on future advancements in MIoT are discussed. Examples and case studies are included. It is written in an easy-to-understand style with the help of numerous figures and datasets. This book serves as a reference book for scientific investigators who are interested in working on MIoT, as well as researchers developing methodology in this field. It may also be used as a textbook for postgraduate-level courses in computer science or information technology.

This book looks at the growing segment of Internet of Things technology (IoT) known as Internet of Medical Things (IoMT), an automated system that aids in bridging the gap between isolated and rural communities and the critical healthcare services that are available in more populated and urban areas. Many technological aspects of IoMT are still being researched and developed, with the objective of minimizing the cost and improving the performance of the overall healthcare system. This book focuses on innovative IoMT methods and solutions being developed for use in the application of healthcare services, including post-surgery care, virtual home assistance, smart real-time patient monitoring, implantable sensors and cameras, and diagnosis and treatment planning. It also examines critical issues around the technology, such as security vulnerabilities, IoMT machine learning approaches, and medical data compression for lossless data transmission and archiving. Internet of Medical Things is a valuable reference for researchers, students, and postgraduates working in biomedical, electronics, and communications engineering, as well as practicing healthcare professionals.

Security implementation is crucial in the Internet of Medical Things (IoMT) as it ensures the protection of sensitive medical data and prevents unauthorized access to or manipulation of devices and systems. This book covers different aspects of security implementations and challenges in IoMT and aims to bring researchers together to contribute their findings to recommend new methodologies and feasible solutions for implementing security and novel architectures in artificial intelligence, machine learning, and data science in the field of healthcare and IoT. IoMT includes a wide range of connected medical devices and systems, such as wearable devices, medical sensors, and electronic health records, that collect, store, and share sensitive medical information. Without proper security measures, this information could be compromised, leading to serious privacy breaches, financial fraud, and even physical harm to patients.

SMART HEALTHCARE SYSTEM DESIGN This book deeply discusses the major challenges and issues for security and privacy aspects of smart health-care systems. The Internet-of-Things (IoT) has emerged as a powerful and promising technology, and though it has significant technological, social, and economic impacts, it also poses new security and privacy challenges. Compared with the traditional internet, the IoT has various embedded devices, mobile devices, a server, and the cloud, with different capabilities to support multiple services. The pervasiveness of these devices represents a huge attack surface and, since the IoT connects cyberspace to physical space, known as a cyber-physical system, IoT attacks not only have an impact on information systems, but also affect physical infrastructure, the environment, and even human security. The purpose of this book is to help achieve a better integration between the work of researchers and practitioners in a single medium for capturing state-of-the-art IoT solutions in healthcare applications, and to address how to improve the proficiency of wireless sensor networks (WSNs) in healthcare. It explores possible automated solutions in everyday life, including the structures of healthcare systems built to handle large amounts of data, thereby improving clinical decisions. The 14 separate chapters address various aspects of the IoT system, such as design challenges, theory, various protocols, implementation issues, as well as several case studies. Smart Healthcare System Design covers the introduction, development, and applications of smart healthcare models that represent the current state-of-the-art of various domains. The primary focus is on theory, algorithms, and their implementation targeted at real-world problems. It will deal with different applications to give the practitioner a flavor of how IoT architectures are designed and introduced into various situations. Audience: Researchers and industry engineers in information technology, artificial intelligence, cyber security, as well as designers of healthcare systems, will find this book very valuable.

Machine Learning and the Internet of Medical Things in Healthcare discusses the applications and challenges of machine learning for healthcare applications. The book provides a platform for presenting machine learning-enabled healthcare techniques and offers a mathematical and conceptual background of the latest technology. It describes machine learning techniques along with the emerging platform of the Internet of Medical Things used by practitioners and researchers worldwide. The book includes deep feed forward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology. It also presents the concepts of the Internet of Things, the set of technologies that develops traditional devices into smart devices. Finally, the book offers research perspectives, covering the convergence of machine learning and IoT. It also presents the application of these technologies in the development of healthcare frameworks. - Provides an introduction to the Internet of Medical Things through the principles and applications of machine learning - Explains the functions and applications of machine learning in various applications such as ultrasound imaging, biomedical signal processing, robotics, and biomechatronics - Includes coverage of the evolution of healthcare applications with machine learning, including Clinical Decision Support Systems, artificial intelligence in biomedical engineering, and AI-enabled connected health informatics, supported by real-world case studies

INTERNET OF HEALTHCARE THINGS The book addresses privacy and security issues providing solutions through authentication and authorization mechanisms, blockchain, fog computing, machine learning algorithms, so that machine learning-enabled IoT devices can deliver information concealed in data for fast, computerized responses and enhanced decision-making. The main objective of this book is to motivate healthcare providers to use telemedicine facilities for monitoring patients in urban and rural areas and gather clinical data for further research. To this end, it provides an overview of the Internet of Healthcare Things (IoHT) and discusses one of the major threats posed by it, which is the data security and data privacy of health records. Another major threat is the combination of numerous devices and protocols, precision time, data overloading, etc. In the IoHT, multiple devices are connected and communicate through certain protocols. Therefore, the application of emerging technologies to mitigate these threats and provide secure data communication over the network is discussed. This book also discusses the integration of machine learning with the IoHT for analyzing huge amounts of data for predicting diseases more accurately. Case studies are also given to verify the concepts presented in the book. Audience Researchers and industry engineers in computer science, artificial intelligence, healthcare sector, IT professionals, network administrators, cybersecurity experts.