A. Prasanth – författare

Cognitive Computing for Internet of Medical Things (IoMT) offers a complete assessment of the present scenario, role, challenges, technologies, and impact of IoMT-enabled smart healthcare systems. It contains chapters discussing various biomedical applications under the umbrella of the IoMT.

Key Features

This book is primarily aimed at graduates, researchers and academicians working in the area of development of the application of the of the application of the IoT in smart healthcare. Industry professionals will also find this book helpful.

Cognitive Computing for Internet of Medical Things (IoMT) offers a complete assessment of the present scenario, role, challenges, technologies, and impact of IoMT-enabled smart healthcare systems. It contains chapters discussing various biomedical applications under the umbrella of the IoMT.

Key Features

This book is primarily aimed at graduates, researchers and academicians working in the area of development of the application of the of the application of the IoT in smart healthcare. Industry professionals will also find this book helpful.

Technological Advancement in Internet of Medical Things and Blockchain for Personalized Healthcare presents an overview of the innovative concepts, technologies, and various biomedical applications of the Internet of Medical Things (IoMT).

Features:

• Provides insights into smart contracts, healthcare monitoring equipment, and the next generation of Internet of Things sensors to improve adherence to chronic disease management programs and patient health.

• Discusses the IoMT for personalized healthcare, security, and privacy issues of the IoMT in the healthcare sector.

• Elaborates on the opportunities and challenges of blockchain technology in the healthcare system.

• Focuses on the convergence of the IoMT and blockchain for emerging personalized healthcare systems.

• Presents techniques and methods to secure IoMT devices to protect them from cyberattacks.

This book is primarily written for graduate students and academic researchers working in the fields of computer science and engineering, biomedical engineering, and electrical engineering.

Technological Advancement in Internet of Medical Things and Blockchain for Personalized Healthcare presents an overview of the innovative concepts, technologies, and various biomedical applications of the Internet of Medical Things (IoMT).

Features:

• Provides insights into smart contracts, healthcare monitoring equipment, and the next generation of Internet of Things sensors to improve adherence to chronic disease management programs and patient health.

• Discusses the IoMT for personalized healthcare, security, and privacy issues of the IoMT in the healthcare sector.

• Elaborates on the opportunities and challenges of blockchain technology in the healthcare system.

• Focuses on the convergence of the IoMT and blockchain for emerging personalized healthcare systems.

• Presents techniques and methods to secure IoMT devices to protect them from cyberattacks.

This book is primarily written for graduate students and academic researchers working in the fields of computer science and engineering, biomedical engineering, and electrical engineering.

This book delves into the history of biometrics, the different systems that have been developed to date, problems that have arisen from these systems, the necessity of AI-based biometrics systems, different AI techniques developed to date (including machine learning, deep learning, natural language processing, and pattern recognition), their potential uses and applications, security and privacy issues in AI-based Biometric systems, current trends in AI-based biometrics, and presents case studies of AI-based biometrics.

This book delves into the history of biometrics, the different systems that have been developed to date, problems that have arisen from these systems, the necessity of AI-based biometrics systems, different AI techniques developed to date (including machine learning, deep learning, natural language processing, and pattern recognition), their potential uses and applications, security and privacy issues in AI-based Biometric systems, current trends in AI-based biometrics, and presents case studies of AI-based biometrics.

A digital twin, in simple words, is a virtual model such that it accurately reflects an object or data. The usage of blockchain, along with the amalgamation of AI and big data, exploits the potential of the data generated from current industrial practices, giving rise to the digital twin model that can benefit from blockchain technology. This new book addresses this technology to actualize secure systems, networks, and environments. It details the modeling and simulation of blockchain-based digital twins and explores various applications along with challenges and opportunities. The volume explores its application in several industries, including healthcare, agriculture, and mechanics.

A digital twin, in simple words, is a virtual model such that it accurately reflects an object or data. The usage of blockchain, along with the amalgamation of AI and big data, exploits the potential of the data generated from current industrial practices, giving rise to the digital twin model that can benefit from blockchain technology. This new book addresses this technology to actualize secure systems, networks, and environments. It details the modeling and simulation of blockchain-based digital twins and explores various applications along with challenges and opportunities. The volume explores its application in several industries, including healthcare, agriculture, and mechanics.

This book explores the applications and advancements of federated learning across diverse sectors, focusing on its integration with cutting- edge technologies like Internet of Things (IoT), artificial intelligence (AI), blockchain, and digital twins. Real-world examples and case studies illustrate federated learning’s role in healthcare, smart cities, and maritime applications while addressing critical concerns such as security. It provides insights into federated learning’s transformative potential, offering practical strategies for intelligent systems and sustainable environments.

The book particularly:

• Focuses on the federated learning–based model optimization, addressing the significance of IoT and federated learning in the evolution of intelligent systems for various applications;

• Describes the different optimization techniques of federated learning systems from a practical point of view;

• Highlights economic, social, and environmental impacts of smart technologies and provides insights into IoT, 5G/ 6G communication, and computing standards;

• Provides analysis of the use cases of federated learning regarding the development of IoT, AI, blockchain, digital twins;

• Offers strategies for overcoming challenges associated with federated learning systems, including connectivity, computation, threats, privacy, and security issues.

It covers fundamental concepts, practical implementations, and trends, to serve as a reference resource for professionals and researchers in the field.

This book explores the applications and advancements of federated learning across diverse sectors, focusing on its integration with cutting- edge technologies like Internet of Things (IoT), artificial intelligence (AI), blockchain, and digital twins. Real-world examples and case studies illustrate federated learning’s role in healthcare, smart cities, and maritime applications while addressing critical concerns such as security. It provides insights into federated learning’s transformative potential, offering practical strategies for intelligent systems and sustainable environments.

The book particularly:

• Focuses on the federated learning–based model optimization, addressing the significance of IoT and federated learning in the evolution of intelligent systems for various applications;

• Describes the different optimization techniques of federated learning systems from a practical point of view;

• Highlights economic, social, and environmental impacts of smart technologies and provides insights into IoT, 5G/ 6G communication, and computing standards;

• Provides analysis of the use cases of federated learning regarding the development of IoT, AI, blockchain, digital twins;

• Offers strategies for overcoming challenges associated with federated learning systems, including connectivity, computation, threats, privacy, and security issues.

It covers fundamental concepts, practical implementations, and trends, to serve as a reference resource for professionals and researchers in the field.