G. R. Gangadharan – författare

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

Cloud computing is the on-demand availability of computer system resources, especially data storage and computing power, without direct active management by the user. This book explores algorithms, protocols, and system design principles of key smart technologies including cloud computing and the internet of things.• Discusses the system design principles in cloud computing along with artificial intelligence, machine learning, and data analytics applications• Presents blockchain-based solutions, cyber-physical system applications, and deep learning approaches to solving practical problems• Highlights important concepts including the cloud of things architecture, cloud service management and virtualization, and resource management techniques• Covers advanced technologies including fog computing, edge computing, and distributed intelligence• Explores cloud-enabling technology, broadband networks and internet architecture, internet service providers (ISPs), and connectionless packet switching.The book is primarily written for graduate students, academic researchers, and professionals in the field of computer science and engineering, electrical engineering, and information technology.

“Ultimately, this is a remarkable book, a practical testimonial, and a comprehensive bibliography rolled into one. It is a single, bright sword cut across the various murky green IT topics. And if my mistakes and lessons learned through the green IT journey are any indication, this book will be used every day by folks interested in greening IT.”— Simon Y. Liu, Ph.D. & Ed.D., Editor-in-Chief, IT Professional Magazine, IEEE Computer Society, Director, U.S. National Agricultural LibraryThis book presents a holistic perspective on Green IT by discussing its various facets and showing how to strategically embrace itHarnessing Green IT: Principles and Practices examines various ways of making computing and information systems greener – environmentally sustainable -, as well as several means of using Information Technology (IT) as a tool and an enabler to improve the environmental sustainability. The book focuses on both greening of IT and greening by IT – complimentary approaches to attaining environmental sustainability.   In a single volume, it   comprehensively covers several key aspects of Green IT - green technologies, design, standards, maturity models, strategies and adoption -, and presents a clear approach to greening IT encompassing green use, green disposal, green design, and green manufacturing. It also illustrates how to strategically apply green IT in practice in several areas.Key Features: Presents a comprehensive coverage of key topics of importance and practical relevance  - green technologies, design, standards, maturity models, strategies and adoptionHighlights several useful approaches to embracing green IT in several areasFeatures chapters written by accomplished experts from industry and academia who have first-hand knowledge and expertise in specific areas of green ITPresents a set of review and discussion questions for each chapter that will help the readers to examine and explore the green IT domain furtherIncludes a companion website providing  resources for further information and presentation slidesThis book will be an invaluable resource for IT Professionals, academics, students, researchers, project leaders/managers, IT business executives, CIOs, CTOs and anyone interested in Green IT and harnessing it to enhance our environment.

This book discusses various machine learning & cognitive science approaches, presenting high-throughput research by experts in this area. Bringing together machine learning, cognitive science and other aspects of artificial intelligence to help provide a roadmap for future research on intelligent systems, the book is a valuable reference resource for students, researchers and industry practitioners wanting to keep abreast of recent developments in this dynamic, exciting and profitable research field. It is intended for postgraduate students, researchers, scholars and developers who are interested in machine learning and cognitive research, and is also suitable for senior undergraduate courses in related topics. Further, it is useful for practitioners dealing with advanced data processing, applied mathematicians, developers of software for agent-oriented systems and developers of embedded and real-time systems.

This book discusses various machine learning & cognitive science approaches, presenting high-throughput research by experts in this area. Bringing together machine learning, cognitive science and other aspects of artificial intelligence to help provide a roadmap for future research on intelligent systems, the book is a valuable reference resource for students, researchers and industry practitioners wanting to keep abreast of recent developments in this dynamic, exciting and profitable research field. It is intended for postgraduate students, researchers, scholars and developers who are interested in machine learning and cognitive research, and is also suitable for senior undergraduate courses in related topics. Further, it is useful for practitioners dealing with advanced data processing, applied mathematicians, developers of software for agent-oriented systems and developers of embedded and real-time systems.