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Scrivener Publishing 100 Cummings Center, Suite 541J Beverly, MA 01915-6106
Artificial Intelligence and Soft Computing for Industrial Transformation
Series Editor: Dr. S. Balamurugan ([email protected])
Scope: Artificial Intelligence and Soft Computing Techniques play an impeccable role in industrial transformation. The topics to be covered in this book series include Artificial Intelligence, Machine Learning, Deep Learning, Neural Networks, Fuzzy Logic, Genetic Algorithms, Particle Swarm Optimization, Evolutionary Algorithms, Nature Inspired Algorithms, Simulated Annealing, Metaheuristics, Cuckoo Search, Firefly Optimization, Bio-inspired Algorithms, Ant Colony Optimization, Heuristic Search Techniques, Reinforcement Learning, Inductive Learning, Statistical Learning, Supervised and Unsupervised Learning, Association Learning and Clustering, Reasoning, Support Vector Machine, Differential Evolution Algorithms, Expert Systems, Neuro Fuzzy Hybrid Systems, Genetic Neuro Hybrid Systems, Genetic Fuzzy Hybrid Systems and other Hybridized Soft Computing Techniques and their applications for Industrial Transformation. The book series is aimed to provide comprehensive handbooks and reference books for the benefit of scientists, research scholars, students and industry professional working towards next generation industrial transformation.
Publishers at Scrivener
Martin Scrivener ([email protected]) Phillip Carmical ([email protected])
Advanced Healthcare Systems
Empowering Physicians with IoT-Enabled Technologies
Edited by
Rohit Tanwar,
S. Balamurugan,
R. K. Saini,
Vishal Bharti
and
Premkumar Chithaluru
This edition first published 2022 by John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA and Scrivener Publishing LLC, 100 Cummings Center, Suite 541J, Beverly, MA 01915, USA
© 2022 Scrivener Publishing LLC
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Library of Congress Cataloging-in-Publication Data
ISBN 978-1-119-76886-9
Cover image: Pixabay.Com
Cover design by Russell Richardson
Set in size of 11pt and Minion Pro by Manila Typesetting Company, Makati, Philippines
Printed in the USA
10 9 8 7 6 5 4 3 2 1
Preface
The applications and challenges of machine learning and artificial intelligence in the internet of things for healthcare applications are comprehensively covered in this book. Rapid developments in hardware, software and communication technologies have facilitated the emergence of internet-connected sensory devices that provide observations and data measurements from the physical world. The technology of internet-connected devices, referred to as the internet of things (IoT), continues to extend the current internet by providing connectivity and interactions between the physical and cyber worlds. The IoT is undoubtedly transforming the healthcare industry by redefining the space of devices and interaction of people in delivering healthcare solutions, resulting in applications that benefit patients, families, physicians, hospitals and insurance companies. The use of remote monitoring in the healthcare sector possible with IoT-enabled devices has the potential to keep patients safe and healthy, and empowers doctors to provide superlative care, thereby increasing patients’ engagement and satisfaction as a result of their interactions with doctors becoming easier and more efficient. Furthermore, remote monitoring of patients’ health helps reduce the length of hospital stays and prevents readmissions, in addition to having a major impact on reducing healthcare costs significantly and improving treatment outcomes.
In addition to increasing volume, the IoT generates big data characterized by its velocity in terms of time and location dependency, with a variety of multiple modalities and varying data quality. Intelligent processing and analysis of this big data are the keys to developing smart IoT applications, thereby making space for machine learning (ML) applications. Due to its computational tools that can substitute for human intelligence in the performance