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IoT-Based Data Analytics for the Healthcare Industry - 1st Edition - ISBN: 9780128214725

IoT-Based Data Analytics for the Healthcare Industry

1st Edition

Techniques and Applications

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Editors: Sanjay Kumar Singh Ravi Shankar Singh Anil Kumar Pandey Sandeep Udmale Ankit Chaudhary
Paperback ISBN: 9780128214725
Imprint: Academic Press
Published Date: 1st December 2020
Page Count: 370
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Table of Contents

Section I Health IoT Data Analytics
1. The internet of things in healthcare industry
2. IoT Healthcare Architecture
3. Characteristics of IoT Health Data
4. Health data analytics using Internet of Things
5. Computational Intelligence in Internet of Things for Future Healthcare Applications

Section II IoT Services in Health Industry
6. IoT Services in Health Industry with Fog/Edge and Cloud Computing
7. Multi Criteria Decision Making in Health Informatics using IoT
8. A Research Review on Semantic Interoperability issues in Electronic Health Record System in Medical Healthcare
9. IoT for Health Insurance companies
10. Security and privacy challenges in Healthcare using internet of things
11. A secure blockchain based solution for harnessing the future of smart healthcare

Section III Applications of IoT for Humans
12. Designing an effective e-healthcare system using Internet of Things
13. Heart rate monitoring system using internet of things
14. A Smart Hand for VI: Resource Constrained Assistive Technology for Visually Impaired
15. Internet of Things in Pain Monitoring System

Section IV Applications of IoT for Animals
16. Applications of Internet of Things in Animal Science
17. Internet of Animal Health Things: A New Frontier in Animal Biometrics and Data Analytics Research
18. IoT in Controlling and Preventing Spread of Infectious Diseases
19. Tele-Medicine System for Animals using Low Bandwidth Cellular Communication past COVID-19
20. Internet of Things and Other Emerging Technologies in Digital Pathology


IoT Based Data Analytics for the Healthcare Industry: Techniques and Applications explores recent advances in the analysis of healthcare industry data through IoT data analytics. The book covers the analysis of ubiquitous data generated by the healthcare industry, from a wide range of sources, including patients, doctors, hospitals, and health insurance companies. The book provides AI solutions and support for healthcare industry end-users who need to analyze and manipulate this vast amount of data. These solutions feature deep learning and a wide range of intelligent methods, including simulated annealing, tabu search, genetic algorithm, ant colony optimization, and particle swarm optimization.

The book also explores challenges, opportunities, and future research directions, and discusses the data collection and pre-processing stages, challenges and issues in data collection, data handling, and data collection set-up. Healthcare industry data or streaming data generated by ubiquitous sensors cocooned into the IoT requires advanced analytics to transform data into information. With advances in computing power, communications, and techniques for data acquisition, the need for advanced data analytics is in high demand. 

Key Features

  • Provides state-of-art methods and current trends in data analytics for the healthcare industry
  • Addresses the top concerns in the healthcare industry using IoT and data analytics, and machine learning and deep learning techniques
  • Discusses several potential AI techniques developed using IoT for the healthcare industry
  • Explores challenges, opportunities, and future research directions, and discusses the data collection and pre-processing stages


Researchers, academicians, and experts working in IoT in Health Industry, Health Management, Biomedical Engineering, Medical Applications, and Analysis, Application of Machine Learning and Deep Learning in Health, Big data-based learning techniques, Integrated approach of IoT and Artificial Intelligence for the Healthcare industry. Scientists, Researchers, Practitioners, Professionals from Government and Cloud-centric applications-based industries as well as Industries planning to deploy advanced analytics (DL) on Industrial Data


No. of pages:
© Academic Press 2021
1st December 2020
Academic Press
Paperback ISBN:

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About the Editors

Sanjay Kumar Singh

Sanjay Kumar Singh received the M.Tech. degree in computer applications from the IIT (ISM), Dhanbad, India, in 1995, and the Ph.D. degree in computer science and engineering from Uttar Pradesh Technical University, Lucknow, India, in 2004. He is currently a Professor with the Department of Computer Science and Engineering, IIT (BHU) Varanasi, Varanasi, India. He has authored or coauthored more than 150 national and international journal publications, book chapters, and conference papers. His current research interests include biometrics, computer vision, image and video processing, pattern recognition, and artificial intelligence. Dr. Singh is a member of the ACM and Computer Society of India. He is a Guest Editorial Board Member, a reviewer for various journals, and a TPC Member for various conferences.

Affiliations and Expertise

IIT (ISM), Dhanbad, India

Ravi Shankar Singh

Ravi Shankar Singh is Associate Professor at Department of Computer Science and Engineering, IIT (BHU), Varanasi, India. He received his B. Tech., M. Tech. and Ph.D., all in Computer Science and Engineering. His research interests include Algorithms and High Performance Computing. He has authored several research publications and one book. He has conducted many workshops/seminars in various areas of Computer Science and Engineering. He has served as reviewer of many reputed international journals.

Affiliations and Expertise

IIT (BHU), Varanasi, India

Anil Kumar Pandey

Anil Kumar Pandey completed his master degree in Mathematics and Postgraduate Diploma in Computer Science Application. He has done Master in Computer Science and Computer Application. He has done Ph.D in Computer Science He is working as Programmer in Banaras Hindu University. He has about 32 years experience of teaching and Research. Dr. Pandey have exposure of community based data analysis. He has assisted more than 20 Ph.D. students in Science, Humanities and Medicine. He has expertise in relational data base management system, AI and machine learning and IOT.

Affiliations and Expertise

Banaras Hindu University, India

Sandeep Udmale

Sandeep S. Udmale received the B.E. degree in computer engineering from the University of Mumbai, Mumbai, India, in 2006, and the M.Tech. degree in computer engineering from Dr. Babasaheb Ambedkar Technological University, Raigad, India, in 2009. He is currently pursuing the Ph.D. degree in computer science and engineering with IIT (BHU) Varanasi, Varanasi, India. He is currently an Assistant Professor with the Department of Computer Engineering and Information Technology, Veermata Jijabai Technological Institute, Mumbai, India. His current research interests include machine learning, data science, and optimization and pattern analysis. Mr. Udmale is a member of the ACM and Computer Society of India.

Affiliations and Expertise

University of Mumbai, Mumbai, India

Ankit Chaudhary

Ankit Chaudhary is an Assistant Professor at Dept. of Computer Science, The University of Missouri at Saint Louis. He received his B.Tech., M.Eng. and Ph.D., all in Computer Engineering. His research interests include Data Science, Computer Vision and Cyber Security. He has authored seventy research publications and two books. He is an Associate Editor of Computers and Electrical Engineering, an Elsevier Journal. Also he is on the Editorial Board of several International Journals and serves as Program Chair/TPC in many Conferences. He served as federal grant reviewer and also a reviewer for Journals including IEEE Trans. on Image Processing, IEEE Trans. on Multimedia, IEEE Trans. on Visualization & Computer Graphics, IET Computer Vision, IET Image Processing, ACM Trans. on Interactive Intelligent Systems, Signal Image and Video Processing, Robotics and Autonomous Systems.

Affiliations and Expertise

The University of Missouri, Saint Louis, USA