Efficient data handling for massive Internet of medical things : healthcare data analytics / Chinmay Chakraborty, Uttam Ghosh, Vinayakumar Ravi, Yogesh Shelke, editors.
Chakraborty, Chinmay, 1984- editor.; Ghosh, Uttam, editor.; Ravi, Vinayakumar, editor.; Shelke, Yogesh, editor.
2021
R859.7.I58
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Title
Efficient data handling for massive Internet of medical things : healthcare data analytics / Chinmay Chakraborty, Uttam Ghosh, Vinayakumar Ravi, Yogesh Shelke, editors.
ISBN
9783030666330 (electronic bk.)
3030666336 (electronic bk.)
9783030666323
3030666328
DOI
https://doi.org/10.1007/978-3-030-66633-0
Published
Cham : Springer, [2021]
Copyright
©2021
Language
English
Description
1 online resource : illustrations
Item Number
10.1007/978-3-030-66633-0 doi
Call Number
R859.7.I58
Dewey Decimal Classification
610.285
Summary
This book focuses on recent advances and different research areas in multi-modal data fusion under healthcare informatics and seeks out theoretical, methodological, well-established and validated empirical work dealing with these different topics. This book brings together the latest industrial and academic progress, research, and development efforts within the rapidly maturing health informatics ecosystem. Contributions highlight emerging data fusion topics that support prospective healthcare applications. The book also presents various technologies and concerns regarding energy aware and secure sensors and how they can reduce energy consumption in health care applications. It also discusses the life cycle of sensor devices and protocols with the help of energy-aware design, production, and utilization, as well as the Internet of Things technologies such as tags, sensors, sensing networks, and Internet technologies. In a nutshell, this book gives a comprehensive overview of the state-of-the-art theories and techniques for massive data handling and access in medical data and smart health in IoT, and provides useful guidelines for the design of massive Internet of Medical Things. Presents a rigorous introduction to theoretical foundations and practical solutions for Internet of Medical Things; Covers data handling, intelligence and security and related issues to guide the massive data handling techniques for healthcare; Includes examples and case studies for further study for academics, researchers, and professionals.
Note
Includes index.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed September 15, 2021).
Added Author
Chakraborty, Chinmay, 1984- editor.
Ghosh, Uttam, editor.
Ravi, Vinayakumar, editor.
Shelke, Yogesh, editor.
Series
Internet of things. 2199-1081
Available in Other Form
Efficient data handling for massive Internet of medical things.
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Chapter 1. An Overview of the Internet of Medical Things and its Modern Perspective
Chapter 2. Big medical data analytics under Internet of Things
Chapter 3. Big Medical Data Analytics using Sensor Technology
Chapter 4. Smart Healthcare Technologies for Massive Internet of Medical Things
Chapter 5. Sensor Informatics of IoT, AR/VR, and MR in Healthcare Applications
Chapter 6. Body Sensor Networks as emerging trends of technology in health care system: Challenges and Future
Chapter 7. Smart sensors technologies for Healthcare system
Chapter 8. Cloud and IoMT-based Big Data Analytics system during COVID-19 pandemic
Chapter 9. Remote human
health and activities monitoring using wearable sensor based system- a review
Chapter 10. A Healthcare Resource Management Optimization Framework for ECG Biomedical Sensors
Chapter 11. Diabetes Detection and Sensor Based Continuous Glucose Monitoring
A Deep Learning Approach
Chapter 12. Sensing the Mind-An Exploratory Study About Sensors used in E-Health and M-Health Applications for Diagnosis of Mental Health Condition
Chapter 13. Role of Sensors, Devices and Technology for Detection of COVID-19 Virus
Chapter 14. Implementation of Internet of Medical Things (IoMT): Clinical and Policy Implications
Chapter 15. Applicability of Blockchain Technology in Healthcare Industry: Applications, Challenges & Solutions.

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