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Efficient Data Handling for Massive Internet of Medical Things : Healthcare Data Analytics / edited by Chinmay Chakraborty, Uttam Ghosh, Vinayakumar Ravi, Yogesh Shelke.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- Internet of Things, Technology, Communications and Computing, 2199-1081
- Language:
- English
- Subjects (All):
- Cooperating objects (Computer systems).
- Telecommunication.
- Medical informatics.
- Biomedical engineering.
- Cyber-Physical Systems.
- Communications Engineering, Networks.
- Health Informatics.
- Biomedical Engineering and Bioengineering.
- Local Subjects:
- Cyber-Physical Systems.
- Communications Engineering, Networks.
- Health Informatics.
- Biomedical Engineering and Bioengineering.
- Physical Description:
- 1 online resource (XIV, 388 pages) : 100 illustrations
- Edition:
- 1st ed. 2021.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2021.
- System Details:
- text file PDF
- 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.
- Contents:
- 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's 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 and Solutions.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-030-66633-0
- 9783030666330
- Access Restriction:
- Restricted for use by site license.
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