5G IoT and Edge Computing for Smart Healthcare
- 1st Edition - March 29, 2022
- Editors: Akash Kumar Bhoi, Victor Hugo Costa de Albuquerque, Samarendra Nath Sur, Paolo Barsocchi
- Language: English
- Paperback ISBN:9 7 8 - 0 - 3 2 3 - 9 0 5 4 8 - 0
- eBook ISBN:9 7 8 - 0 - 3 2 3 - 9 0 6 6 4 - 7
5G IoT and Edge Computing for Smart Healthcare addresses the importance of a 5G IoT and Edge-Cognitive-Computing-based system for the successful implementation and realizati… Read more
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Request a sales quote5G IoT and Edge Computing for Smart Healthcare addresses the importance of a 5G IoT and Edge-Cognitive-Computing-based system for the successful implementation and realization of a smart-healthcare system. The book provides insights on 5G technologies, along with intelligent processing algorithms/processors that have been adopted for processing the medical data that would assist in addressing the challenges in computer-aided diagnosis and clinical risk analysis on a real-time basis. Each chapter is self-sufficient, solving real-time problems through novel approaches that help the audience acquire the right knowledge.
With the progressive development of medical and communication - computer technologies, the healthcare system has seen a tremendous opportunity to support the demand of today's new requirements.
- Focuses on the advancement of 5G in terms of its security and privacy aspects, which is very important in health care systems
- Address advancements in signal processing and, more specifically, the cognitive computing algorithm to make the system more real-time
- Gives insights into various information-processing models and the architecture of layers to realize a 5G based smart health care system
- Cover image
- Title page
- Table of Contents
- Copyright
- List of contributors
- Chapter 1. Edge-IoMT-based enabled architecture for smart healthcare system
- Abstract
- 1.1 Introduction
- 1.2 Applications of an IoMT-based system in the healthcare industry
- 1.3 Application of edge computing in smart healthcare systems
- 1.4 Challenges of using edge computing with IoMT-based system in smart healthcare system
- 1.5 The framework for edge-IoMT-based smart healthcare system
- 1.6 Case study for the application of edge-IoMT-based systems enabled for the diagnosis of diabetes mellitus
- 1.7 Future prospects of edge computing for internet of medical things
- 1.8 Conclusions and future research directions
- References
- Chapter 2. Physical layer architecture of 5G enabled IoT/IoMT system
- Abstract
- 2.1 Architecture of IoT/IoMT system
- 2.2 Consideration of uplink healthcare IoT system relying on NOMA
- 2.3 Conclusions
- References
- Chapter 3. HetNet/M2M/D2D communication in 5G technologies
- Abstract
- 3.1 Introduction
- 3.2 Heterogenous networks in the era of 5G
- 3.3 Device-to-Device communication in 5G HetNets
- 3.4 Machine-to-Machine communication in 5G HetNets
- 3.5 Heterogeneity and interoperability
- 3.6 Research issues and challenges
- 3.7 Smart healthcare using 5G5G Inter of Things: a case-study
- 3.8 Conclusions
- References
- Chapter 4. An overview of low power hardware architecture for edge computing devices
- Abstract
- 4.1 Introduction
- 4.2 Basic concepts of cloud, fog and edge computing infrastructure
- 4.3 Low power hardware architecture for edge computing devices
- 4.4 Examples of edge computing devices
- 4.5 Edge computing for intelligent healthcare applications
- 4.6 Impact of edge computing, Internet of Things and 5G on smart healthcare systems
- 4.7 Conclusion and future scope of research
- References
- Chapter 5. Convergent network architecture of 5G and MEC
- Abstract
- 5.1 Introduction
- 5.2 Technical overview on 5G network with MEC
- 5.3 Convergent network architecture for 5G with MEC
- 5.4 Current research in 5G with MEC
- 5.5 Challenges and issues in implementation of MEC
- 5.6 Conclusions
- References
- Chapter 6. An efficient lightweight speck technique for edge-IoT-based smart healthcare systems
- Abstract
- 6.1 Introduction
- 6.2 The Internet of Things in smart healthcare system
- 6.3 Application of edge computing in smart healthcare system
- 6.4 Application of encryptions algorithm in smart healthcare system
- 6.5 Results and discussion
- 6.6 Conclusions and future research directions
- References
- Chapter 7. Deep learning approaches for the cardiovascular disease diagnosis using smartphone
- Abstract
- 7.1 Introduction
- 7.2 Disease diagnosis and treatment
- 7.3 Deep learning approaches for the disease diagnosis and treatment
- 7.4 Case study of a smartphone-based Atrial Fibrillation Detection
- 7.5 Discussion
- 7.6 Conclusion
- References
- Chapter 8. Advanced pattern recognition tools for disease diagnosis
- Abstract
- 8.1 Introduction
- 8.2 Disease diagnosis
- 8.3 Pattern recognition tools for the disease diagnosis
- 8.4 Case study of COVID-19 detection
- 8.5 Discussion
- 8.6 Conclusions
- References
- Chapter 9. Brain-computer interface in Internet of Things environment
- Abstract
- 9.1 Introduction
- 9.2 Brain-computer interface classification
- 9.3 Key elements of BCI
- 9.4 Modalities of BCI
- 9.5 Computational intelligence methods in BCI/BMI
- 9.6 Online and offline BCI applications
- 9.7 BCI for the Internet of Things
- 9.8 Secure brain-brain communication
- 9.9 Summary and conclusion
- 9.10 Future research directions and challenges
- Abbreviations
- References
- Chapter 10. Early detection of COVID-19 pneumonia based on ground-glass opacity (GGO) features of computerized tomography (CT) angiography
- Abstract
- 10.1 Introduction
- 10.2 Background
- 10.3 Materials and methods
- 10.4 Results and analysis
- 10.5 Conclusion
- References
- Chapter 11. Applications of wearable technologies in healthcare: an analytical study
- Abstract
- 11.1 Introduction
- 11.2 Application of wearable devices
- 11.3 The importance of wearable technology in healthcare
- 11.4 Current scenario of wearable computing
- 11.5 The wearable working procedure
- 11.6 Wearables in healthcare
- 11.7 State-of-the-art implementation of wearables
- 11.8 Future scope and conclusion
- References
- Index
- No. of pages: 324
- Language: English
- Edition: 1
- Published: March 29, 2022
- Imprint: Academic Press
- Paperback ISBN: 9780323905480
- eBook ISBN: 9780323906647
AB
Akash Kumar Bhoi
Dr. Akash Kumar Bhoi, holds degrees in B.Tech, M.Tech, and Ph.D., and has been contributing to the field of computer science and engineering. He assumed the role of Assistant Professor (Research) at the Department of Computer Science and Engineering, Sikkim Manipal Institute of Technology (SMIT), India, in 2012. In addition to his academic responsibilities, Dr. Bhoi extended his expertise during a research tenure as a Research Associate at the Wireless Networks (WN) Research Laboratory, Institute of Information Science and Technologies, National Research Council (ISTI-CRN) in Pisa, Italy, from January 20, 2021, to January 19, 2022. Dr. Bhoi further serves as the University Ph.D. Course Coordinator for "Research & Publication Ethics (RPE)." He is an active member of professional organizations such as IEEE, ISEIS, and IAENG, and holds associate membership with IEI and UACEE. He plays a significant role as an editorial board member and reviewer for esteemed Indian and international journals and regularly contributes as a reviewer. His research expertise encompasses a wide array of domains, including Biomedical Technologies, the Internet of Things, Computational Intelligence, Antenna technology, and Renewable Energy. Dr. Bhoi has a notable publication record, with multiple papers featured in national and international journals and conferences. Dr. Bhoi has played a pivotal role in the organization of international conferences and workshops, offering his expertise as a key contributor. Currently, he is involved in editing several books in collaboration with international publishers
Vd
Victor Hugo Costa de Albuquerque
SS
Samarendra Nath Sur
PB