5G IoT and Edge Computing for Smart Healthcare

5G IoT and Edge Computing for Smart Healthcare

1st Edition - March 29, 2022

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  • Editors: Akash Bhoi, Victor de Albuquerque, Samarendra Sur, Paolo Barsocchi
  • eBook ISBN: 9780323906647
  • Paperback ISBN: 9780323905480

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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 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.  

Key Features

  • 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


Industry, professionals, academicians and researchers and post graduate students involved in Electrical engineering, Communication Engineering, Computer Engineering, Data Engineering, Biomedical Engineering and allied field of 5G physical layer design, Data processing, Predictive analysis, Machine Learning Algorithms, Communication Networking, cognitive algorithm and Computational Intelligence in data engineering systems. Electronics and communication engineering, Computer Science Engineering, Data Science Engineering and Machine Learning based engineering

Table of Contents

  • 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

Product details

  • No. of pages: 324
  • Language: English
  • Copyright: © Academic Press 2022
  • Published: March 29, 2022
  • Imprint: Academic Press
  • eBook ISBN: 9780323906647
  • Paperback ISBN: 9780323905480

About the Editors

Akash Bhoi

Akash Kumar Bhoi [B.Tech, M.Tech, Ph.D.] is working as Assistant Professor (Research) in the Department of Computer Science and Engineering at Sikkim Manipal Institute of Technology (SMIT), India, since 2012. He is also working (Period: 20th Jan 2021 - 19th Jan 2022) as Research Associate at Wireless Networks (WN) Research Laboratory, Institute of Information Science and Technologies, National Research Council (ISTI-CRN) Pisa, Italy. He is a University Ph.D. Course Coordinator for “Research & Publication Ethics (RPE).” He is a member of IEEE, ISEIS, and IAENG, an associate member of IEI, UACEE, and an editorial board member reviewer of Indian and international journals. He is also a regular reviewer of repute journals, namely IEEE, Springer, Elsevier, Taylor and Francis, Inderscience, etc. His research areas are Biomedical Technologies, the Internet of Things, Computational Intelligence, Antenna, Renewable Energy. He has published several papers in national and international journals and conferences. He has 100+ documents registered in the Scopus database by the year 2020. He has also served on numerous organizing panels for international conferences and workshops. He is currently editing several books with Springer Nature, Elsevier and Routledge & CRC Press. He is also serving as Guest editor for special issues of the journal like Springer Nature and Inderscience.

Affiliations and Expertise

Assistant Professor, Department of Computer Science and Engineering, Sikkim Manipal Institute of Technology, Sikkim Manipal University, Sikkim, India

Victor de Albuquerque

Victor Hugo C. de Albuquerque [M’17, SM’19] is a collaborator Professor and senior researcher at the Graduate Program on Teleinformatics Engineering at the Federal University of Ceará, Brazil, and at the Graduate Program on Telecommunication Engineering, Federal Institute of Education, Science and Technology of Ceará, Fortaleza/CE, Brazil. He has a Ph.D in Mechanical Engineering from the Federal University of Paraíba (UFPB, 2010), an MSc in Teleinformatics Engineering from the Federal University of Ceará (UFC, 2007), and he graduated in Mechatronics Engineering at the Federal Center of Technological Education of Ceará (CEFETCE, 2006). He is a specialist, mainly, in Image Data Science, IoT, Machine/Deep Learning, Pattern Recognition, Robotic.

Affiliations and Expertise

Professor and Senior Researcher, Federal University of Ceara, Fortaleza, Graduate Program on Teleinformatics Engineering,Fortaleza/CE, Brazil

Samarendra Sur

Dr. Samarendra Nath Sur (M’2016). He received B.Sc degree in Physics (Hons.) from the University of Burdwan in 2007. He received M.Sc. degree in Electronics Science from Jadavpur University in 2007 and M.Tech degree in Digital Electronics and Advanced Communication from Sikkim Manipal University in 2012. He received his Ph. D degree from NIT, Durgapur. Since 2008, he has been associated with the Sikkim Manipal Institute of Technology, India, where he is currently an assistant professor in the Department of Electronics & Communication Engineering. His current research interests include Broadband Wireless Communication (MIMO and Spread Spectrum Technology), Advanced Digital Signal Processing, and Remote Sensing. He is a Member of the Institute of Electrical and Electronics Engineers (IEEE), IEEE-IoT, IEEE Signal Processing Society, Institution of Engineers (India) (IEI) and International Association of Engineers (IAENG). He was the recipient of the University Medal & Dr. S.C. Mukherjee Memorial Gold Centered Silver Medal from Jadavpur University in 2007.

Affiliations and Expertise

Assistant Professor, Department of Electronics and Communication Engineering, Sikkim Manipal Institute of Technology (SMIT), Majitar, Sikkim, India

Paolo Barsocchi

Paolo Barsocchi is a researcher at the Information Science and Technologies Institute (ISTI) of the National Research Council (CNR) at Pisa, Italy. He received his M.Sc. and Ph.D. degrees in information engineering from the University of Pisa in 2003 and 2007, respectively. Since 2017 he is Head of the Wireless Networks Research Laboratory. He is currently involved in several European projects, national and regional projects. The overall amount of attracted and managed funds both at European and national level is about €3M. He has been nominated as a regional competence reference person for advanced manufacturing solutions in Industry 4.0 in 2017, and as a contact person in the Cluster-PON call in 2017 for the CNR Department DIITET, which ISTI belongs to. His research interests are in the areas of internet of things (IoT), wireless sensor networks, cyberphysical systems, machine learning and data analysis techniques, smart environments, ambient assisted living, activity recognition and indoor localization.

Affiliations and Expertise

Researcher, Information Science and Technologies Institute (ISTI), National Research Council (CNR), Pisa, Italy

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