5G IoT and Edge Computing for Smart Healthcare 1st Edition by Akash Kumar Bhoi, Victor Hugo Costa de Albuquerque, Samarendra Nath Sur, Paolo Barsocchi ISBN 9780323905480 032390548X

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Product details:

ISBN 10: 032390548X
ISBN 13: 9780323905480
Author: Akash Kumar Bhoi, Victor Hugo Costa de Albuquerque, Samarendra Nath Sur, Paolo Barsocchi

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.

• 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

5G IoT and Edge Computing for Smart Healthcare 1st Edition Table of contents:

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

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Tags: Akash Kumar Bhoi, Victor Hugo Costa de Albuquerque, Samarendra Nath Sur, Paolo Barsocchi, 5G IoT, Edge Computing