5G IoT and Edge Computing for Smart Healthcare

by Akash Kumar Bhoi PhD. (Editor), Victor Hugo Costa de Albuquerque MSc, PhD (Editor), Samarendra Nath Sur (Editor), Paolo Barsocchi MSc, PhD (Editor)

Overview

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.

Product Details

ISBN-13:	9780323905480
Publisher:	Elsevier Science
Publication date:	03/29/2022
Series:	Intelligent Data-Centric Systems
Pages:	324
Product dimensions:	7.50(w) x 9.25(h) x (d)

About the Author

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

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.

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.

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.

Table of Contents

1. Fundamentals and architecture of edge computing platform: 5G IoT/IoMT
2. Physical layer architecture of 5G enabled IoT/IoMT system
3. HetNet/M2M/D2D communication in 5G technologies
4. Sensor Networks: Data and Traffic Models in 5G Network
5. Convergent Network Architecture of 5G and MEC
6. Privacy and Security aspect of MEC enabled 5G- IoT network
7. Healthcare data encryption, data processing for the data acquired from smart sensors and smart city healthcare approaches
8. Artificial Neural Networks/ Deep Learning approaches for the disease diagnosis and treatment
9. Advanced pattern recognition tools/ computer vision algorithm for the disease diagnosis
10. Cognitive computing for the data cognition for the information relevant to the user’s disease and resource management
11. Computational Intelligence in Human-machine interface (HMI) for telemedicine application
12. Case Study: challenges and implications of smart healthcare applications and solutions to address these challenges

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From the Publisher

Covers the latest trends in data processing related 5G IoT and edge computing for successful implementation of a smart health care system