Smart Healthcare Monitoring Using IoT with 5G : Challenges, Directions, and Future Predictions book cover
1st Edition

Smart Healthcare Monitoring Using IoT with 5G
Challenges, Directions, and Future Predictions




ISBN 9780367775292
Published December 23, 2021 by CRC Press
272 Pages 76 B/W Illustrations

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Book Description

Focusing on the challenges, directions, and future predictions with the role of 5G in smart healthcare monitoring, this book offers the fundamental concepts and analyses on the methods to apply Internet of Things (IoT) in monitoring devices for diagnosing and transferring data. It also discusses self-managing to help providers improve their patients' healthcare experience.

Smart Healthcare Monitoring Using IoT with 5G: Challenges, Directions, and Future Predictions illustrates user-focused wearable devices such as Fitbit health monitors and smartwatches by which consumers can self-manage and self-monitor their own health. The book covers new points of security and privacy concerns, with the expectation of IoT devices gaining more popularity within the next ten years. Case studies depicting applications and best practices as well as future predictions of smart healthcare monitoring by way of a 5G network are also included.

Interested readers of this book include anyone working or involved in research in the field of smart healthcare, such as healthcare specialists, computer science engineers, electronics engineers, and pharmaceutical practitioners.

Table of Contents

1. The Internet of Things in Healthcare Management: Potential Applications and Challenges. 2. Blending of Internet of Things and Deep Transfer Learning (DTL): Enabling Innovations in Healthcare (COVID-19) and Applications. 3. Potential Applications and Challenges of Internet of Things in Healthcare. 4. IoT and Smart Health Management. 5. Current Status of Alzheimer’s Disease in India: Prevalence, Stigma, and Myths. 6. Phytochemicals' Potential to Reverse the Process of Neurodegeneration. 7. Existing Methods and Emerging Trends for Novel Coronavirus (COVID-19) Detection Using Residual Network (ResNet): A Review on Deep Learning Analysis. 8. Clinical Impact of COVID on Diabetic Patients. 9. Smart Hospitals Using Artificial Intelligence and Internet of Things for COVID-19 Pandemic. 10. Researcher Issues and Future Directions in Healthcare Using IoT and Machine Learning. 11. Diseases Prediction and Diagnosis System for Healthcare Using IoT and Machine Learning. 12. Challenges and Solution of COVID-19 Pandemic Based on AI and Big Data. 13. A Review of Artificial Intelligence Applications for COVID-19 Contact Tracing.

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Editor(s)

Biography

Meenu Gupta completed her PhD in Computer Science & Engineering with emphasis on Traffic Accident Severity problem from the Ansal University, Gurugram, India (2020), an M.Tech in Computer Science & Engineering from the M.D. U University, Rohtak, India (2010), and she graduated in Information Technology at the K.U.K University, Kurukshetra, India (2006). She is currently Associate Professor in Chandigarh University. She has 13 years of teaching experience. Her areas of research are Machine Learning, Intelligent Systems, Data mining, with specific interest in, Artificial Intelligence, Image Processing and Analysis, Smart cities, Data Analysis, and human/brain-machine interaction. She also completed two edited books of CRC press on Healthcare and Cancer diseases. She also has 4 authored books on engineering streams. She worked as a reviewer of many journals like, Big Data, CMC, Scientific Report, TSP, etc. She is a life member of ISTE and IAENG. She has authored or co-authored over 50 papers in refereed international journals (SCI/SCIE/WoS/Scopus/etc.), conferences, and more than 20 book chapters. She also chaired IEEE international Conference and convened many workshops/FDP.

Gopal Chaudhary is currently working as an assistant professor in Bharati Vidyapeeth’s College of Engineering, Guru Gobind Singh Indraprastha University, Delhi, India. He holds a Ph.D. in biometrics at the division of Instrumentation and Control Engineering, Netaji Subhas Institute of Technology, University of Delhi, India. He received B.E. degree in electronics and communication engineering in 2009 and the MTech degree in microwave and optical communication from Delhi Technological University (formerly known as Delhi College of Engineering), New Delhi, India, in 2012. He has 30 publications in refereed national/international journals and conferences (e.g. Elsevier, Springer, Inderscience) in the area of biometrics and its applications. His current research interests include soft computing, intelligent systems, information fusion, and pattern recognition. He has organized many conferences and contributed to special issues.

Victor Hugo C. de Albuquerque [M17, SM19] has a Ph.D. in Mechanical Engineering with emphasis on Materials 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 Technology at the Federal Center of Technological Education of Ceará (CEFETCE, 2006). He is currently Full Professor of the Graduate Program in Applied Informatics, and coordinator of the Laboratory of Industrial Informatics, Electronics and Health at the University of Fortaleza (UNIFOR). Data Science Director at the Superintendency for Research and Public Safety Strategy of Ceará State (SUPESP/CE), Brazil. He has experience in Computer Systems, mainly in the research fields of: Applied Computing, Intelligent Systems, Visualization and Interaction, with specific interest in Pattern Recognition, Artificial Intelligence, Image Processing and Analysis, as well as Automation with respect to biological signal/image processing, image segmentation, biomedical circuits and human/brain-machine interaction, including Augmented and Virtual Reality Simulation Modeling for animals and humans. Additionally, he has research at the microstructural characterization field through the combination of non-destructive techniques with signal/image processing and analysis and pattern recognition. Prof. Victor is the leader of the Industrial Informatics, Electronics and Health Research Group. He is Editor-in-Chief of the Journal of Artificial Intelligence and Systems and Associate Editor of the IEEE Access, Applied Soft Computing, Frontiers in Communications and Networks, Computational Intelligence and Neuroscience, Journal of Nanomedicine and Nanotechnology Research, Computational Physiology and Medicine, and Journal of Mechatronics Engineering, and he has been Lead Guest Editor of several high-reputed journals, and TPC member of many international conferences.