Internet of Things Based Smart Healthcare: Intelligent and Secure Solutions Applying Machine Learning Techniques

ISBN-13: 9789811914072 / Angielski / Twarda / 2022

Biswas, Suparna

Opis

This book provides both the developers and the users with an awareness of the challenges and opportunities of advancements in healthcare paradigm with the application and availability of advanced hardware, software, tools, technique or algorithm development stemming the Internet of Things. The book helps readers to bridge the gap in their three understanding of three major domains and their interconnections: Hardware tested and software APP development for data collection, intelligent protocols for analysis and knowledge extraction. Medical expertise to interpret extracted knowledge towards disease prediction or diagnosis and support. Security experts to ensure data correctness for precise advice. The book provides state-of-the-art overviews by active researchers, technically elaborating healthcare architectures/frameworks, protocols, algorithms, methodologies followed by experimental results and evaluation. Future direction and scope will be precisely documented for interested readers.

Spis treści

Part 1 IoT based Smart Healthcare.- Chapter 1 Introduction.- Chapter 2 Architecture for Smart Healthcare: Cloud vs Edge.- Chapter 3 Main Challenges and Concerns of Health IoT Data.- Part 2 Context and Body Vitals Monitoring Systems.- Chapter 4 Human Activity Recognition Systems Based on Sensor Data using Machine Learning.- Chapter 5 Human Activity Recognition Systems Based on Audio-Video Data using Machine Learning and Deep learning.- Chapter 6 Review of Body Vitals Monitoring Systems for Disease Prediction.- Chapter 7 Review of Context Aware System Implementations.- Part 3 Social Sensing Applications for Public Health.- Chapter 8 Types of Social Sensing Data.- Chapter 9 Social Data Analysis Techniques and Applications.- Chapter 10 Challenges and Limitations of Social Data Analysis Approaches.- Part 4 Reliability, Security and Privacy of Health Data.- Chapter 11 Quality of Service vs Quality of Experience for Real-time Smart Healthcare.- Chapter 12 Security and Privacy Issues of Health Data.- Chapter 13 Review of Performance Metrics and Corrective Measures for Health Data Analysis.

O autorze

Suparna Biswas is Associate Professor in the Department of Computer Science & Engineering in Maulana Abul Kalam Azad University of Technology, India. She has received M.E. and Ph.D. from Jadavpur University, West Bengal, in 2004 and 2013, respectively. She was Erasmus Mundus Postdoctoral Research Fellow in cLINK project in Northumbria University, Newcastle, UK, during 2014–15. She is currently handling two funded research projects in the capacity of PI and Co-PI in the area of IoT-based remote healthcare. She has co-authored a number of research papers published in journals, conferences and as book chapters of international repute. Her areas of research interests are IoT, network security, mobile computing and remote healthcare. 

Chandreyee Chowdhury is Associate Professor in the Department of Computer Science and Engineering at Jadavpur University, India. Her research interests include IoT in healthcare, indoor localization and human activity recognition. She was awarded Post Doctoral Fellowship by Erasmus Mundus in 2014 to carry out research work at Northumbria University, UK. She has served as Technical Program Committee Members of many international conferences. She has published around 100 papers in reputed journals, book chapters and international peer-reviewed conferences. She is Member of IEEE and IEEE Computer Society. 

Biswa Ranjan Acharya is Academic currently associated with Kalinga Institute of Industrial Technology Deemed to be University along with pursuing Ph.D. in computer application from Veer Surendra Sai University of Technology, India. He has received MCA in 2009 from IGNOU, New Delhi, India, and M.Tech. in Computer Science and Engineering in the year of 2012 from Biju Pattanaik University of Technology, India. He is also associated with various educational and research societies like IEEE, IACSIT, CSI, IAENG and ISC. He has along with 2 years of industry experience as Software Engineer, a total of 10 years experience in both academia of some reputed university like Ravenshaw University and software development field. He is currently working on research area multiprocessor scheduling along with different fields like data analytics, computer vision, machine learning and IoT. He published some research article in international repute journal as well as serving as Reviewer. 

Chuan-Ming Liu is Professor in the Department of Computer Science and Information Engineering (CSIE), National Taipei University of Technology, Taiwan, where he was Department Chair from 2013–2017. Currently, he is pointed to be Head of the Extension Education Center at the same school. Dr. Liu received his Ph.D. in Computer Science from Purdue University in 2002 and joined the CSIE Department in Taipei Tech in the spring of 2003. In the summers of 2010 and 2011, he had held visiting appointments at Auburn University and Beijing Institute of Technology, respectively.