Intelligent Internet of Things for Healthcare and Industry

ISBN-13: 9783030814724 / Angielski / Twarda / 2022 / 402 str.

Uttam Ghosh; Chinmay Chakraborty; Lalit Garg

Spis treści

Chapter 1. Effectiveness of machine and deep learning in IoT enabled devices for healthcare system.- Chapter 2. Network protocols for the internet of health things.- Chapter 3. Affective computing for eHealth using low cost remote internet-of-things based EMG platform.- Chapter 4. Application of internet of things (IoT) to fight Covid-19 epidemic.- Chapter 5. An enhanced IoT based array of sensors for monitoring patients health.- Chapter 6. A secured smart healthcare monitoring systems using blockchain technology.- Chapter 7. Computational intelligence in healthcare with special emphasis on bioinformatics and internet of medical things.- Chapter 8. A review on security and privacy of internet of medical things.- Chapter 9. An Introduction to Wearable Sensor Technology.- Chapter 10. A fog based intelligent secured IoMT framework for early diabetes prediction  .- Chapter 11. A comprehensive analysis of sustainable IoT infrastructure in the post-covid-19 era.- Chapter 12. Reinforced rider optimization algorithm for diagnosis of autism spectrum disorder and medical data.- Chapter 13. Machine Learning for Fog Computing Based IoT Networks in Smart City Environment.- Chapter 14. QoS and Energy Efficiency Using Green Cloud Computing  .- Chapter 15. Privacy issues in smart IoT for Healthcare and Industry.- Chapter 16. Intelligent IoT for automotive industry 4.0 - challenges, opportunities, and future trends.- Chapter 17. Smart security for industrial and healthcare IoT applications.

O autorze

Dr. Uttam Ghosh is working as an Assistant Professor of the Practice in the Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, USA. Dr. Ghosh obtained his PhD in Electronics and Electrical Engineering from the Indian Institute of Technology Kharagpur, India in 2013, and has Post-doctoral experience at the University of Illinois in Urbana-Champaign, Fordham University, and Tennessee State University. He has been awarded the 2018-2019 Junior Faculty Teaching Fellow (JFTF) and has been promoted to a Graduate Faculty position at Vanderbilt University. Dr. Ghosh has published Forty papers at reputed international journals including IEEE Transaction, Elsevier, Springer, IET, Wiley, InderScience and IETE, and also in top international conferences sponsored by IEEE, ACM, and Springer. Dr. Ghosh has conducted several sessions and workshops related to Cyber-Physical Systems (CPS), SDN, IoT and smart cities as co-chair at top international conferences including IEEE SECON, CPSCOM, IEMCON, ICDCS and so on. He has served as a Technical Program Committee (TPC) member at renowned international conferences including ACM SIGCSE, IEEE LCN, IEMCON, STPSA, SCS SpringSim, IEEE Compsac. He is serving as an Associate Editor of the International Journal of Computers and Applications, Taylor & Francis, and also a reviewer for international journals including IEEE Transactions, Elsevier, Springer and Wiley. Dr. Ghosh is contributing as guest editor for special issues with ACM Transactions on Internet Technology (TOIT), Springer MTAP, Wiley ITL. He is a Senior Member of the IEEE and a member of AAAS, ASEE, ACM, and Sigma Xi. His main research interests include Cybersecurity, Computer Networks, Wireless Networks, Information Centric Networking and Software-Defined Networking, Energy Delivery Systems, Cloud Computing.

 

Dr. Chinmay Chakraborty is an Assistant Professor in the Dept. of Electronics and Communication Engineering, BIT Mesra. Before BIT, he worked at the Faculty of Science and Technology, ICFAI University, Agartala, Tripura, India as a Sr. lecturer. He worked as a Research Consultant in the Coal India project at Industrial Engineering & Management, IIT Kharagpur. He worked as a project coordinator of the Telecom Convergence Switch project under the Indo-US joint initiative. He also worked as a Network Engineer in System Administration at MISPL, India. His primary areas of research include Wireless Body Area Network, Internet of Medical Things, Energy-Efficient Wireless Communications and Networking, Point-of-Care Diagnosis. Dr. Chakraborty has published fifty papers at reputed international journals, chapters, and international conferences. He has authored and edited seven books “PSTN-IP Telephony Gateway for Ensuring QoS in Heterogeneous Networks”, Lap Lambert, “Advanced Classification Techniques for Healthcare Analysis” IGI Global, and “Smart Medical Data Sensing and IoT Systems Design in Healthcare, IGI Global ”, “Artificial Intelligence and the Fourth Industrial Revolution”, Pan Stanford Publishing, “Internet of Things for Healthcare Technologies”, Springer Nature, “Advances in Telemedicine for Health Monitoring”, IET, “Green Computing and Predictive Analytics for Healthcare”, CRC. He serves as a guest editor of Future Internet journal special issue (Internet of Healthcare Things (IoHT): Methods, Advances, and Applications. Dr. Chakraborty is a member of Internet Society, Machine Intelligence Research Labs, and Institute for Engineering Research and Publication. He received a young research excellence award, Global Peer Review Award, Young Faculty Award, and Outstanding Researcher Award.

 

Lalit Garg is a Senior Lecturer in Computer Information Systems at the University of Malta, Malta and an honorary lecturer at the University of Liverpool, UK. His research interests are missing data handling, machine learning, data mining, mathematical and stochastic modelling, and operational research, and their applications, especially in the healthcare domain. He has published over 100 technical papers in refereed high impact journals, conferences and books. He has organized many conferences and also delivered keynotes in many other conferences.

 Dr. Gautam Srivastava was awarded his B.Sc. degree from Briar Cliff University in U.S.A. in the year 2004, followed by his M.Sc. and Ph.D. degrees from the University of Victoria in Victoria, British Columbia, Canada in the years 2006 and 2012, respectively. He then taught for 3 years at the University of Victoria in the Department of Computer Science, where he was regarded as one of the top undergraduate professors in the Computer Science Course Instruction at the University. From there in the year 2014, he joined a tenure-track position at Brandon University in Brandon, Manitoba, Canada, where he currently is active in various professional and scholarly activities. He was promoted to the rank Associate Professor in January 2018. Dr. G, as he is popularly known, is active in research in the field of Data Mining and Big Data. In his 8-year academic career, he has published a total of 200 papers in high-impact conferences in many countries and in high-status journals (SCI, SCIE) and has also delivered invited guest lectures on Big Data, Cloud Computing, Internet of Things, and Cryptography at many Taiwanese and Czech universities. He is an Editor of several international scientific research journals. He currently has active research projects with other academics in Taiwan, Singapore, Canada, Czech Republic, Poland and U.S.A. He is constantly looking for collaboration opportunities with foreign professors and students.

Blurb

This book promotes and facilitates exchanges of research knowledge and findings across different disciplines on the design and investigation of machine learning-based data analytics of IoT infrastructures. This book is focused on the emerging trends, strategies, and applications of IoT in both healthcare and industry data analytics perspectives. The data analytics discussed are relevant for healthcare and industry to meet many technical challenges and issues that need to be addressed to realize this potential. The IoT discussed helps to design and develop the intelligent medical and industry solutions assisted by data analytics and machine learning. At the end of every chapter readers are encouraged to check their understanding by means of brainstorming summary, discussion, exercises and solutions. 

• Focused on the emerging trends, strategies, and applications of IoT in both healthcare and industry data analytics perspectives;
• Promotes an exchange of research across disciplines on the design and investigation of machine learning-based data analytics of IoT infrastructures;
• Features case studies emphasizing social and research perspectives on cyber-physical systems, data analytics, intelligence and security.