Efficient Data Handling for Massive Internet of Medical Things: Healthcare Data Analytics

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ISBN 10: 3030666328 / ISBN 13: 9783030666323

Editore: Springer, 2021

2021. Hardcover. . . . . . Codice articolo V9783030666323

Riassunto:

This book focuses on recent advances and different research areas in multi-modal data fusion under healthcare informatics and seeks out theoretical, methodological, well-established and validated empirical work dealing with these different topics. This book brings together the latest industrial and academic progress, research, and development efforts within the rapidly maturing health informatics ecosystem. Contributions highlight emerging data fusion topics that support prospective healthcare applications. The book also presents various technologies and concerns regarding energy aware and secure sensors and how they can reduce energy consumption in health care applications. It also discusses the life cycle of sensor devices and protocols with the help of energy-aware design, production, and utilization, as well as the Internet of Things technologies such as tags, sensors, sensing networks, and Internet technologies.  In a nutshell, this book gives a comprehensive overview of the state-of-the-art theories and techniques for massive data handling and access in medical data and smart health in IoT, and provides useful guidelines for the design of massive Internet of Medical Things. 

Informazioni sull?autore:

Dr. Chinmay Chakraborty is working as an Assistant Professor (Sr.) in the Dept. of Electronics and Communication Engineering, Birla Institute of Technology, Mesra, India. 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 Telecommunication Convergence Switch project under the Indo-US joint initiative. He also worked as a Network Engineer in System Administration at MISPL, India. His main research interests include the Internet of Medical Things, Wireless Body Area Network, Wireless Networks, Telemedicine, m-Health/e-health, and Medical Imaging. Dr. Chakraborty has published 70 papers at reputed international journals, conferences, book chapters, and books. He is an Editorial Board Member in the different Journals and Conferences. He is serving as a Guest Editor of MDPI-Future Internet Journal, Wiley-Internet Technology Letters, Springer-Annals of Telecommunications, and Lead Guest Editor of IGI-International Journal of E-Health and Medical Communications, Springer – Multimedia Tools and Applications, Lead Series Editor of CRC- Advances in Smart Healthcare Technologies, and also Associate Editor of International Journal of End-User Computing and Development, and has conducted a session of SoCTA-19, ICICC – 2019, Springer CIS 2020, SoCTA-20, SoCPaR 2020, and also a reviewer for international journals including IEEE Access, IEEE Sensors, IEEE Internet of Things, Elsevier, Springer, Taylor & Francis, IGI, IET, TELKOMNIKA Telecommunication Computing Electronics and Control, and Wiley. Dr. Chakraborty is co-editing Eight books on Smart IoMT, Healthcare Technology, and Sensor Data Analytics with CRC Press, IET, Pan Stanford, and Springer. He has served as a Publicity Chair member at renowned international conferences including IEEE Healthcom, IEEE SP-DLT. Dr. Chakraborty is a member of Internet Society, Machine Intelligence Research Labs, and Institute for Engineering Research and Publication. He received a Best Session Runner-up Award, Young Research Excellence Award, Global Peer Review Award, Young Faculty Award, and Outstanding Researcher Award. He was the speakers for AICTE, DST sponsored FDP and CEP Short Term Course.

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 MASS, IEEE SECON, IEEE CPSCOM, IEEE IEMCON, IEEE 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. Vinayakumar Ravi is working as a Postdoctoral research fellow in developing and implementing novel computational and machine learning algorithms and applications for big data integration and data mining with Jegga Lab, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA. He received his Ph.D. degree in computer science from Computational Engineering & Networking, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, India. His Ph.D. work centre’s on application of machine learning and deep learning for Cyber Security and discusses the importance of natural language processing, image processing and big data analytics for Cyber Security. His research interests include application of data mining, machine learning (including deep learning), natural language processing and image processing for Cyber Security, big security data analytics, disease gene discovery/prioritization, computational drug discovery and drug repositioning. Dr. Ravi has more than 50 research publications in reputed conferences and journals. Ravi's publications include prestigious conferences in the area of Cyber Security, like IEEE S&P and IEEE Infocom. He has given many invited talks on deep learning applications in IEEE conferences and Industry workshops in 2018. He has got a full scholarship to attend Machine Learning Summer School (MLSS) 2019, London. Dr. Ravi has served as a Technical Program Committee (TPC) member at international conferences including SSCC, IEEE TrustCom, and IEEE SmartData. He is an editorial board member for Journal of the Institute of Electronics and Computer and he has organized a shared task on detecting malicious domain names (DMD 2018) as part of SSCC'18 and ICACCI'18. More research details available at https://vinayakumarr.github.io/

Dr. Yogesh Shelke has more than a decade of experience spanning roles from IP researcher, innovation consulting and med-tech advisory to leading healthcare companies, to drive their future R&D strategies. Starting his career as physician in tertiary care delivery centers, he has been acknowledged for his expertise in emerging healthcare trends such Internet of Medical Things, Artificial Intelligence and Machine Learning for healthcare applications, Data analytics in care delivery, and product development in digital healthcare domain. He has been associated with industry-academic collaborations, Journal editorials, conferences and strategic research initiatives from healthcare organizations.

Dati bibliografici

Titolo: Efficient Data Handling for Massive Internet...
Casa editrice: Springer
Data di pubblicazione: 2021
Legatura: Rilegato
Condizione: New