Foundations of Data Science Based Healthcare Internet of Things

Author:   Parikshit N. Mahalle ,  Sheetal S. Sonawane
Publisher:   Springer Verlag, Singapore
Edition:   1st ed. 2021
ISBN:  

9789813364592


Pages:   64
Publication Date:   23 January 2021
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Foundations of Data Science Based Healthcare Internet of Things


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Overview

This book offers a basic understanding of the Internet of Things (IoT), its design issues and challenges for healthcare applications. It also provides details of the challenges of healthcare big data, role of big data in healthcare and techniques, and tools for IoT in healthcare. This book offers a strong foundation to a beginner. All technical details that include healthcare data collection unit, technologies and tools used for the big data analytics implementation are explained in a clear and organized format.

Full Product Details

Author:   Parikshit N. Mahalle ,  Sheetal S. Sonawane
Publisher:   Springer Verlag, Singapore
Imprint:   Springer Verlag, Singapore
Edition:   1st ed. 2021
Weight:   0.454kg
ISBN:  

9789813364592


ISBN 10:   9813364599
Pages:   64
Publication Date:   23 January 2021
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Chapter 1. Introduction.- Chapter 2. Internet of things in healthcare.- Chapter 3. Big Data- Chapter 4. Data Science and tecniques.- Chapter 5. Conclusion.

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Author Information

Dr. Parikshit N. Mahalle obtained B.E. degree in Computer Engineering from Amravati University, M.E. degree from SPPU, Pune, and Ph.D. in specialization in Wireless Communication from Aalborg University, Denmark. He was Postdoc Researcher at CMI, Aalborg University, Copenhagen. Currently, he is working as Professor and Head in the Department of Computer Engineering at Smt. Kashibai Navale College of Engineering, and recognized as Ph.D. guide of SSPU Pune. He has 20 years of teaching and research experience. He is on the Research and Recognition Committee at several universities. He is a senior member IEEE and ACM, and a life member of CSI and ISTE. He is a reviewer, an editor of ACM, Springer and Elsevier Journals and a member of Editorial Review Board for IGI Global. He has published more than 150 publications with 1242 citations and h-index 14. He has edited 5 and authored 13 books and also has 7 patents to his credit. He has published a book on Data Analytics for COVID-19 Outbreak. He has delivered more than 100 lectures at national and international levels on IoT, Big Data and Digitization. He has worked as BOS-Chairman for Information Technology and is working as a member of BOS Computer Engineering SPPU and several other institutions. He has received “Best Faculty Award” by Sinhgad Institutes and Cognizant Technologies Solutions.   Dr. Sheetal S. Sonawane is Associate Professor in the Department of Computer Engineering at Pune Institute of Computer Technology (Pune) since 2003. She received Ph.D. from the College of Engineering at Pune University in 2018 under the guidance of Dr. Parag Kulkarni. She received Bachelors in Computer Engineering from Pune University in 2000 and 4th rank holder in Pune University for Master in Computer Engineering in the year 2006. Her main research interests are in the areas of data mining and information retrieval. She has published widely in international journals published by Springer and Inderscience and conference proceedings by IEEE and Springer having more than 400 citations. She is the recipient of Best Paper Award for her IEEE conference paper. She has also written book chapters in books like big data analytics by PHI Publication and “Semigraph and their applications” by Academy of Discrete Mathematics and Applications, India. She is a reviewer of conferences and journals like Elsevier and Inderscience. She has more than 30 publications to her credit in international journals and conferences. In recent years, she has focused her research in machine learning, handling big unstructured data and graph model for representing and analyzing text document. 

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