The book is a collection of peer-reviewed best selected research papers presented at the International Conference on Data Analytics and Insights (ICDAI 2024), organized by Techno International, Kolkata, India, during July 2527, 2024. The two volumes of the book cover important topics like sensor and network data analytics and insights; big data analytics and insights; biological and biomedical data analysis and insights; optimization techniques, time series analysis and forecasting; power and energy systems data analytics and insights; civil and environmental data analytics and insights; and industry and applications.

Presents research works in the field of data analytics Provides original works presented at ICDAI 2023 held in Kolkata, India, during May 2023 Serves as a reference for researchers and practitioners in academia and industry

Autorentext

Nabendu Chaki is a Senior Member of IEEE and an Associate Professor in the Department of Computer Science & Engineering, University of Calcutta, India. Besides editing several volumes in LNCS, Springer, and other series, Nabendu has authored three textbooks with reputed publishers like Taylor and Francis (CRC Press), Pearson Education, etc. Dr. Chaki has published more than 100 refereed research papers in Journals and International conferences. His areas of research interest include image processing, distributed systems, and network security. Dr. Chaki has also served as a Research Assistant Professor in the Ph.D. program (Software Engineering) at U.S. Naval Postgraduate School, Monterey, CA. He is a visiting faculty member for many universities including the University of Ca'Foscari, Venice, Italy. Dr. Chaki has contributed to SWEBOK v3 of the IEEE Computer Society as a Knowledge Area Editor for Mathematical Foundations. Besides, being an editorial board member of many international journals, he has also served on the committees of more than 50 international conferences. He is the founding Chapter Chair of the ACM Professional Chapter in Kolkata, India since January 2014.

Nilanjana Dutta Roy is an Associate Professor in the Department of Computer Science & Engineering, Techno International New Town, Kolkata. She received her Ph.D. from the Indian Institute of Engineering Science and Technology, Shibpur, India. Dr. Dutta Roy has published 40 research papers in various journals and conferences and 1 authored book. She has published 1 patent and completed 2 DBT, Govt. of India-sponsored projects. She is the receiver of TitanXP GPU from NVIDIA Corporations, USA, ATAL FDP Grant from AICTE, India, Foldscopes from Stanford University, etc. She is a member of the IEEE, and Computer Society of India.

Sanjay Chakraborty is currently working as an Associate Professor at Techno International Newtown. He completed his Ph.D. at the University of Calcutta. He completed his Master of technology from the National Institute of Technology, Raipur. He completed his Bachelor of technology from the West Bengal University of Technology. He has published 62 research papers in various international journals, conferences, and book chapters. He has published three internationally authored books. His areas of interest are data mining, machine learning, deep learning, and quantum computing. He is a professional member of the International Association of Engineers, Internet Society Kolkata Chapter, Institute of Research Engineers & Doctors, and International Computer Science and Engineering Society. He has a total of 13 years of teaching and research experience. He worked as a reviewer in several international conferences, IEEE transactions, and SCI/SCIE journals. He is the recipient of a silver medal during his Master, IEEE Young Professional Best Paper Award in CICBA 2017, the most-cited author in the biomedical journal 2022, and the "INNOVATION AWARD" for his outstanding achievement in the field of Innovation by Techno India Institution's Innovation Council 2019.

Papiya Debnath is an Associate Professor in the Department of Basic Science and Humanities (Mathematics), at Techno International New Town, Kolkata, India. She received her Master of Science in Applied Mathematics from the Indian Institute of Engineering Science and Technology, Shibpur in 2006. She received M.Phil degree in Applied Mathematics from the University of Calcutta, India in 2009 and PhD in Applied Mathematics from the University of Calcutta in 2019. She has 16.5 years of experience in teaching, research, and administration. She has published 41 papers in National, International Journals and conference proceedings, 5 book chapters, and served as the editor of 2 books, and 9 patents. She is guiding 2 Ph.D. students. She is a member of the IEEE Geoscience and Remote Sensing Society.

Xin-She Yang obtained his DPhil in Applied Mathematics from the University of Oxford. He then worked at Cambridge University and then later at National Physical Laboratory (UK) as a Senior Research Scientist. Now he is Reader at Middlesex University London, and a co-Editor of the Springer Tracts in Nature-Inspired Computing. He is also an elected Fellow of the Institute of Mathematics and its Applications (FIMA, UK) and Fellow of Asian Computational Intelligence Society. He was the IEEE Computational Intelligence Society (CIS) chair for the Task Force on Business Intelligence and Knowledge Management (2015 to 2020). He has published more than 40 books and more than 350 peer-reviewed research papers with more than 91,500 citations. He has been on the prestigious list of most influential researchers or highly-cited researchers (Web of Sciences) for nine consecutive years since 2016.

Inhalt

In-body Transmitter and Receiver Antenna Design and Analysis to Assess Path Loss for Wireless Capsule Endoscopy.- For 5G Applications, Design and Performance Analysis of a Patch Antenna in Ka-band Operating at 28 GHz.- Frequency Stability Analysis in Interconnected Power Grid Using ACO Technique Optimized PID Controller .- Deep Learning Approaches for Automated Diagnosis of Polycystic Ovary Syndrome using Medical Imaging: A Comprehensive Survey.- Improving sales process efficiency with data science - a case study .