Human- Centric Integration of Next-Generation Data Science and Blockchain Technology: Advancing Society 5.0 Paradigms

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· Academic Press
Ebook
320
Pages
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About this ebook

Human- Centric Integration of Next Generation Data Science and Blockchain Technology: Advancing Society 5.0 Paradigms focuses on the current technological landscape, addressing the evolving integration of data science and blockchain within the context of Society 5.0. This comprehensive resource explains the convergences between data science, blockchain, and the human-centric vision of Society 5.0, while also filling the gap in understanding and navigating this transformative intersection with recent shifts towards more decentralized and data-driven paradigms.The book introduces the concept of Society 5.0, examining the historical context, and outlines the evolving technological landscape shaping our interconnected future. It discusses the fundamental principles of data science, from data collection and preprocessing to exploratory data analysis and explains the transformative impact of data science and blockchain across industries such as healthcare, finance, education, and transportation. This book is essential to understanding and shaping the future of technology and society from decentralized solutions to predictive analytics/ emerging technologies. - Addresses the evolving integration of data science and blockchain within the context of Society 5.0 - Introduces the basic architecture and taxonomy of blockchain technology - Explores the future urban lives under the concept of "Society 5.0", characterized by the key phrases of data-driven society and knowledge-intensive society - Offers a firm foundation and understanding of recent advancements in various domains such as data analytics, neural networks, computer vision, and robotics, along with practical solutions to existing problems in fields such as healthcare, manufacturing industries, security, and infrastructure management

About the author

Amit Kumar Tyagi is an Assistant Professor, at the National Institute of Fashion Technology, New Delhi, India. Previously he worked as an Assistant Professor (Senior Grade 2), and Senior Researcher at Vellore Institute of Technology (VIT), Chennai Campus, India from 2019-2022. He received his Ph.D. Degree (Full-Time) in 2018 from Pondicherry Central University, India. He joined the Lord Krishna College of Engineering, Ghaziabad (LKCE) from 2009 to 2010, and 2012 to 2013. He was an Assistant Professor and head researcher at Lingaya’s Vidyapeeth (formerly known as Lingaya’s University), India from 2018 to 2019. He supervised one PhD thesis and more than ten Master dissertations. He has contributed to several projects such as “AARIN and “P3- Block to address some of the open issues related to privacy breaches in Vehicular Applications (such as Parking) and Medical Cyber-Physical Systems (MCPS). He has published over 200 papers in refereed high-impact journals, conferences, and books, and some of his articles won best paper awards. Also, he has filed more than 25 patents (Nationally and Internationally) in the areas of Deep Learning, Internet of Things, Cyber-Physical Systems, and Computer Vision. He has edited more than 25 books for IET, Elsevier, Springer, CRC Press, etc. Additionally, he has authored 4 Books on Intelligent Transportation Systems, Vehicular Ad-hoc Network, Machine learning and Internet of Things, with IET UK, Springer Germany, and BPB India publisher. He won the Faculty Research Award of the Year for 2020, 2021, and 2022 consecutively, given by Vellore Institute of Technology, Chennai, India. Recently, he was awarded the best paper award for his paper “A Novel Feature Extractor Based on the Modified Approach of Histogram of Oriented Gradient, in ICCSA 2020, Italy (Europe). His current research focuses on Next Generation Machine Based Communications, Blockchain Technology, Smart and Secure Computing and Privacy. He is a regular member of the ACM, IEEE, MIRLabs, Ramanujan Mathematical Society, Cryptology Research Society, Universal Scientific Education and Research Network, CSI, and ISTE.

Dr. Tiwari received his Ph.D. in the Department of Computer Science & Engineering (CSE) from the Indian Institute of Technology (Banaras Hindu University), Varanasi (India) in 2012 and M. Tech. in Computer Science and Technology from the University of Mysore (India) in 2009. Currently. He is working as an Associate Professor in the School of Computing Science and Engineering (SCSE), Galgotias University, Greater Noida, Gautam Budha Nagar, Uttar Pradesh (India). He has authored and co-author more than 50 national and international journal publications, book chapters, and conference articles. He has five patents filed to his credit. His research interests include machine learning, deep learning, computer vision, medical image analysis, pattern recognition, and biometrics. Dr. Tiwari is a FIETE and member of ACM, IET, CSI, ISTE, IAENG, SCIEI. He is also a guest editorial board member and a reviewer for many international journals of repute.

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