Artificial Intelligence and Digital Twin-Based Big Data Analytics for Blockchain-IoT Enabled Applications
1st Edition
Will be published approx. on 1. September 2026
Book
Hardback
428 pages
978-1-041-09148-6 (ISBN)
Description
In today's era, the integration of cutting-edge technologies like Artificial Intelligence (AI), Digital Twin technology, and Big Data Analytics, is transforming Blockchain-enabled IoT ecosystems. Today AI enhances predictive intelligence and decision-making, while Digital Twins create real-time virtual replicas of physical systems for monitoring and simulation. Big Data analytics processes massive IoT-generated data streams to extract actionable insights whereas Blockchain technology ensures data integrity, transparency, and secure decentralized communication among devices. Together, these technologies enable smart, autonomous, and trustworthy systems across domains such as healthcare, smart cities, and industrial automation. This convergence improves efficiency, resilience, and scalability in next-generation IoT applications for modern society.
More details
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Professional and scholarly
Academic, Postgraduate, Professional Practice & Development, Professional Training, Undergraduate Advanced, and Undergraduate Core
Illustrations
81 s/w Tabellen, 118 s/w Zeichnungen, 1 Farbfoto bzw. farbiges Rasterbild, 7 s/w Photographien bzw. Rasterbilder, 125 s/w Abbildungen, 1 farbige Abbildung
81 Tables, black and white; 118 Line drawings, black and white; 1 Halftones, color; 7 Halftones, black and white; 1 Illustrations, color; 125 Illustrations, black and white
Dimensions
Height: 254 mm
Width: 178 mm
ISBN-13
978-1-041-09148-6 (9781041091486)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
Amit Kumar Tyagi is an Assistant Professor, at the National Forensic Sciences University, Gandhinagar, Gujarat, India. He received his Ph.D. Degree (Full-Time) in 2018 from Pondicherry Central University, 605014, Puducherry, India. He has previously worked as an assistant professor at several institutes like Lord Krishna College of Engineering (LKCE), Ghaziabad (July 2009-July 2010, and October 2012- October 2013), Lingaya's Vidyapeeth (formerly known as Lingaya's University), Faridabad (September 2018-May 2019), VIT Chennai (June 2019-November 2022) and NIFT New Delhi (November 2022-September 2025). His current research focuses on Next Generation Machine Based Communications, Blockchain Technology, Smart and Secure Computing and Privacy. He is a senior member of IEEE.
Shabnam Kumari is a Ph.D. scholar in the Department of Computer Science, Faculty of Science and Humanities, SRM Institute of Science and Technology, Chennai, Tamil Nadu, India. She has more than 3 years of experience including teaching, research and other areas. She has completed her MCA from YMCA University of Science and Technology, Faridabad. She has filed more than five national and international patents in the area of IoTs, Machine Learning, Deep Learning and Wireless Network. She has published over twenty research articles in International Conferences and Journals. Her areas of interest include Machine Learning, Deep Learning, and related fields. She is a lifetime member of ACM-Women and SCRS.
Shabnam Kumari is a Ph.D. scholar in the Department of Computer Science, Faculty of Science and Humanities, SRM Institute of Science and Technology, Chennai, Tamil Nadu, India. She has more than 3 years of experience including teaching, research and other areas. She has completed her MCA from YMCA University of Science and Technology, Faridabad. She has filed more than five national and international patents in the area of IoTs, Machine Learning, Deep Learning and Wireless Network. She has published over twenty research articles in International Conferences and Journals. Her areas of interest include Machine Learning, Deep Learning, and related fields. She is a lifetime member of ACM-Women and SCRS.
Content
Preface. Acknowledgement. Section 1: Basic and Fundamentals 1. Digital Twins in the Era of IoT and AI. 2. Advanced Analytics with AI and Machine Learning. 3. Big Data Analytics in Modern Technologies. 4. Role of Smart Finance and Management in the Industry 5.0 Era. 5. Blockchain-Enabled Examination Integrity: Guaranteeing Transparency and Security. Section 2: Methos and Principles 6. Big Data Architectures for Blockchain-IoT Systems. 7. AI-Driven Data Processing and Decision-Making: Machine Learning in Internet of Things. 8. Leveraging AI to Examine Cultural Familiarity as a Moderator in the Price-Purchase Link: Insights from Vietnamese Consumers of Korean Cosmetics in the Era of Hallyu. 9. Industry 5.0 and Smart Economy: A Managerial Perspective. Section 3: Applications and Use Cases 10. Forecasting Humidity Saturation for Climate-Resilient and Sustainable Agriculture in Africa's Arid Farmlands Using Machine Learning. 11. Emerging Technologies for Smart Banking and Financial Systems for Modern Era. 12. E-Waste Management in Communication Technology: AI Integrated Bioleaching. 13. Machine Learning-Enabled Digital Twins For Diagnostic and Therapeutic Purposes. 14. Next-Gen Financial Management: Smart Systems and Industry 5.0 Integration for a Sustainable World. Section 4: Open Issues and Future Opportunities 15. Industrial IoT Transformation in Aircraft Manufacturing and Maintenance, Repair, and Overhaul Operations. 16. Digital Twins Enabled by AI and the Internet of Things for Intelligent Cities and Ecologically Designed Ecosystems. 17. Ethical and Legal Considerations for Artificial Intelligence, Blockchain, and the Internet of Things. 18. Future of AI-based Applications in Education Sector: Challenges and Scope. 19. Theoretical Foundations of Digital Twins for Predictive Intelligence in IoT-Driven Healthcare Ecosystems. 20. Strategic Management in the Smart Era: Industry 5.0 and Digital Finance. 21. AI Enabled Smart Banking Systems: An Analysis from Society's Perspective. Index.