Decentralized Futures Navigating the Integration of Blockchain Technology with Artificial Intelligence

Chapter 1 Introduction to Blockchain Technology: A Revolutionary Paradigm Shift Chapter 2 Integrating Internet of Things (IoT) and Blockchain: Current Applications, Challenges, and Future Perspectives  Chapter 3 Blockchain Technology: Foundations, Challenges, and Future Prospects Chapter 4 Biologically Plausible Spiking Neural Networks for Blockchain Technology: A Review of Synergies and Challenges Chapter 5 Enhancing Security and Transparency in AI with Blockchain Chapter 6 Enhancing UPI security with AI: An Ensemble-Based Fraud Detection Model Chapter 7 Decentralized Machine Learning: Opportunities and Challenges Chapter 8 Enhancing Supply Chain Sustainability through Blockchain Technology:            A Scholarly Analysis Chapter 9 BASIS-IoT: Blockchain and AI-integrated SDN-based Framework for Smart Irrigation Systems in IoT Environments Chapter 10 Decentralized Identity and AI-Powered Identity Management Chapter 11 IMBM: Integrating Metaverse, Blockchain, and Machine Learning models for effective Disease diagnosis Chapter 12 Modelling Herding and Contagion Effects in Digital Currencies: A Comparative Study of Holt-Winters and Deep Learning Approaches Chapter 13 Privacy-Preserving AI Through Blockchain and Federated Learning Chapter 14 Blockchain Based Intelligent Transportation Management System

Biography

Dr. Amrutanshu Panigrahi is an Assistant Professor in the Department of Computer Science and Engineering at Siksha ‘O’ Anusandhan (Deemed to be University), Bhubaneswar, Odisha, India. Demonstrating a strong commitment to international research collaboration, Dr. Panigrahi is currently undertaking Postdoctoral Research at Lincoln University College, Malaysia. His core research interests lie at the intersection of Blockchain Technology, ML, DL, and Cloud Computing. He is an Editorial Board Member of BMC Artificial Intelligence, Edelweiss Applied Science and Technology journal, and Discover Artificial Intelligence.

Dr. Abhilash Pati is an Assistant Professor in the Department of CSE, FET-ITER, Siksha ‘O’ Anusandhan (Deemed to be University), Bhubaneswar, India. He is currently a postdoctoral fellow at Lincoln University College in Malaysia.. His research interests include IoT, Fog Computing, ML, and DL. He is an editorial board member of various journals, including Discover Artificial Intelligence, Big Data and Computing Visions, BMC Artificial Intelligence, and Edelweiss Journal of Engineering and Technology and has authored three textbooks.

Dr. Prince Jain is an Assistant Professor (Research Cadre) in the Department of Mechatronics Engineering at Parul University, Vadodara, India. He received his Ph.D. from Punjab Engineering College Chandigarh under the prestigious Visvesvaraya Ph.D. Fellowship of the Ministry of Electronics and Information Technology Government of India. His work spans machine learning, artificial intelligence, metamaterial absorbers and antennas, nanotechnology, and biomedical signal processing. Dr. Jain serves on the editorial boards of Scientific Reports, International Journal of Antennas and Propagation, Journal of Electrical and Computer Engineering, and Discover Applied Sciences.

Dr. Haipeng Liu is an Associate Professor at Coventry University, where he actively contributes to research and postgraduate supervision, particularly in projects focused on cost-effective healthcare solutions using wearable sensors. His areas of interest include wearable healthcare technologies, biomedical sensing, and intelligent monitoring systems. His work centers on post-stroke rehabilitation monitoring, leveraging emerging technologies such as artificial intelligence, the Internet of Medical Things (IoMT), and cloud-based diagnostics to enable continuous, remote patient care. Beyond research, he mentors students and promotes diversity initiatives, including supporting female participation in STEM through international scholarship programs. His contributions reflect a commitment to advancing accessible, technology-driven healthcare and improving patient outcomes through innovative engineering solutions.