Decentralized Futures

Navigating the Integration of Blockchain Technology with Artificial Intelligence
1. Auflage 2026
ISBN: 978-1-041-11166-5
Verlag: Taylor & Francis Ltd

Buch, Englisch, 360 Seiten, Format (B × H): 156 mm x 234 mm

This book provides readers with a comprehensive grasp of blockchain technology by exploring its applications, security measures and protocols along with the need for safe blockchain networks, and the incorporation of artificial intelligence improving blockchain performance.

Decentralized Futures: Navigating the Integration of Blockchain Technology with Artificial Intelligence seeks to provide readers with a thorough understanding of blockchain technology, security frameworks, and the integration of artificial intelligence. The book initially focuses on the fundamental characteristics of blockchain, alongside various implementation frameworks. The authors explore machine learning techniques to identify suspicious and fraudulent transaction patterns, such as in behavior analysis and examine AI-based clustering and classification techniques to break apart blockchain data for easier processing and more efficient analysis. Additionally, this book provides an in-depth examination of consensus mechanisms that enhance blockchain effectiveness. Through real-world applications, readers will gain practical insights by applying the lessons and guidance from these examples to their own work. The book investigates how AI integration with blockchain creates effective decentralized futures, while also providing an exploratory perspective on the opportunities and challenges inherent in this convergence.

This book targets a mixed audience of data scientists, engineers, researchers, academics, and students on different levels to share and contribute cutting-edge technologies, methodologies, frameworks, and practices in the Blockchain integrated with AI.

Zielgruppe

Postgraduate and Professional Reference

Autoren/Hrsg.

Panigrahi, Amrutanshu

Pati, Abhilash

Jain, Prince

Liu, Haipeng

Inhaltsverzeichnis

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

Über Autor(innen)

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.