Artificial Intelligence, Machine Learning and Blockchain in Digital Twin Computing

Erscheinungsjahr 2026
ISBN: 978-0-443-43914-8
Verlag: Elsevier Science

Buch, Englisch, 400 Seiten, Format (B × H): 191 mm x 235 mm, Gewicht: 449 g

Artificial Intelligence, Machine Learning and Blockchain in Digital Twin Computing explores the synergy between artificial intelligence, machine learning, blockchain technology, and digital twin computing. The book overviews each technology, establishing a clear understanding of their individual roles and potential when combined. The second section delves into the integration of these technologies, focusing on key themes such as enhancing system simulations, ensuring data integrity, and enabling secure, real-time decision-making. Practical applications and case studies are used to illustrate how this convergence can drive innovation in industries like manufacturing, healthcare, and smart cities. Final sections look ahead, discussing emerging trends, challenges, and future opportunities.

Digital twin computing is the bridge between the real and virtual worlds. Digital twin computing also is the mirror that reflects the real world into the virtual world. Blockchain technology can refine the digital twins (DTs) by ensuring transparency, decentralized data storage, data immutability, and peer-to-peer communication in various applications. DT provides a powerful tool able to generate a huge amount of training data for machine learning algorithms (MLAs).

Autoren/Hrsg.

Sonawane, Vijay

Fachgebiete

• Mathematik | Informatik EDV | Informatik Professionelle Anwendung
• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik

Inhaltsverzeichnis

Part 1: INTRODUCTION
1. Introduction to digital twin computing
2. Introduction to AI/ML
3. Basics of Blockchain Technology
4. Convergence of Intelligence: Exploring the Integration of AI, ML and Blockchain
Part 2: INTEGRATION OF AI/ML AND BLOCKCHAIN IN DIGITAL TWIN
5. Synergizing AI/ML and Digital Twin Computing
6. Leveraging Blockchain in Digital Twin Systems
7. Blockchain for collaborative AI/ML in DT computing
8. Blockchain for decentralized and secure AI/ML in DT computing
9. Blockchain for IoT-enabled digital twin
10. Converging Technologies for Innovation of Digital Twin
Part 3: EMERGING APPLICATIONS
11. Production optimization/lifecycle management in smart manufacturing (Factory digital twin)
12. Damage Detection and Predictive Maintenance in Smart Infrastructures based on Digital Twining approach
13. Prediction and Remediation of Cancer Using Digital Twins: A Comprehensive Review
14. Selected Applications of AI-Based Digital Twins for Industry 4.0/5.0
Part 4: ADVANCED TOPICS AND FUTURE DIRECTIONS
15. Emerging Trends in Digital Twin Technologies
16. Advancing Real-Time Insights: Leveraging AI Digital Twins for Enhanced System and Optimization
17. Digital Twin Computing: Recent Evolution, Challenges, and Future Directions
18. Future Trends in AI-Enhanced Digital Twins: From Autonomous Systems to Quantum Integration
19. Ethical consideration and regulatory challenges
20. Future Perspectives on AI/ML and Blockchain
21. Security, Privacy, and Trust Frameworks for AI-Driven Digital Twin Ecosystems

Über Autor(innen)

Sonawane, Vijay
Dr. Vijay R. Sonawane holds a Ph.D. in Computer Engineering from K.L. University, Vijayawada, and has over 20 years of academic and research experience in computer science and information technology. His areas of expertise include Artificial Intelligence, Machine Learning, Blockchain Technology, Cloud Computing, Data Security, Explainable AI, and Digital Twins.

He has an extensive research record with 24+ journal publications indexed in SCI, Scopus, and Web of Science, along with several international conference papers published through Springer and IEEE. His contributions span advanced research topics such as blockchain-enabled data security, optimization techniques, greenhouse energy efficiency, cloud-based authentication, and AI-driven healthcare systems. He also serves as a reviewer for reputed journals such as Applied Artificial Intelligence (Taylor & Francis).

Dr. Vijay R. Sonawane has completed multiple funded research projects, and secured grants from AICTE, BCUD, MHRD, and MSFDA. His innovative work includes developing IoT systems, healthcare kiosks, and the Krushi Basket mobile application. He has also filed multiple Indian patents in emerging technologies.

An active academic leader, he has served as Head of Department, contributed to achieving NBA accreditation, established Centers of Excellence (DELL EMC, Red Hat & AWS Academy), and organized numerous national-level FDPs, conferences, and workshops. He has also contributed significantly to curriculum development with Pune University (SPPU) through syllabus design and faculty orientation programs.