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Full Description
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). On the other hand, AI/ML based/driven DT offers many advantages for optimization, prediction, damage detection/predictive maintenance/predictive modeling/decision support, lifecycle management for the real physical assets. Artificial Intelligence, Machine Learning and Blockchain in Digital Twin Computing offers a comprehensive exploration of the synergy between artificial intelligence, machine learning, blockchain technology, and digital twin computing. Structured into three main sections, the book begins with a foundational overview of 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. The final section looks ahead, discussing emerging trends, challenges, and future opportunities in this evolving field. By blending theory with practical insights, this book serves as both an educational resource and a practical guide for professionals, researchers, and students seeking to harness the power of these advanced technologies in complex, real-world environments.
Contents
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
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