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.
- Explores the seamless integration of artificial intelligence, machine learning, blockchain, and digital twin computing for enhanced system performance
- Features real-world examples from industries such as manufacturing, healthcare, and smart cities
- Highlights the latest research trends and emerging opportunities in the interdisciplinary field
- Offers solutions to challenges in implementing these technologies
- Discusses future trends and potential advancements in the field
