Digital Twins
Core Principles and AI Integration
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65 226 Ft
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Product details:
- Publisher Elsevier Science
- Date of Publication 1 June 2026
- ISBN 9780443455735
- Binding Paperback
- No. of pages250 pages
- Size 276x216 mm
- Weight 450 g
- Language English 700
Categories
Long description:
Digital Twins: Core Principles, System Engineering, and AI Integration provides a comprehensive overview of digital twin technology, a cutting-edge innovation that bridges the physical and digital worlds. The book addresses common challenges such as data integration, security, scalability, and the alignment of digital twin models with actual physical processes. After presenting core concepts of digital twins for software engineering, the book discusses integration with advanced digital solutions such as AI, IoT, Cloud computing, Big Data Analytics, and Extended Reality (XR). Next, the authors provide readers with a thorough presentation of digital twins' applications in a variety of settings and industry/research topics.
Finally, the book concludes with a discussion of challenges and solutions, along with future trends in digital twins research and development. As digital twin technology evolves, its integration with various advanced digital solutions is becoming essential for achieving real-time insights and autonomous decision-making. Challenges include understanding the interoperability of these technologies, managing data complexity, ensuring security, and optimizing for low-latency environments.
Table of Contents:
PART I: INTRODUCTION AND FOUNDATIONS
1. Introduction
2. Foundational Concepts of Digital Twins
3. Technological Ecosystem of Digital Twins
PART II: INTEGRATION WITH ADVANCED DIGITAL SOLUTIONS
4. Integration with Artificial Intelligence (AI)
5. Integration with the Internet of Things (IoT)
6. Integration with Cloud Computing
7. Integration with Big Data Analytics
8. Integration with Extended Reality (XR)
PART III: APPLICATIONS IN VARIOUS SECTORS
9. Applications in Smart Manufacturing and Industry 4.0
10. Applications in Healthcare and Personalized Medicine
11. Applications in Smart Agriculture and Food
12. Applications in Smart Cities and Urban Planning
13. Applications in Energy and Utilities
14. Applications in Aerospace and Defense
PART IV: CHALLENGES, SOLUTIONS, AND FUTURE TRENDS
15. Challenges and Solutions in Digital Twin Integration
16. Future Trends and Research Directions