Digital Twins
Core Principles and AI Integration
- 1st Edition - May 28, 2026
- Latest edition
- Editors: Bedir Tekinerdogan, Cor Verdouw
- Language: English
Digital Twins: Core Principles and AI Integration offers a structured and up-to-date overview of digital twin technology, combining foundational principles with the rapidly growin… Read more
Description
Description
Digital Twins: Core Principles and AI Integration offers a structured and up-to-date overview of digital twin technology, combining foundational principles with the rapidly growing role of artificial intelligence (AI). This book introduces the core concepts, modeling approaches, and software and systems engineering foundations needed to design and implement digital twins effectively. It then explores architectural methods, lifecycle management, interoperability, and the alignment between physical systems and their digital representations. A central part of this book focuses on data science and AI-enabled digital twins, demonstrating how machine learning, deep learning, generative AI, and autonomous agents enhance predictive analytics, optimization, anomaly detection, and automated decision-making. Integration with Internet of Things (IoT), cloud–edge infrastructures, big data analytics, and XR technologies further shows how intelligent digital twins evolve into adaptive and interactive systems. Real-world applications from manufacturing, agriculture, food systems, energy, mobility, healthcare, and urban environments illustrate the practical value of AI-driven digital twins. This book concludes with key challenges and future directions, including trustworthy AI, security, data governance, and the scaling of digital twin ecosystems.
Key features
Key features
- Clear progression from foundations and architecture to AI integration and real-world applications
- Dedicated focus on how AI transforms digital twin intelligence and autonomy
- Case studies demonstrating implementation across major sectors
- Insight into future trends, research challenges, and opportunities
Readership
Readership
Computer Science researchers, software engineers, programmers, and software researchers in academia and industry, including software engineers, software developers, and architects who are interested in developing software that includes digital twins. The book will also cater to developers, researchers, or professionals working with digital twins in artificial intelligence, machine learning who are looking to learn more about digital twins integration in Software Engineering and ML apps development
Table of contents
Table of contents
PART I: Introduction and foundations of digital twins
1. Introduction - Bedir Tekinerdogan and Cor Verdouw
2. Modeling artificial intelligence integration in digital twins: a systematic survey - Bedir Tekinerdogan and Cor Verdouw
3. Autonomous digital twins: foundations, challenges, and future directions - Wallace Manzano, Valdemar V. Graciano Neto, Bedir Tekinerdogan and Elisa Y. Nakagawa
PART II: AI integration in digital twins
4. System engineering and artificial intelligence integration principles of digital-twins for tactical edge environments - Muhammad A. Chauhan, Iqbal Gondal, Muhammad A. Babar and Haifeng Shen
5. Artificial intelligence-augmented digital twins: a comparative study of machine learning and large language model integration in smart systems - Yara Ayman Abouelenin and Manar Jammal
6. Enhancing Internet of Things security through artificial intelligence and digital twins - Adela N. Videsjorden, Arda Goknil, Ashish Rauniyar, Erik J. Husom, Rustem Dautov, Leonard Tudorache and Ivan Kurtev
7. Digital twins for artificial intelligencebased simulation of upcoming payment trends - Andreas Speck, Thomas Stuht and Melanie Roering
8. Optimizing agricultural sustainability: integrating the power of digital twin and artificial intelligence for renewable energy management - Hikmet Can Doğancı and Ebru Gökalp
9. Towards intelligent immersive systems: the convergence of digital twins, extended reality, and artificial intelligence - Seyedehfaezeh M. Parsa, Bedir Tekinerdogan, William Hurst and Majid Zare-Bidaki
10. Cloud-native digital twins for enhanced autonomous vehicle safety - George Daoud, Zubair Islam, Mohammad Yasser Zaki, Mohamed El-Darieby and Reza R. Far
PART III: Software and systems engineering
11. Enhancing automation and manufacturing with digital twin systems - Sarthak Jindal, Atul Mishra and Alok Mishra
12. Exploring the concept and use of organizational digital twin - Maria-Isabel Sanchez-Segura, Fuensanta Medina- Dominguez and Juan-Miguel Gomez-Berbis
13. Data clumps as structural indicators in digital twin software: a static analysis perspective - Nils Baumgartner, Alexander Tessmer, Padma Iyenghar and Elke Pulvermüller
14. Intent-based unmanned aerial vehicle control: enabling unmanned aerial vehicle autonomy through large language model-based digital twin control - Hediye Orhan, Esma Nisa Candan, Alperen Eroğlu and Hüseyin Haklı
15. DevOps for and by digital twins leveraging virtual replicas in continuous software engineering - Gwendal Beaumont, Antoine Beugnard, Jannik Laval, Salvador Martínez, Souad R. Chaniour, Christelle Urtado, Sylvain Vauttier and Bérenger Akodo
PART IV: Application domains
16. Digital twin underwater game engine environment for generating deep learning fish detection datasets - Ivan Nikolov, Sebastian Whitehead, Jonas Lind, Rasmus Jacobsen, Arlonsompoon Lind and Mads Sørensen
17. Toward digital twins in the petroleum industry: opportunities and challenges - Marya Al Amri, William Hurst, Kwabena Bennin and Bedir Tekinerdogan
18. The digital twin revolution: optimizing healthcare built environments for safety, efficiency, and resiliency - Marwa Elkashif and Alshimaa A. Farag
19. Reducing errors in disaster management data with digital-twin architecture - Yusuf Kaşan, Mehmet Akşit, Umutcan Ayasandır, Nail Karabay and Seher Turan
20. Digital twins for disaster management: mitigating structural obstacles in the response pipeline - Togay Yazar, Yusuf Kaşan, Seher Turan and Mehmet Akşit
21. Digital twin-based reference architecture for smart greenhouses - Gürkan Soykan, Önder Babur, Qingzhi Liu and Bedir Tekinerdogan
Conclusion
Acknowledgements
References
Index
1. Introduction - Bedir Tekinerdogan and Cor Verdouw
2. Modeling artificial intelligence integration in digital twins: a systematic survey - Bedir Tekinerdogan and Cor Verdouw
3. Autonomous digital twins: foundations, challenges, and future directions - Wallace Manzano, Valdemar V. Graciano Neto, Bedir Tekinerdogan and Elisa Y. Nakagawa
PART II: AI integration in digital twins
4. System engineering and artificial intelligence integration principles of digital-twins for tactical edge environments - Muhammad A. Chauhan, Iqbal Gondal, Muhammad A. Babar and Haifeng Shen
5. Artificial intelligence-augmented digital twins: a comparative study of machine learning and large language model integration in smart systems - Yara Ayman Abouelenin and Manar Jammal
6. Enhancing Internet of Things security through artificial intelligence and digital twins - Adela N. Videsjorden, Arda Goknil, Ashish Rauniyar, Erik J. Husom, Rustem Dautov, Leonard Tudorache and Ivan Kurtev
7. Digital twins for artificial intelligencebased simulation of upcoming payment trends - Andreas Speck, Thomas Stuht and Melanie Roering
8. Optimizing agricultural sustainability: integrating the power of digital twin and artificial intelligence for renewable energy management - Hikmet Can Doğancı and Ebru Gökalp
9. Towards intelligent immersive systems: the convergence of digital twins, extended reality, and artificial intelligence - Seyedehfaezeh M. Parsa, Bedir Tekinerdogan, William Hurst and Majid Zare-Bidaki
10. Cloud-native digital twins for enhanced autonomous vehicle safety - George Daoud, Zubair Islam, Mohammad Yasser Zaki, Mohamed El-Darieby and Reza R. Far
PART III: Software and systems engineering
11. Enhancing automation and manufacturing with digital twin systems - Sarthak Jindal, Atul Mishra and Alok Mishra
12. Exploring the concept and use of organizational digital twin - Maria-Isabel Sanchez-Segura, Fuensanta Medina- Dominguez and Juan-Miguel Gomez-Berbis
13. Data clumps as structural indicators in digital twin software: a static analysis perspective - Nils Baumgartner, Alexander Tessmer, Padma Iyenghar and Elke Pulvermüller
14. Intent-based unmanned aerial vehicle control: enabling unmanned aerial vehicle autonomy through large language model-based digital twin control - Hediye Orhan, Esma Nisa Candan, Alperen Eroğlu and Hüseyin Haklı
15. DevOps for and by digital twins leveraging virtual replicas in continuous software engineering - Gwendal Beaumont, Antoine Beugnard, Jannik Laval, Salvador Martínez, Souad R. Chaniour, Christelle Urtado, Sylvain Vauttier and Bérenger Akodo
PART IV: Application domains
16. Digital twin underwater game engine environment for generating deep learning fish detection datasets - Ivan Nikolov, Sebastian Whitehead, Jonas Lind, Rasmus Jacobsen, Arlonsompoon Lind and Mads Sørensen
17. Toward digital twins in the petroleum industry: opportunities and challenges - Marya Al Amri, William Hurst, Kwabena Bennin and Bedir Tekinerdogan
18. The digital twin revolution: optimizing healthcare built environments for safety, efficiency, and resiliency - Marwa Elkashif and Alshimaa A. Farag
19. Reducing errors in disaster management data with digital-twin architecture - Yusuf Kaşan, Mehmet Akşit, Umutcan Ayasandır, Nail Karabay and Seher Turan
20. Digital twins for disaster management: mitigating structural obstacles in the response pipeline - Togay Yazar, Yusuf Kaşan, Seher Turan and Mehmet Akşit
21. Digital twin-based reference architecture for smart greenhouses - Gürkan Soykan, Önder Babur, Qingzhi Liu and Bedir Tekinerdogan
Conclusion
Acknowledgements
References
Index
Product details
Product details
- Edition: 1
- Latest edition
- Published: May 28, 2026
- Language: English
About the editors
About the editors
BT
Bedir Tekinerdogan
Dr. Bedir Tekinerdogan is a full professor and chair of the Information Technology group at Wageningen University in The Netherlands. He received his MSc degree (1994) and a PhD degree (2000) in Computer Science, both from the University of Twente, The Netherlands. From 2003 until 2008 he was a faculty member at University of Twente, after which he joined Bilkent University until 2015. He has more than 20 years of experience in software engineering research and education. His main research includes the engineering of smart software-intensive systems. In particular, he has focused on and is interested in software architecture design, software product line engineering, model-driven development, parallel computing, cloud computing and system of systems engineering. He has been active in dozens of national and international research and consultancy projects with various large software companies whereby he has worked as a principal researcher and leading software/system architect. He has developed and taught more than 15 different academic software engineering courses and has provided software engineering courses to more than 50 companies in The Netherlands, Germany and Turkey.
Affiliations and expertise
Wageningen University, Wageningen, The NetherlandsCV
Cor Verdouw
Dr. Cor Verdouw is a senior scientist at Wageningen University & Research in The Netherlands. He holds a degree in Business Economics from Erasmus University Rotterdam and received his Ph.D. from Wageningen University. His research focusses on key areas such as business informatics, agri-food chains and digital innovation. He has over 20 years of experience in research and education within this field. He has extensive expertise in coordinating national and European research and innovation projects across diverse agri-food sectors. In addition to his academic work, he has gained industry experience as a business consultant and as an innovation manager at a horticulture-focused software company.
Affiliations and expertise
Wageningen University, The Netherlands