Foundations of Digital Twins

Digital twin computing is the bridge between the real and virtual worlds, and operates as a mirror that reflects the real world into the virtual world. Digital twin technologies take data from sensor networks in the real world, utilise artificial intelligence and machine learning to analyse the data, and then create a digital representation or simulation that updates as their real world counterpart updates. As such, the model can be used to understand the real world environment, and the digital twin can be used to make informed decisions that will be of benefit in the real world. Foundations of Digital Twins explains the fundamentals of digital twins, how digital twin technologies can gather real world data using the sensor networks that comprise the Internet of Things, and how that data can be sorted, analysed, and utilised to improve services and to increase sustainability. Structured in five sections, the book begins with an introductory overview of each technology, establishing a clear understanding of their individual roles and their potential when combined. The second section delves into data acquisition, featuring advanced sensors, drones, robots and actuators. Part Three considers data exchange and security, focusing on CPS, the internet of things, and blockchain. Part Four looks at how digital twins can impact on data computing, such as video streaming, cloud computing, fog computing and edge-computing. The final section explores the future opportunities and risks of adopting advanced technologies in this evolving field, including artificial intelligence, the ethical issues concerned when collecting and using data, and the security implications. By blending theory with practical insights, Foundations of Digital Twins serves as both an educational resource and a practical guide for researchers, students and professionals seeking to harness the power of these advanced technologies in complex, real world environments.

• Format: Paperback
• Language: English
• ISBN: 044343896X
• ISBN13: 9780443438967
• Release Date: October 2026
• Publisher: Elsevier
• Length: 594 Pages
• Weight: 0.99 lbs.