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| Title | Digital Twin Technology Fundamentals |
|---|---|
| ID_Doc | 20242 |
| Authors | Chaiburi C.; Yingngam B. |
| Year | 2024 |
| Published | Digital Twins for Smart Cities and Villages |
| DOI | http://dx.doi.org/10.1016/B978-0-443-28884-5.00001-4 |
| Abstract | The advent of digital twin technology signifies a major shift in diverse sectors, ranging from manufacturing to healthcare. This technology provides a virtual representation of physical systems, enabling real-time monitoring, analysis, and optimization. However, implementing digital twins presents notable challenges, including data integration, scalability, and cybersecurity issues. This chapter aims to offer a comprehensive understanding of digital twin technology, exploring its core principles, applications, and potential impacts. It addresses the challenges of its adoption and proposes strategies for effective implementation. In addition, the chapter discusses the architecture of digital twins, along with their components such as data models, sensors, and analytics and explores various case studies across industries, highlighting the benefits and limitations of digital twins in practical scenarios. It concludes that the potential of digital twin technology for driving innovation and efficiency is significant, yet realizing this potential depends on overcoming critical challenges. The chapter emphasizes the need for interdisciplinary strategies and strong security measures when implementing digital twins. Looking to the future, it identifies potential research areas, including the integration of artificial intelligence and machine learning to boost predictive capabilities and the application of digital twins in burgeoning areas such as sustainable energy and smart cities. © 2025 Elsevier Inc. All rights reserved. |
| Author Keywords | Artificial intelligence; Cybersecurity; Data integration; Digital twins; Industry applications; Predictive analytics; Real-time analysis; Scalability; Sustainable innovation; Virtual modeling |
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