This course aims to provide students with a comprehensive understanding of digital twins and their transformative role in the Architecture, Engineering, Construction, and Operations (AECO) industry. Students will explore the theoretical foundations of digital twins, including their definitions, underlying technologies, and data integration processes. The course delves into case studies, enabling students to understand modeling, simulating, and analyzing digital twins for real-world AECO scenarios. Additionally, students will critically examine the ethical, societal, and sustainability implications of digital twin adoption. By the end of the course, students will be equipped to leverage digital twins as innovative tools for problem-solving, collaboration, and decision-making in the built environment.

The course is structured into three main phases: theoretical foundations, practical applications, and evaluation. In the first phase (Weeks 1–4), students will be introduced to the core concepts of digital twins, including their history, key principles, and enabling technologies such as Building Information Modeling (BIM), the Internet of Things (IoT), and artificial intelligence (AI). Data acquisition, interoperability, and standardization challenges in AECO will also be discussed. The second phase (Weeks 5–11) shifts focus to hands-on learning, where students will analyze case studies of digital twins in construction, infrastructure management, and smart cities. Collaborative research projects will encourage interdisciplinary problem-solving and innovation. The final phase (Weeks 12–14) covers ethical considerations and emerging trends like cognitive digital twins, resilience, and sustainability. Students will present their research reports, demonstrating their ability to understand the theory. The course concludes with a forward-looking discussion on the future of digital twins in AECO, preparing students to contribute to the evolving landscape of the industry.