Digital twins are virtual replicas of physical objects, systems, or processes that enable simulation, prediction, and optimization of their behavior. In infrastructure context, digital twins have demonstrated the ability to accurately simulate complex systems, predict potential failures, and optimize performance, leading to enhanced safety and security, reduced downtime, and significant cost savings.

By leveraging advanced algorithms and machine learning techniques, it is possible to automate the generation of digital twins and their corresponding simulation models for various systems, such as water and energy networks, civil structures (e.g., bridges, buildings) and process plants.

The symposium will explore the benefits and challenges of implementing automated digital twin technologies.