The adoption of Digital Twins (DTs) in the built environment sector is gradually increasing, as DTs can offer substantial value to all of the associated stakeholders. DTs can be used to construct, manage, maintain, and monitor physical built facilities. However, there are only a few built facilities with available digital models. There are mainly two reasons for this situation. The first reason is that many facilities have no pre-existing digital models from when they were constructed. Secondly, even if digital models exist, they were not updated through the assets’ lifecycle. Hence, digital models are missing all asset modifications. This substantially reduces the reliability and usability of the data.
Existing capturing technologies such as laser scanning or photogrammetry allow the automation of data acquisition for geometric models. However, the generation of semantically rich DTs is a complex process that is extremely labour-intensive. In this Focus Group, the aim is to develop methods that can reconstruct 3D models of the built environment from point clouds automatically or semi-automatically, using interdisciplinary methods across construction engineering and computer vision. The ultimate objective of the work is to automatically construct accurate geometric models enriched with semantic and contextual information through employing state-of-art artificial intelligence techniques.
TUM-IAS funded doctoral candidate:
Yuandong Pan, Computational Modeling and Simulation