This research project focuses on the development of new methods and frameworks to automatically process point clouds, acquired from construction projects. Point clouds provide 3D representation of the surface of objects built on construction sites. Such information can be utilized for as-built geometric digital twin modeling, progress monitoring, structural health monitoring, quality control and surface defect assessment. Point clouds can be acquired by different means, such as laser scanners and overlapping images. The point cloud may also be collected at stationary locations, such as in terrestrial laser scanners (TLS), or dynamically using mobile devices, such as drone images. In both cases, it is also possible to automate the process of collection of point clouds through robot integration (e.g., self-driving robots). The image on the left provides a visual representation of point clouds acquired from the same scene using overlapping images through structure-from motion (SfM), and TLS.