Automated progress monitoring of building construction
Suggested elective courses: Laser scanning, Scene Understanding with Unmanned Aerial Vehicles / other deep learning courses, Programming courses (python)
No fieldwork included/required
The research is part of the Digital Twins @ ITC - Ingenuity project. A developer working on the project is available as advisor.
3D models such as Building information models (BIM) are valuable for industry for various planning purposes. One application is automated building construction monitoring. Data acquired from the field during the construction can be matched against the BIM plans to monitor the construction process.
In this MSc project, the student is expected to research methods on how labelled 3D point clouds can be matched against the elements in a BIM model. Labels for the point cloud are obtained by running a readily available deep learning networks on the dataset from the new ITC building.
See background information: Lehtola, V. V., Nikoohemat, S., & Nüchter, A. (2021). Indoor 3D: Overview on scanning and reconstruction methods. Handbook of Big Geospatial Data, 55-97.
Machine/deep learning methods for indoor point cloud classification. Programming is done with python3. Labelled point clouds and labelled BIM models from the new ITC building (under construction) are made available.
Lehtola, V. V., Nikoohemat, S., & Nüchter, A. (2021). Indoor 3D: Overview on scanning and reconstruction methods. Handbook of Big Geospatial Data, 55-97.
https://isprs-annals.copernicus.org/articles/X-1-W1-2023/461/2023/