| Title |
Automating building element detection for deconstruction planning and material reuse: A case study |
| ID_Doc |
22939 |
| Authors |
Gordon, M; Batalle, A; De Wolf, C; Sollazzo, A; Dubor, A; Wang, T |
| Title |
Automating building element detection for deconstruction planning and material reuse: A case study |
| Year |
2023 |
| Published |
|
| Abstract |
To address the need for a shift from a linear to a circular economy in the built environment, this paper develops a semi-automated assistive process for planning building material deconstruction for reuse using sensing and scanning, Scan-to-BIM, and computer vision techniques. These methods are applied and tested in a real-world case study in Geneva, Switzerland, with a focus on reconstruction and recovery analysis for floor beam sys-tems. First, accessible sensing and scanning tools, such as mobile photography and smartphone-based consumer-grade Lidar devices, are used to capture imagery and other data from an active demolition site. Then, photo-grammetry and point cloud data analysis are performed to construct a 3D BIM model of relevant areas. The structural relationships between reconstructed BIM elements are evaluated to score the feasibility for recovery of each element. This study illustrates what is feasible and where further development is necessary for automating building material reuse planning at scale to increase the uptake of circular economy practices in the construction sector. |
| PDF |
https://doi.org/10.1016/j.autcon.2022.104697
|
