Development of a method for the automatic generation of a semantically enriched 3D building model for the determination of components and materials.

The refurbishment of the building sector plays a central role in achieving the climate targets in Germany and Europe. According to Dena, in addition to the residential sector, the heterogeneous non-residential building stock in Germany also requires solutions in order to exploit the decarbonization potential in this area. Unlike for residential buildings, there is still no reliable data available for non-residential buildings that would allow them to be divided into building classes and the renovation requirements of a building to be derived from this. For this reason, Caala, together with the TUM and the IÖR, wants to develop a tool that enables an initial energy, structural and ecological building assessment from data that is already available online. A refurbishment proposal is generated fully automatically for each of these assessments, which always includes current and innovative refurbishment solutions. These variants are automatically enriched with further semantic data as the planning process progresses in order to generate a BIM-capable digital twin of the building.

More information here.

Project partner:

• CAALA GmbH
• Leibniz-Institut für ökologische Raumentwicklung, e.V. (IÖR)

Publications:

• Noichl, F.; Forth, K.; De Wolf, C.; Borrmann, A. (2025): From Point Cloud to Material Passport Automated Creation of Material Passports of Existing Steel Structures based on Point Clouds . EG-ICE 2025, Edinburgh, UK
• Forth, K.; Noichl, F.; Borrmann, A.: LCA Calculation of Retrofitting Scenarios using Geometric Model Reconstruction and Semantic Enrichment of Point Clouds and Images. Proc. of the ASCE International Conference on Computing in Civil Engineering 2023, Corvalis, Orgaon, USA, 2024; DOI: 10.1061/9780784485231.047