Fenz, S., Bergmayr, J., & Giannakis, G. (2023). IFC-based building renovation scenario generator. In Proceedings of the 2023 European Conference on Computing in Construction and the 40th International CIB W78 Conference. 2023 European Conference on Computing in Construction and the 40th International CIB W78 Conference, Heraklion, Greece. https://doi.org/10.35490/EC3.2023.170
E194-04 - Forschungsbereich Data Science E194 - Institut für Information Systems Engineering
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Published in:
Proceedings of the 2023 European Conference on Computing in Construction and the 40th International CIB W78 Conference
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ISBN:
978-0-701702-73-1
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Date (published):
2023
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Event name:
2023 European Conference on Computing in Construction and the 40th International CIB W78 Conference
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Event date:
10-Jul-2023 - 12-Jul-2023
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Event place:
Heraklion, Greece
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Number of Pages:
7
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Peer reviewed:
Yes
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Keywords:
building renovation planning; BIM; scenario generator; IFC
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Abstract:
Increasing the building renovation rate is key to drive energy efficiency in the sector and contribute to the European Green Deal. The RenoDSS building renovation scenario generator, developed within the H2020 project BIMERR, generates IFC files that represent potential renovated building configurations based on: (i) the IFC representation of the current building configuration, (ii) potential renovation measures selected by the user and their defined mapping to IFC elements, and (iii) a rule set on how these renovation measures can be combined and applied on the building. The automated and BIM-based approach enables the efficient generation of renovation scenarios, the calculation of renovation scenario KPIs, and the identification of the most suitable scenarios by comparing the scenarios' KPIs. Validation at two pilots has shown substantial time savings at generating renovation scenarios, calculating their KPIs, and identifying the most suitable renovation scenario for the individual renovation project.
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Research Areas:
Digital Transformation in Manufacturing: 50% Information Systems Engineering: 50%
