IFC models for semi-automating common planning checks for building permits

Journal Article (2022)
Authors

F. Noardo (TU Delft - Urban Data Science)

T. Wu (TU Delft - Urban Data Science)

GAK Arroyo Ohori (TU Delft - Urban Data Science)

T.F. Krijnen (TU Delft - Urban Data Science)

JE Stoter (TU Delft - Urban Data Science)

Research Group
Urban Data Science
Copyright
© 2022 F. Noardo, T. Wu, G.A.K. Arroyo Ohori, T.F. Krijnen, J.E. Stoter
To reference this document use:
https://doi.org/10.1016/j.autcon.2021.104097
More Info
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Publication Year
2022
Language
English
Copyright
© 2022 F. Noardo, T. Wu, G.A.K. Arroyo Ohori, T.F. Krijnen, J.E. Stoter
Research Group
Urban Data Science
Volume number
134
DOI:
https://doi.org/10.1016/j.autcon.2021.104097
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Abstract

To support building permit issuing with automatic digital tools, the reuse of models produced by designers would make the process quicker and more objective. However, current studies and pilots often leave a gap with respect to the models as actually provided by architects, having varying quality and content. In this study, rather than taking a top down approach, we started from the available data and made the necessary inferences, which gave the opportunity to tackle basic and common issues often preventing smooth automatic processing. Specific characteristics of the IFC models were outlined and a tool was developed to extract the necessary information from them to check representative regulations. While the case study is specific in location, regulations and input models, the type of issues encountered are a generally applicable example for automated code compliance checking. This represents a solid base for future works towards the automation of building permits issuing.