Computational Geometric Approach for BIM Semantic Enrichment to Support Automated Underground Garage Compliance Checking

Abstract

The need for manual semantic annotation to domain-specific building information modeling (BIM) models limits the application of BIM technology in various architecture, engineering, and construction fields. BIM semantic enrichment refers to a procedure that can identify missing information and improve interoperability across different applications. The need for semantic enrichment of BIM models is often emphasized in the literature; however, few studies have shown the potential of semantic enrichment approaches in dealing with problems in real-world cases. To provide an empirical demonstration in the practice, an example of BIM semantic enrichment for supporting underground garage compliance checking is selected as a case study. Geometric reasoning is one of the effective approaches to enhance semantic information in BIM models to support real-world applications. In this study, a computational geometric approach is developed to demonstrate how geometric information can be extracted and used to infer missing semantics in underground garage BIM models. A prototype system is developed, and real underground garage BIM models are used to validate the effectiveness of the proposed approach. The contribution of this study is that it provides the detailed implementation of performing geometric reasoning to enhance BIM semantics in real-world cases. Additionally, the findings of this case study show that the proposed computational geometric approach has the potential to enhance the semantics of BIM models to support decision making in real-world engineering problems, and the developed algorithms can be used to automate the compliance checking process of the underground garage.