Automated Extraction of Locational Information from IFC-Based Building Information Models

Locational information in building information models (BIMs) is essential for providing geographical context to a project as well as the relative spatial context to each and every individual building element that the project is composed of. From a construction automation perspective, one main application is the use of locational data as input for robot-assisted operations in the construction of building components. Nevertheless, obtaining locational information is a time-intensive, laborious, and error-susceptible process. To address this gap, the authors proposed a logic-based approach for examining BIMs and retrieving the positional data of building elements. A duplex apartment model was used to test the proposed method, which achieved 100% precision and 92.31% recall compared to a gold standard. Building elements, such as columns and beams, from the model were successfully extracted. Results show that logic representation and reasoning can be effectively used for extracting locational information in the context of construction automation.