Accurate and proactive inspection of constructed objects and identification of their defects and design conformity is vital to both facility management and construction projects. A project’s building information model (BIM) needs to be regularly updated to more accurately reflect the actual site conditions. However, conventional practices lack site-data integration with models and rely on manual, error-prone, and costly updates. This paper proposes and demonstrates a robust technique that uses the industry foundation classes (IFC) schema to automatically update an as-designed BIM based on site observations for inspected building elements. It receives as input an inspected object’s actual type and inspection details including the detected defects/changes, responsible actors, as-built/as-is type, captured images, and time and the date of the inspection. The algorithm automatically analyzes the IFC data model to retrieve the element’s semantics and identifies discrepancies between the as-built/as-is and as-designed object conditions. Based on the results of the discrepancy analysis, the IFC data model is populated with new semantics, resulting in the update of object types, properties, and three-dimensional (3D) shape representations. Inspection details and user entries are automatically documented in the BIM and assigned to objects to enable potential diagnostics and tractability. This automates site-to-BIM data transfer and supports reality-capture techniques.
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Hamledari et al. (2017) studied this question.
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