Development of Semantically Rich 3D Retrofit Models

The use of Building Information Modeling (BIM) has gained considerable interest in new build projects. However, its use in existing assets has been limited to geometric models utilizing point cloud data (PCD) as the primary source of data. The inclusion of nongeometrical data from distributed sources in the geometric model to make it semantically rich has considerable challenges. This paper proposes an approach to provide a framework for generating semantically-rich parametric models for existing assets. Although the geometric information such as length, width, area, and volume can be extracted from PCD, nongeometric data may need to be appended to this to generate genuinely semantically rich models. The comma-separated values (CSV) format is used to represent the data that can be extracted from PCD. In addition, the nongeometric information derived from other sources are appended to the CSV file. Subsequently, the resource description framework (RDF) data are generated from the data in the CSV files. RDF is a commonly used Semantic Web technology for storing, sharing, and reusing information on the web. The RDF data then are used to create the Industry Foundation Classes (IFC) data model by translating RDF into IFC. The IFC file is used to generate three-dimensional (3D) BIM by importing it into any IFC-compliant application. The proposed approach was validated on one part of the Edinburgh Castle, a relatively complex historical building. The choice of building for validating the approach was driven by technical as well as pragmatic reasons. Technically, the robustness of the approach would have been proven if it were shown to work for a complex rather than a relatively simple building. Pragmatically, the authors had access to data on Edinburgh Castle due to an ongoing partnership with Historic Environment Scotland (HES). However, as a result of the validation process, it is suggested that the proposed approach should be applicable to any existing building.