Indoor navigation supported by the Industry Foundation Classes (IFC)

Abstract

Building Information Modeling (BIM) represents a new technology which supports the creation and management of a construction project for buildings. The most well-known open BIM standard, the Industry Foundation Classes (IFC), provides the detailed 3D geometry and rich spatial semantics. It has drawn growing attention of researchers working in geographical information science (GIS). In many related applications, indoor navigation greatly benefits from IFC since it requires the information about building interiors. IFC provides the semantics and geometry of building, and topological relationships of building elements can be readily derived. These three types of information are extensively used in the research on indoor navigation. In this paper we review the current approaches, applications and solutions developed for different aspects of indoor navigation, and summarize the latest status about the use of IFC-based BIM for indoor navigation. In the literature regarding both IFC and indoor navigation, a total of 87 related papers are identified and categorized. 30 papers relate to the generation of indoor navigation models; 20 papers are about model conversion and data modeling on the basis of the IFC schema; 13 papers refer to IFC applications with dynamic environments; 14 papers focus on the support of IFC to indoor localization; and the other papers involve various topics such as visualization and network queries based on IFC. We find that the most active research direction is to generate navigation models from IFC data, yet there is no robust automation method of the generation. By discussing the pros and cons of the current applications, this paper suggests three new directions for further research on the IFC supports to indoor navigation. That is, researchers can further investigate the vertical dimension of the 3D geometry in IFC, facilitate the transformation from IFC to standardized indoor navigation models and manage real-time data with IFC to reflect indoor changes.