Interlinking BIM and GIS data for a semantic pedestrian network and applications in high-density cities

Abstract

In high-density cities, pedestrians frequently traverse many publicly accessible indoor spaces, such as metro stations and footbridges, which seamlessly connect with outdoor sidewalks, forming indoor-outdoor combined pedestrian networks. However, the information island phenomenon hinders these connections in the digital world because outdoor sidewalks and indoor spaces are modelled using Geographical Information Systems (GIS) and Building Information Modelling (BIM) technologies, respectively, which challenges obtaining integrated information for intelligent pedestrian services. This study presents an approach for interlinking BIM and GIS data for a semantic pedestrian network using semantic web technologies. The proposed approach automatically converts BIM and GIS data into linked data and establishes interlinkages between BIM and GIS data through semantic queries and inferences. The resulting semantic pedestrian network based on integrated linked data graphs forms a knowledge base, including topological and geometrical information and abundant semantic information from BIM and GIS datasets. The application potential of the semantic pedestrian network is demonstrated through information query and semantic route planning. This research contributes to establishing indoor-outdoor combined semantic pedestrian networks ensuring seamless data integration.