NAVI-graph: a Semantics-based Network for Indoor Pathfinding

Junxiang Zhu1, Mun On Wong2, Nicholas Nisbet3, Jinying Xu1, Judith Fauth1, Ioannis Brilakis1
1 Department of Engineering, University of Cambridge, Cambridge, United Kingdom
2 Department of Civil and Environmental Engineering, University of Macau, Macao
3 Bartlett School of Sustainable Construction, University College London, London, United Kingdom
DOI: 10.35490/EC3.2025.170
Abstract: The conventional approaches for establishing indoor networks for pathfinding are mostly based on geometry processing. The generated networks are geometric networks that lack semantics, which have limited their use. This study proposes a new semantics-driven approach for constructing navigable indoor networks that utilizes the rich semantic information from Industry Foundation Classes (IFC) in the form of IFC-Graph. A real-world building model was used to validate the proposed approach, and the result shows that 1) the sematic-based indoor network is easier to establish from IFC-Graph; 2) the semantics-driven approach can enable semantics-driven pathfinding, which can provide more possibilities in pathfinding applications.
Keywords: Building Information Modeling (BIM), Digital Twin (DT), IFC-Graph, Indoor pathfinding, Industry Foundation Classes (IFC), Labelled property graph

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