Abstract
Abstract. Nowadays, the complexity of structures in urban environments and the interest in location-based applications increase simultaneously. Along with this is the rise in demand for the firm establishment of data models representing these spaces. Establishing network models that portray topological relationships of space have strengthened support for navigation applications. However, researchers have revisited the limitations of existing standards. As analogous standards have specifications for expressing space at various scales, most have focused on outdoor space or the geometric aspect. Hence, this paper proposes subspacing requirements for a Level of Detail (LOD) model for network-based topological data. We examine various constraints that influence space partition and align these with various application cases for indoor navigation. Through these, we investigate appropriate space subdivision approaches for each level according to applicable constraints and recommended applications. This study poses as an initial study towards establishing a general framework for implementing a 3D hierarchical network-based topological data model.
Highlights
The spatial data requirements for indoor location-based services (LBS) increase continuously with the accelerated development of urban areas and complex structures
While analogous data models such as CityGML have specifications for multi-scale data representation, and the same has been explored for indoor geometric datasets, literature has been lacking in describing Levels of detail for topological data, especially network-based models
We presented an indoor space Level of Detail (LOD) specification for network-based topological data
Summary
The spatial data requirements for indoor location-based services (LBS) increase continuously with the accelerated development of urban areas and complex structures. IndoorGML’s network structure composed of nodes and edges represents the indoor spaces and their topological relationships, respectively. This standard’s theoretical background is based on the Node-Relation Structure (NRS), a logical data model which utilizes the Poincare Duality to convert primal space into dual space (Lee and Kwan, 2005). The Logical NRS is the fundamental representation of topological relationships in an indoor environment These relationships are not sufficient to perform network-based. We propose a level of detail specification for establishing indoor network-based topological data. The section discusses studies related to specifying LOD specifications, approaches to subspacing, and application cases of indoor navigation. The final section discusses the conclusions of the study and further studies on the topic
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
