Buchumschlag

Developing a CityGML-based Graph Data Model for Utility Infrastructure in Smart Cities

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Veröffentlicht in:ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences vol. X-G-2025 (2025), p. 405
1. Verfasser: Ensiyeh Javaherian Pour
Weitere Verfasser: Atazadeh, Behnam, Rajabifard, Abbas, Sabri, Soheil
Veröffentlicht:
Copernicus GmbH
Schlagworte:
Data management
Complexity
Data loss
Infrastructure
Graph theory
Data structures
Cities
Smart cities
Data models
Remote sensing
Interoperability
Datasets
Photogrammetry
Graphs
Integrated approach
Connectivity
Resource Description Framework-RDF
Spatial data
Internet of Things
Semantics
IoT devices
Economic
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Abstract:Graph data models are essential for the development of smart cities, where interconnected systems such as utility networks, transportation, and IoT devices must function cohesively. The complexity of smart city infrastructure necessitates 3D data structures capable of managing intricate relationships, dynamic environments, and high connectivity across diverse systems. Graph data models are particularly suited for this purpose, as they offer an integrated 3D digital representation of urban complexity and interconnectivity. This study employs the Labelled Property Graph (LPG) framework to develop a 3D graph data model based on the Utility Network Application Domain Extension (ADE) of the CityGML standard. The proposed approach enhances utility network data management, enabling advanced analyses such as connectivity assessment and pathfinding. The developed graph data model is evaluated in terms of constraint preservation, information integrity, and connection realism. Results demonstrate that the model accurately represents real-world utility network structures while preventing data loss and duplication.
ISSN:2194-9042
2194-9050
DOI:10.5194/isprs-annals-X-G-2025-405-2025
Quelle:Engineering Database