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

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.