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. 2024 Jun 9;24(12):3761.
doi: 10.3390/s24123761.

Digital Twin Smart City: Integrating IFC and CityGML with Semantic Graph for Advanced 3D City Model Visualization

Phuoc-Dat Lam  1 , Bon-Hyon Gu  1 , Hoang-Khanh Lam  1 , Soo-Yol Ok  1 , Suk-Hwan Lee  1
Affiliations

Digital Twin Smart City: Integrating IFC and CityGML with Semantic Graph for Advanced 3D City Model Visualization

Phuoc-Dat Lam et al. Sensors (Basel). .

Abstract

The growing interest in building data management, especially the building information model (BIM), has significantly influenced urban management, materials supply chain analysis, documentation, and storage. However, the integration of BIM into 3D GIS tools is becoming more common, showing progress beyond the traditional problem. To address this, this study proposes data transformation methods involving mapping between three domains: industry foundation classes (IFC), city geometry markup language (CityGML), and web ontology framework (OWL)/resource description framework (RDF). Initially, IFC data are converted to CityGML format using the feature manipulation engine (FME) at CityGML standard's levels of detail 4 (LOD4) to enhance BIM data interoperability. Subsequently, CityGML is converted to the OWL/RDF diagram format to validate the proposed BIM conversion process. To ensure integration between BIM and GIS, geometric data and information are visualized through Cesium Ion web services and Unreal Engine. Additionally, an RDF graph is applied to analyze the association between the semantic mapping of the CityGML standard, with Neo4j (a graph database management system) utilized for visualization. The study's results demonstrate that the proposed data transformation methods significantly improve the interoperability and visualization of 3D city models, facilitating better urban management and planning.

Keywords: 3D visualization; CityGML; building information model (BIM); digital twin; industry foundation classes (IFC); smart city.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
The detailed workflow of the proposed methodology for data visualization in city modeling.
Figure 2
Figure 2
Workflow of the 3D mesh generation process for visualization scenarios.
Figure 3
Figure 3
The semantic mapping rule between IFC and CityGML entities. Note: “*” UML notation used to representation the cardinal relationship among CityGML classes that shows the number of occurrence or possibilities and an intermediately model is shown inside the red box.
Figure 4
Figure 4
Parent/child lookup features (above) and conversion from IfcBuilding to CityGML Building (below).
Figure 5
Figure 5
A simple conversion, converting IfcSpace to CityGML Room (above) and IfcPlate–IfcWindow to CityGML Window (below).
Figure 6
Figure 6
Complex conversion of CityGML Building Installation (above) and Wall Surface (below).
Figure 7
Figure 7
The hierarchical CityGML tree structure of building-type community center sample.
Figure 8
Figure 8
Example of CityGML Building envelope and literal.
Figure 9
Figure 9
Illustration of Attribute Structure in CityGML: A Generic Example.
Figure 10
Figure 10
The candidate attributes rules of the CityGML structure sample.
Figure 11
Figure 11
The candidate attributes rules of the RDF structure sample.
Figure 12
Figure 12
Example of predicate registration in CityGML-IFC core: cityObjectMember is a predicate.
Figure 13
Figure 13
Example of attribute registration within a CityGML tag: an attribute example with gml:Envelope.
Figure 14
Figure 14
The workflow involves converting CityGML data into the Cesium 3D Tiles format.
Figure 15
Figure 15
The implementation process from CityGML to Cesium 3D Tiles.
Figure 16
Figure 16
Visualizing 3D Objects with Metadata Animation Using KML in the Cesium Web Service.
Figure 17
Figure 17
3D geometry and properties results of the CityGML model via FME Inspector.
Figure 18
Figure 18
3D geometry and properties results of the CityGML model via FME inspector.
Figure 19
Figure 19
Graph representation for CityGML: (a) RDF Neo4j sample and (b) RDF graph and OWL classes of IfcCurtainWall entity.
Figure 20
Figure 20
(a) Highlighted individual building elements in the Converted 3D Tiles of Cesium Ion and queried properties of highlighted building elements, (b) visualization of time series data, (c) visualizations of 2-floor models (left) and 3-floor models (right).
Figure 21
Figure 21
(a) Building element and (b) road furniture model and (c) the inside building in Unreal Engine 5.0.
See this image and copyright information in PMC

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