Design of a 3D Intelligent Building Management Framework that Integrates Geographic Information Systems and Building Information Models

Promoting the construction of 3D intelligent buildings is one of the important paths to achieve high-quality development in the new stage of architecture. This study first constructs a 3D model of an intelligent building based on a building information model, and then collects environmental data using the constructed geographic information system. Finally, a semantic constraint based transformation approach is adopted to integrate multi-source data such as geographic information system data and building information model data, and construct a 3D intelligent building management framework system. The results showed that the selected optimization algorithm could effectively compress the data of the 3D model. Taking the "Car" 3D model data as an example, it could be compressed to 66.4% of the original file. Moreover, in the simplification process, the research method had better results in detail processing. The constructed system could quickly complete the rendering of the 3D model at different distances. The rendering time of the system for the overall appearance of intelligent buildings, intelligent system equipment, and 3D models of pipelines was 9.1s, 12.0s, and 7.2s, respectively. The frame rates during rendering were 35.2-46.2FPS, 27.6-38.1FPS, and 48.2-53.1FPS, respectively. This system achieves precise modeling and management of intelligent buildings, providing theoretical support for the construction of similar building management systems.

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Publication Details

Journal
Informatica
Published
2024-11-05
DOI
https://doi.org/10.31449/inf.v48i16.6031
Primary Topic
3D Modeling in Geospatial Applications
Type
article
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article

Design of a 3D Intelligent Building Management Framework that Integrates Geographic Information Systems and Building Information Models

Hairong Huang, Rongxing Wu, Dong Zheng
Informatica
3D Modeling in Geospatial Applications
article

Design of a 3D Intelligent Building Management Framework that Integrates Geographic Information Systems and Building Information Models

Hairong Huang, Rongxing Wu, Dong Zheng
article en

Abstract

Promoting the construction of 3D intelligent buildings is one of the important paths to achieve high-quality development in the new stage of architecture. This study first constructs a 3D model of an intelligent building based on a building information model, and then collects environmental data using the constructed geographic information system. Finally, a semantic constraint based transformation approach is adopted to integrate multi-source data such as geographic information system data and building information model data, and construct a 3D intelligent building management framework system. The results showed that the selected optimization algorithm could effectively compress the data of the 3D model. Taking the "Car" 3D model data as an example, it could be compressed to 66.4% of the original file. Moreover, in the simplification process, the research method had better results in detail processing. The constructed system could quickly complete the rendering of the 3D model at different distances. The rendering time of the system for the overall appearance of intelligent buildings, intelligent system equipment, and 3D models of pipelines was 9.1s, 12.0s, and 7.2s, respectively. The frame rates during rendering were 35.2-46.2FPS, 27.6-38.1FPS, and 48.2-53.1FPS, respectively. This system achieves precise modeling and management of intelligent buildings, providing theoretical support for the construction of similar building management systems.

InformaticaVol. 48(16)
Ningbo Polytechnic (CN), Zhejiang Tongji Vocational College of Science and Technology (CN)
Sustainable cities and communities
Openalex Percentile: Top 79%
3D Modeling in Geospatial Applications
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Design of a 3D Intelligent Building Management Framework that Integrates Geographic Information Systems and Building Information Models — Hairong Huang, Rongxing Wu, et al. · Informatica (2024) | TGRS Research Map | TGRS