| id |
cdrf2023_225 |
| authors |
Ziyu Tong, Hang Zheng |
| year |
2023 |
| title |
Generation Scheme of IndoorGML Model Based on Building Information Model |
| doi |
https://doi.org/https://doi.org/10.1007/978-981-99-8405-3_19
|
| source |
Proceedings of the 2023 DigitalFUTURES The 5st International Conference on Computational Design and Robotic Fabrication (CDRF 2023) |
| summary |
In recent years, the concept of City Information Model (CIM) has received wide attention. However, the interior spaces are difficult to handle in CIM due to its complexity in terms of location and connection on 3D. Indoor Geography Markup Language (IndoorGML) is a data format standard for the exchange and representation of indoor space data and provided a method to describe interior space objects for CIM. However, the existing generation process is cumbersome and difficult to integrate semantic information. This study proposed a BIM-based IndoorGML model generation scheme. The scheme took the typical Revit model as the data base, extracted the location and attribute information of elements respectively, then generated the topologically expressed model integrated the semantic information. The study selected a hospital with complex interior spaces as a case study for the generation experiments of IndoorGML model. The result showed that the scheme is highly feasible even for such complex buildings. This study further calculated complex network-related attributes and analyzed the relationship between interior spaces to explore the application potential of the model. |
| series |
cdrf |
| email |
|
| full text |
 file.pdf (4,875,917 bytes) |
| references |
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| last changed |
2024/05/29 14:04 |
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