Wen, Ya;
Wang, Mudan;
Ariyachandra, Mahendrini;
Wei, Ran;
Brilakis, Ioannis;
Xiao, Lizhao;
(2024)
Knowledge Driven Rule-Based Building Geometric Digital Twin Construction: State of the Art Review.
In:
Proceedings of the 2024 European Conference on Computing in Construction.
European Conference on Computing in Constructionan Conference on Computing in Construction: Chania, Crete, Greece.
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Abstract
Automatic construction of the building geometric digital twins (gDTs) is implemented based on the scanned data from the existing buildings. The highly detailed gDTs necessitates the top-down construction method informed by the predefined building knowledge. This paper reviews the building rules used for the model-driven building indoor environment gDTs construction. It is found that these knowledge is fragmented and lacks systematic analysis. The research categorise these rules into three groups and proposes an Ontology-based knowledge graphs (KGs) approach for organising this knowledge. This method aims to integrate rules for gDT construction to establish a knowledge system for the further research.
| Type: | Proceedings paper |
|---|---|
| Title: | Knowledge Driven Rule-Based Building Geometric Digital Twin Construction: State of the Art Review |
| Event: | 2024 European Conference on Computing in Construction |
| Location: | Chania, Greece |
| Dates: | 14th-17th July 2024 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.35490/EC3.2024.250 |
| Publisher version: | http://www.doi.org/10.35490/EC3.2024.250 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions. |
| Keywords: | Digital Twin construction, Model-driven DT construction, Building knowledge, Knowledge driven, Knowledge graph |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10195558 |
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