Journal
JOURNAL OF BUILDING ENGINEERING
Volume 49, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.jobe.2022.103999
Keywords
BIM; Embedded knowledge; Strategy extraction; Automatic control
Funding
- National Science Foundation of China (NSFC) [52178307]
- Natural Science Foundation of Jiangsu Province [BK20210439]
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Building Information Modelling (BIM) has revolutionized the construction industry's production and operations management, but it currently lacks the ability to integrate expert knowledge information to guide the building activity process. To address this issue, researchers have proposed a method that utilizes a knowledge-embedded model and knowledge extraction algorithm to standardize and embed expert knowledge into BIM, enabling knowledge-driven automatic control.
Building information modelling (BIM) has revolutionized production and operations management in the construction industry. Currently, however, the BIM environment can integrate only basic static information. Expert knowledge information to guide the building activity process is lacking. Consequently, with the increasing complexity of building services, BIM has difficulty adapting to the needs of rapid collaboration in the building operation process. To solve this problem, first, we present the basic knowle-dge-embedded model. The model provides services for knowledge generation and knowledge embedding. Moreover, taking BIM-based fire emergency management as an example, the formal modelling and credibility verification of knowledge are adopted to standardize the knowledge generated from experts to reduce future input errors and interpretation. Second, to provide the capability of process knowledge representation in BIM, we embedded the knowledge of the fire emergency management process into BIM by extending the Industry Foundation Classes (IFC) standard and providing a BIM knowledge extraction algorithm using the IFC standard, thereby extracting the control strategy from BIM to achieve the reasoning of knowledge. Finally, we prototyped BIM-Fire in a real building scenario and validated the effectiveness of the method. The automatic control of knowledge-driven BIM-based activities is realized.
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