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Article

Semantic IFC Data Model for Automatic Safety Risk Identification in Deep Excavation Projects

1
School of Management Engineering, Huaiyin Institute of Technology, Huaian 223003, China
2
Department of Construction Management, Huazhong University of Science and Technology, Wuhan 430074, China
3
Department of Civil Engineering, Aston University, Birmingham B4 7ET, UK
*
Author to whom correspondence should be addressed.
Academic Editor: Diana Kalibatiene
Appl. Sci. 2021, 11(21), 9958; https://doi.org/10.3390/app11219958
Received: 15 September 2021 / Revised: 16 October 2021 / Accepted: 22 October 2021 / Published: 25 October 2021
Safety risk identification throughout deep excavation construction is an information-intensive task, involving construction information scattered in project planning documentation and dynamic information obtained from different field sensors. However, inefficient information integration and exchange have been an important obstacle to the development of automatic safety risk identification in actual applications. This research aims to achieve the requirements for information integration and exchange by developing a semantic industry foundation classes (IFC) data model based on a central database of Building Information Modeling (BIM) in dynamic deep excavation process. Construction information required for risk identification in dynamic deep excavation is analyzed. The relationships among construction information are identified based on the semantic IFC data model, involved relationships (i.e., logical relationships and constraints among risk events, risk factors, construction parameters, and construction phases), and BIM elements. Furthermore, an automatic safety risk identification approach is presented based on the semantic data model, and it is tested through a construction risk identification prototype established under the BIM environment. Results illustrate the effectiveness of the BIM-based central database in accelerating automatic safety risk identification by linking BIM elements and required construction information corresponding to the dynamic construction process. View Full-Text
Keywords: safety; risk; BIM; IFC schema; deep excavation safety; risk; BIM; IFC schema; deep excavation
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MDPI and ACS Style

Zhang, Y.; Xing, X.; Antwi-Afari, M.F. Semantic IFC Data Model for Automatic Safety Risk Identification in Deep Excavation Projects. Appl. Sci. 2021, 11, 9958. https://doi.org/10.3390/app11219958

AMA Style

Zhang Y, Xing X, Antwi-Afari MF. Semantic IFC Data Model for Automatic Safety Risk Identification in Deep Excavation Projects. Applied Sciences. 2021; 11(21):9958. https://doi.org/10.3390/app11219958

Chicago/Turabian Style

Zhang, Yongcheng, Xuejiao Xing, and Maxwell Fordjour Antwi-Afari. 2021. "Semantic IFC Data Model for Automatic Safety Risk Identification in Deep Excavation Projects" Applied Sciences 11, no. 21: 9958. https://doi.org/10.3390/app11219958

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