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

Abstract

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.

The Impact of Artificial Intelligence on Organizational Justice and Project Performance: A Systematic Literature and Science Mapping Review

“…This approach also hints at the potential of AI in decision support systems that can help organizations choose projects more intelligently and make real-time monitoring and adjustments as they are executed. It mentioned that the digital environment is being rapidly transformed due to the development of technologies such as AI, big data, blockchain technology, and cloud computing, indicating both an opportunity and a challenge for organizations [92][93][94]. The COVID-19 pandemic, in particular, has prompted many organizations to go digital rapidly, and digital technologies have become an opportunity to drive development.…”