Real-time identification and prevention of safety risks in dynamic construction activities are demanded by construction safety managers to cope with the growing complexity of the construction site. Most of the studies on BIM-based construction safety inspection and prevention use data from the planning and design stage. Meanwhile, safety managers still need to spend a lot of time gathering reports about construction safety risks in certain periods or areas from inferred results in BIM. Therefore, this paper proposed an automatic safety risk identification and prevention mechanism for the construction process by integrating a safety rule library based on ontology technology and Natural Language Processing. An automatic inspection mechanism integrating BIM and safety rules is constructed, and a presentation mechanism of intelligent detection results based on Natural Language Processing is designed. The construction process safety rule checking system was developed, and the effectiveness of the system was verified by a case study. The outcome of this paper contributes to the development and application of ontology in construction safety research, and the NLP-based safety rule checking result presentation will benefit safety inspectors and construction managers in practice.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.