Achieving Sustainable Construction Safety Management: The Shift from Compliance to Intelligence via BIM–AI Convergence

Heap-Yih Chong, Qinghua Ma, Jianying Lai () and Xiaofeng Liao ()
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Heap-Yih Chong: School of Engineering Audit, Nanjing Audit University, Nanjing 211815, China
Qinghua Ma: School of Engineering Audit, Nanjing Audit University, Nanjing 211815, China
Jianying Lai: School of Engineering Audit, Nanjing Audit University, Nanjing 211815, China
Xiaofeng Liao: School of Civil and Hydraulic Engineering, Chongqing University of Science and Technology, Chongqing 401331, China

Sustainability, 2025, vol. 17, issue 10, 1-19

Abstract: Traditional construction safety management, reliant on manual inspections and heuristic judgments, increasingly fails to address the dynamic, multi-dimensional risks of modern projects, perpetuating fragmented safety governance and reactive hazard mitigation. This study proposes an integrated building information modeling (BIM)–AI platform to unify safety supervision across the project lifecycle, synthesizing spatial-temporal data from BIM with AI-driven probabilistic models and IoT-enabled real-time monitoring for sustainable construction safety management. Employing a Design Science Research methodology, the platform’s phase-agnostic architecture bridges technical–organizational divides, while the Multilayer Neural Risk Coupling Assessment framework quantifies interdependencies among structural, environmental, and human risk factors. Prototype testing in real-world projects demonstrates improved risk detection accuracy, reduced reliance on manual processes, and enhanced cross-departmental collaboration. The system transitions safety regimes from compliance-based protocols to proactive, data-empowered governance. This approach offers scalability across diverse projects. The BIM-AI intelligent fusion platform proposed in this study builds an intelligent construction paradigm with synergistic development of safety governance and sustainability through whole lifecycle risk coupling analysis and real-time dynamic monitoring, which realizes a proactive safety supervision system while significantly reducing construction waste and accident prevention mechanisms.

Keywords: BIM; AI; sustainable construction safety management; proactive; dynamic; prototype; project lifecycle (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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