AI safety management for hazard mitigation and worker protection in green construction

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Authors: Fares K. Al-Anazi, Mohammad Al-Zu'bi, Musab Rabi, Mazen J. Al-Kheetan
Cited by: 2
References: 33

Abstract

Recent growth in green construction projects in Saudi Arabia has increased the use of advanced construction systems, necessitating more proactive and intelligent approaches to safety management. This study examines the role of artificial intelligence (AI) in improving hazard mitigation and worker safety in green construction projects. Five AI-enabled components were assessed: hazard detection, risk prediction, wearable smart devices, AI-based training systems, and AI-supported compliance tools. A quantitative descriptive–analytical approach was adopted using a structured questionnaire distributed to 350 employees working on green construction sites. Simple random sampling was applied, and reliability and validity were confirmed through expert review and Cronbach’s alpha testing. Data were analysed using SPSS and AMOS to examine relationships within the proposed model. The findings indicate that all AI components significantly enhance safety performance. AI-based training systems showed the strongest influence (R2 = 0.509), followed by wearable devices (R2 = 0.334), hazard detection (R2 = 0.216), risk prediction (R2 = 0.124), and compliance tools (R2 = 0.060). The results confirm the robustness of the model and demonstrate that AI integration supports predictive safety management, improved compliance, and reduced incidents, aligning with Saudi Arabia’s Vision 2030 sustainability objectives.

Fields of Study & Subjects

Occupational Health and Safety Research Construction Project Management and Performance BIM and Construction Integration

Publication details

Journal / source
Proceedings of the Institution of Civil Engineers - Engineering Sustainability
Publisher
Emerald
Pages
1–13
Publication date
23 March 2026
Language
EN