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

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.

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Publication Details

Journal
Proceedings of the Institution of Civil Engineers - Engineering Sustainability
Published
2026-03-23
DOI
https://doi.org/10.1680/jensu.25.00177
Primary Topic
Occupational Health and Safety Research
Type
article
Field-Weighted Citation Impact
0.00
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article

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

Musab Rabi, Fares K. Al-Anazi, Mohammad Al-Zu'bi, Mazen J. Al-Kheetan
Proceedings of the Institution of Civil Engineers - Engineering Sustainability
Occupational Health and Safety Research
article

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

Musab Rabi, Fares K. Al-Anazi, Mohammad Al-Zu'bi, Mazen J. Al-Kheetan
article en

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.

Proceedings of the Institution of Civil Engineers - Engineering Sustainability
Mutah University (JO), Addis Ababa Science and Technology University (ET), Jerash University (JO)
Openalex Percentile: Top 14%
Occupational Health and Safety Research
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