Artificial intelligence for occupational health and safety management in construction: a systematic review

Savindi Perera, Vidal Paton-Cole, Shang Gao, Valerie Francis, Pinar Urhal, Patrick Manu, Paulo Jorge Da Silva Bartolo, Clara Cheung, Akilu Yunusa-Kaltungo, Akinloluwa Babalola

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


Reducing occupational safety and health (OSH) incidents has been an area of significant importance to the construction industry. The industry remains one of the most dangerous, with significant occupational fatalities and injuries. Artificial intelligence (AI), including deep learning and machine learning, shows promising potential to reduce injuries and avoid fatalities with the possibility for data acquisition of construction site activities and operations. To systematically assess the studies on AI aimed at improving construction safety, this research investigated 192 published journal articles (in English) within the Scopus database to determine the current research gaps and future work suggested by the publications. The analysis revealed a positive trend in publications in this area. Publications were also analysed based on the country of origin of the research and the host journal. The use of algorithms and the development of algorithms to address OSH issues were the most frequently used research methods, while the use of AI for visualisation and identification of hazards were the most frequent applications. Some research gaps and recommendations for future research are also discussed in the chapter.
Original languageEnglish
Title of host publicationHandbook of Construction Safety, Health and Well-being in the Industry 4.0 Era
EditorsPatrick Manu, Gao Shang, Paulo Jorge Silva Bartolo, Valerie Francis, Anil Sawhney
Place of PublicationAbingdon, UK
Number of pages15
ISBN (Electronic)9781003213796
ISBN (Print)9781032079929, 9781032101354
Publication statusPublished - 18 Apr 2023


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