Proceedings of the

The 33rd European Safety and Reliability Conference (ESREL 2023)
3 – 8 September 2023, Southampton, UK

Machine Learning in Construction Industry: Opportunities and Challenges for Decision-Making and Safety Management

Casper Pilskog Orvika, Vebjørn Ditløvsenb, Elizaveta Bambulyakc and Eirik Albrechtsend

Department of Industrial Economics and Technology Management, Norwegian University of Science and Technology, Norway.


As the construction industry continues to embrace digitalization, machine learning is emerging as a powerful tool to improve efficiency and enhance decision-making throughout the project lifecycle. This study presents an exploration of the potential of machine learning in the construction industry, focusing on reducing accident risks through decision support. Through a combination of workshops and analysis of machine learning applications in other sectors, this study provides insights into the opportunities and challenges associated with machine learning in construction. Results suggest that machine learning tools can enhance information-gathering, visualization of trends, prediction of outcomes, and evaluation of effectiveness. However, challenges such as increased complexity, criticality, and lack of trust in machine learning must be addressed. The study recommends developing a theoretic safety model for machine learning tools, focusing on finding the correct parameters and addressing challenges associated with machine learning. Overall, the study concludes that adopting machine learning can benefit construction, but it is essential to consider these challenges carefully.

Keywords: Machine learning, Accident risk, Decision support, Construction industry, Visionary ML tools, Safety management, Decision-making.

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