Application of Artificial Intelligence for Construction Workers Wellbeing in South Africa

Abstract

Globally, the construction industry is known for its complexity, where a multi-array of interdependent activities all take place at the same time. Construction job sites are increasingly dangerous with historically low levels of innovations and adaptation to change. Construction workers are required to perform repetitive manual tasks involving heavy lifting, bending, twisting, reaching overhead or away from the body and working under generally unfavorable conditions. Construction companies have a moral and legal responsibility to ensure working environments for their workers that do not present a threat to their health, safety and general wellbeing. The purpose of this study is to explore how the application of disruptive AI technologies could improve construction workers’ wellbeing and safety on the job site. This paper reviewed previous studies on the application of AI on construction workers’ wellbeing such as, for example, Weak AI, Strong AI, Machine Learning, Deep Learning and Big Data. Furthermore, keywords such as, for example, Construction, Workers, Health and Safety, Artificial Intelligence and Wellbeing were used to search online databases. The findings of this study indicated that the integration of AI on construction job sites may be used to prevent negative and health and safety prejudicial occurrences from happening by monitoring and tracking the workforce and their construction activities using, for example, applications (apps), wearables or emotional wellbeing tools. Moreover, the complex industry could benefit from machine learning to bank an unlimited amount of data for better overall health and safety performance. Based on the findings, the benefits of AI technologies imbued with machine learning, have a far-reaching impact than the negatives as traditional health and safety systems continue to fail to eliminate construction accidents. Therefore, the adoption of AI could help improve construction workers wellbeing.