Physiological computing for occupational health and safety in construction: Review, challenges and implications for future research. (October 2022) - Fang, Weili; Wu, Dongrui; Love, Peter E.D.; Ding, Lieyun; Luo, Hanbin
Abstract: Recent advances in physiological computing have been made due to Artificial Intelligence and Machine Learning, which have profoundly begun to influence occupational health and safety (OHS) in construction. Acknowledging the current and future use of physiological computing, we address the following research question in this paper: What developments in physiological computing can be used to improve OHS in construction ? Using a narrative systematic review, we examine studies that have used physiological computing in construction to monitor people OHS. Our review indicates that there is a need for physiological computing systems to be: (1) more accurate; (2) portable and easier to use; (3) generalizable across varying work tasks; and (4) accepted by users and their benefits realized. Considering our observations derived from the prevailing literature and practice, we suggest that future research should aim to mitigate OHS risks by focusing on: (1) development of high-quality database; (2) feature engineering extraction by using an array of machine learning techniques; (3) understanding the context and enacting intervention strategies. The upshot of performing such a review is to provide a signpost for future research in physiological computing of OHS in construction.