Computer vision and IoT research landscape for health and safety management on construction sites

Arshad, Sameen; Akinade, Olugbenga; Bello, Sururah; Bilal, Muhammad

Abstract

Aims: Perform a systematic review of current literature to evaluate and summarise the health and safety hazards on construction sites. Methods: Science Direct, SCOPUS and web of science databases were searched for research articles published from 2013 to 2021. From an initial search of 350 research articles, we removed the duplicate articles and carried out an analysis of the abstract and full text that focused on health, safety, hazards, behaviour, on-site health and safety and the digital technologies leaving a total of 66 studies included. Results: Computer vision and Internet of Things (IoT) are the dominant technologies for health and safety management. A comparison of the two technologies reveals that computer vision is dominant because of its non-intrusive approach to data collection; thus, supporting the scalability of computer vision approach at the expense of cost and development time. It will help to prevent on-site health and safety hazards and injuries on construction site. Conclusion: Computer vision offers non-intrusive benefits over Internet of Things (IoT); being able to detect the health and safety hazards. Computer vision has proved to be beneficial for better accuracy prediction, real time data monitoring, and model development for onsite health and safety analytics on the construction site.

Citation

Arshad, S., Akinade, O., Bello, S., & Bilal, M. (2023). Computer vision and IoT research landscape for health and safety management on construction sites. Journal of Building Engineering, 76, Article 107049. https://doi.org/10.1016/j.jobe.2023.107049

• Journal Article Type: Article
• Acceptance Date: Jun 8, 2023
• Online Publication Date: Jun 15, 2023
• Publication Date: Oct 1, 2023
• Deposit Date: Aug 25, 2023
• Publicly Available Date: Aug 25, 2023
• Journal: Journal of Building Engineering
• Electronic ISSN: 2352-7102
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 76
• Article Number: 107049
• DOI: https://doi.org/10.1016/j.jobe.2023.107049
• Keywords: Mechanics of Materials; Safety, Risk, Reliability and Quality; Building and Construction; Architecture; Civil and Structural Engineering
• Public URL: https://uwe-repository.worktribe.com/output/10892501
• Additional Information: This article is maintained by: Elsevier; Article Title: Computer vision and IoT research landscape for health and safety management on construction sites; Journal Title: Journal of Building Engineering; CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.jobe.2023.107049; Content Type: article; Copyright: © 2023 The Authors. Published by Elsevier Ltd.