Big Data and Computer Vision Applications in Construction Safety Management: Complementary Features, Challenges, and Future Research Directions

In recent years, big data (BD) and computer vision (CV) technologies have had an enormous impact on construction safety management; however, no study has discussed their complementary features for construction safety management. Despite extensive review studies on this domain, limited research has explored the challenges and future research directions of the application of BD and CV in construction safety management. Therefore, this paper aims to conduct a systematic literature review of the applications of BD and CV technologies in construction safety management. The paper adopted the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to obtain 60 relevant articles from the Scopus database. The results found 10 complementary features that were divided into three categories or levels: (1) complementary features of BD and CV at the application level, which includes (i) bridges; (ii) construction sites and workers; and (iii) expressways, roads, traffic, and vehicles; (2) complementary features of BD and CV at the data and process level, which includes (iv) assessment; (v) identification, tracking, and monitoring; (vi) detection; (vii) estimation and prediction; and (viii) improvement; and (3) complementary features of BD and CV within Industry 4.0, which includes (ix) artificial intelligence and data mining techniques; and (x) Internet of Things (IoT). Moreover, this paper discussed the cross-synthesis challenges of BD and CV applications including (1) advanced data collection and analytics, (2) real-time monitoring and processing, and (3) diverse data integration and scalability. In addition, the challenges and future research directions were proposed. The findings of this study would contribute to providing more valuable case studies and research opportunities for other researchers and practitioners to mitigate construction safety risks and hazards.