Dynamic safety prewarning mechanism of human–machine–environment using computer vision

Abstract

PurposeThis study provides a safety prewarning mechanism, which includes a comprehensive risk assessment model and a safety prewarning system. The comprehensive risk assessment model is capable of assessing nine safety indicators, which can be categorised into workers’ behaviour, environment and machine-related safety indicators, and the model is embedded in the safety prewarning system. The safety prewarning system can automatically extract safety information from surveillance cameras based on computer vision, assess risks based on the embedded comprehensive risk assessment model, categorise risks into five levels and provide timely suggestions.Design/methodology/approachFirstly, the comprehensive risk assessment model is constructed by adopting grey multihierarchical analysis method. The method combines the Analytic Hierarchy Process (AHP) and the grey clustering evaluation in the grey theory. Expert knowledge, obtained through the questionnaire approach, contributes to set weights of risk indicators and evaluate risks. Secondly, a safety prewarning system is developed, including data acquisition layer, data processing layer and prewarning layer. Computer vision is applied in the system to automatically extract real-time safety information from the surveillance cameras. The safety information is then processed through the comprehensive risk assessment model and categorized into five risk levels. A case study is presented to verify the proposed mechanism.FindingsThrough a case study, the result shows that the proposed mechanism is capable of analyzing integrated human-machine-environment risk, timely categorising risks into five risk levels and providing potential suggestions.Originality/valueThe comprehensive risk assessment model is capable of assessing nine risk indicators, identifying three types of entities, workers, environment and machine on the construction site, presenting the integrated risk based on nine indicators. The proposed mechanism, which adopts expert knowledge through Building Information Modeling (BIM) safety simulation and extracts safety information based on computer vision, can perform a dynamic real-time risk analysis, categorize risks into five risk levels and provide potential suggestions to corresponding risk owners. The proposed mechanism can allow the project manager to take timely actions.

Barriers to the Adoption of New Safety Technologies in Construction: A Developing Country Context

“…This is partly due to construction sites being dynamic, fast-paced, and risky. The high rate of accidents is also attributed to conventional work processes: these are very labor-intensive with few technological advances, involving unsafe behaviors, use of heavy machinery, and dangerous working conditions (Xu & Wang, 2020;Zhou et al, 2015). Furthermore, the construction also reported a considerably high incidences of work-related musculoskeletal disorders (WMSDs) among the workers (Rwamamara et al, 2010).…”

“…In this regard, innovative solutions can provide safety and operational value on construction sites: safer worksites to better safeguard workers (Oesterreich & Teuteberg, 2016). For example, safety simulation using information from surveillance cameras is capable of analyzing integrated human-machine-environment risk to provide dynamic safety prewarnings to allow timely corrective actions (Xu & Wang, 2020). True automation of safety, security, and operational tasks can save time and reduce errors -making worksites run faster, safer, and smarter (Edirisinghe, 2019;Oesterreich & Teuteberg, 2016;Pan & Zhang, 2021).…”

Combining multi-criteria decision making (MCDM) methods with building information modelling (BIM): A review

“…For each of the domains, several subdomains were further identified to narrow down this classification. Building health evaluation [29] Fall protection planning [66] Safety prewarning mechanism [102] Fire risk assessment [106] Constructability Constructability assessment [31,41,42] 8…”

Computer Vision-Based Construction Process Sensing for Cyber–Physical Systems: A Review

“…Similarly, there is a lack of research on how to further utilize the information extracted from the images by computer vision methods to systematically improve the intelligence of the construction process. Among the above literature, only [ 112 ] conducted a construction safety analysis based on the relationship between worker, equipment, and materials at the construction site. The method proposed in this paper relies mainly on expert scoring, which is subjective and needs further validation for applicability between different scenarios.…”