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This study focuses on improving pre-emptive risk recognition and safety checks to prevent workplace accidents. It underscores improvements by addressing existing research issues, suggesting potential enhancements through system development. Work approval procedures and workers’ prior risk awareness, through the confirmation of work safety standards in physically separated work areas, are fundamental methods of preventing serious accidents and creating a safe work environment. A key factor concerning worker safety is recognizing the potential accident risk factors (or hazards) in advance through practical job hazard analysis and consequently take risk-reduction measures in case the safety standards are not met. Despite the crucial significance of pre-awareness of work risks at the majority of construction sites, tools to enhance this awareness are currently limited. Furthermore, real-time detection of work risks and the implementation of risk reduction measures are contingent upon a monitoring environment and a robust safety culture. This study proposed construction worker location-tracking technology that recognizes personal identification (ID). A safety check system based on location tracking combining personal quick response code (QR code) recognition and computer vision technology to automatically identify workers’ personal identities and track their physical location was proposed. A real-time safety check system was implemented to classify automatically whether workers have confirmed hazards and to approve a work process in high-risk workplaces by supervisors. Location-tracking technology with ID recognition performed the following two safety management functions. First, if a construction worker does not pre-check the work risk information before entering the work zone, the geofencing technology automatically classifies workers as those who are not aware of job hazards. Secondly, the safety manager or supervisor entering the on-site work zone possesses the authority to halt work if the work environment fails to meet safety standards and can issue warnings regarding risky situations. Essential functions were validated through a case study involving preliminary testing within the development system. To assess the practical application of the system, virtual simulations were conducted using recorded videos from a construction site to replicate the two essential functions of the system. The system was constructed using an Apache server and Python code, and for testing purposes, the names of the workers were randomized. |
