Seamless AR Safety Training

Seamless AR Safety Training

    Presenter(s)

    Abhijeet Gupta

    Comments

    9:20-9:40, LTC Studio

    Description

    The construction industry remains one of the most hazardous sectors, with a worker losing their life every 99 minutes due to work-related incidents. Despite ongoing advancements in safety protocols, training programs, and regulations, the industry continues to struggle with preventable hazards, particularly falls, electrocutions, and struck-by incidents. Traditional safety measures, including PPE, signage, and worker training, often fall short due to complacency, distractions, and limited real-time hazard awareness. To address these challenges, technology-driven safety solutions are becoming increasingly essential. This study aims to develop an advanced construction safety framework that leverages Augmented Reality (AR) simulations to enhance hazard recognition and safety training. By creating realistic, interactive hazard scenarios, workers can experience high-risk situations in a controlled, immersive environment, leading to improved hazard awareness and response. The AR simulations will focus on four primary hazards—falling, tripping, electrocution, and falling objects—using computer vision and AI-driven hazard detection for real-time safety training. In addition to developing the AR-based framework, this research will systematically review and evaluate twelve emerging safety technologies to assess their effectiveness in preventing construction hazards. These include – Building Information Modeling (BIM), Augmented Reality (AR) & Virtual Reality (VR), Drones, Computer Vision, Wearable Sensors, Internet of Things (IoT) Devices, Predictive Analytics, Proximity Alert Systems, AI/Machine Learning (AI/ML), Safety Management Systems, Digital Twins, Robotics & Automation. The study will construct a technology taxonomy to categorize these solutions and conduct a comparative analysis of pre-2020 and post-2020 research, highlighting how recent advancements have addressed prior limitations. By integrating real-time hazard detection using AR with a comprehensive review of emerging safety technologies, this research aims to provide insights for improving construction safety standards, reducing major workplace fatalities, and enhancing worker training and preparedness.

    Publication Date

    4-23-2025

    Project Designation

    Graduate Research

    Primary Advisor

    Vijayan K. Asari, Tam Nguyen

    Primary Advisor's Department

    Computer Science

    Keywords

    Stander Symposium, College of Arts and Sciences

    Institutional Learning Goals

    Scholarship; Critical Evaluation of Our Times; Community

    Seamless AR Safety Training

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