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oapen-20.500.12657-891172024-04-03T02:23:44Z Chapter Enhancing the Realism of Virtual Construction Safety Training: Integration of Real-Time Location Systems for Real-World Hazard Simulations Speiser, Kilian Hong, Kepeng Teizer, Jochen Construction Safety Digital Twins Education and Training Game Engines Internet of Things Learning Environments Mixed and Virtual Reality Real-Time-Location System Real-world Hazards thema EDItEUR::J Society and Social Sciences::JN Education In numerous studies, virtual training for construction safety has been proposed as a promising approach. However, creating realistic training scenarios requires significant resources, encompassing various elements such as sound, graphics, agent behavior, and realistic hazards. Digital Twins have revolutionized this process, and although so far, on a conceptual level only, significantly reducing the associated workload, it is still not exploiting its full potential. In this work, we propose a novel approach that leverages Real-time Location Systems (RTLS) data to simulate the real-world behavior of construction workers and equipment within Virtual Training Environments (VTEs). We aim to create training scenarios with dynamic real-world instead of hardcoded made-up hazardous events. To achieve this, we propose an extension to our Digital Twin for Construction Safety (DTCS) framework that now integrates (a) trajectory data streams of construction personnel and equipment and (b) technical specifications of the construction site work environment, including location and geometry of terrain and surface objects, to simulate real-world hazards in virtual safety training scenarios. Our further contribution is a case study application to explore the DTCS training capacity. Applying a logical filtering algorithm, we can process the RTLS data and ensure that the movements of the workers and equipment within the virtual environment are as realistic and representative as within the real world. This then enables the creation of realistic hazards that trainees can encounter in the training phase. Preliminary results with trainees suggest that the proposed work can have a high potential to enhance the realism of safety training, especially when they need to experience human-machine-related interactions safely. However, further work is required to create more responsive learning environments where the equipment follows real trajectories but also responds intelligently to the trainees' actions. By leveraging real-time data and advanced visualization technologies, we bridge the gap between the physical and virtual realms, enabling trainees to interact and navigate within a realistic virtual environment 2024-04-02T15:47:04Z 2024-04-02T15:47:04Z 2023 chapter ONIX_20240402_9791221502893_86 2704-5846 9791221502893 https://library.oapen.org/handle/20.500.12657/89117 eng Proceedings e report application/pdf n/a 9791221502893_15.pdf https://books.fupress.com/doi/capitoli/979-12-215-0289-3_15 Firenze University Press 10.36253/979-12-215-0289-3.15 10.36253/979-12-215-0289-3.15 bf65d21a-78e5-4ba2-983a-dbfa90962870 9791221502893 137 12 Florence open access
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In numerous studies, virtual training for construction safety has been proposed as a promising approach. However, creating realistic training scenarios requires significant resources, encompassing various elements such as sound, graphics, agent behavior, and realistic hazards. Digital Twins have revolutionized this process, and although so far, on a conceptual level only, significantly reducing the associated workload, it is still not exploiting its full potential. In this work, we propose a novel approach that leverages Real-time Location Systems (RTLS) data to simulate the real-world behavior of construction workers and equipment within Virtual Training Environments (VTEs). We aim to create training scenarios with dynamic real-world instead of hardcoded made-up hazardous events. To achieve this, we propose an extension to our Digital Twin for Construction Safety (DTCS) framework that now integrates (a) trajectory data streams of construction personnel and equipment and (b) technical specifications of the construction site work environment, including location and geometry of terrain and surface objects, to simulate real-world hazards in virtual safety training scenarios. Our further contribution is a case study application to explore the DTCS training capacity. Applying a logical filtering algorithm, we can process the RTLS data and ensure that the movements of the workers and equipment within the virtual environment are as realistic and representative as within the real world. This then enables the creation of realistic hazards that trainees can encounter in the training phase. Preliminary results with trainees suggest that the proposed work can have a high potential to enhance the realism of safety training, especially when they need to experience human-machine-related interactions safely. However, further work is required to create more responsive learning environments where the equipment follows real trajectories but also responds intelligently to the trainees' actions. By leveraging real-time data and advanced visualization technologies, we bridge the gap between the physical and virtual realms, enabling trainees to interact and navigate within a realistic virtual environment
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