||SAVES: a safety training augmented virtuality environment for construction hazard recognition and severity identification
||Chen A,Golparvar-Fard M,Kleiner B
||One of the most challenging aspects of health and safety (H&S) management for construction sites is ensuring that workers can predict, identify, and respond to potential hazardous conditions before they are exposed. While OSHA addresses the need for enforcement of comprehensive H&S training programs, many safety training programs still do not include hazard recognition or systematic preparations for the avoidance of unsafe conditions. From a scientific standpoint, we currently lack the knowledge of discovering the most efficient training styles for safety and also understanding why and how these styles of training can influence the post-training activities. To address these needs, an Augmented Virtuality(AV) training environment named System for Augmented Virtuality Environment Safety (SAVES) was designed and is presented in this paper. SAVES which integrates a Building Information Model (BIM) with photographs of typical energy sources on a jobsite, allows trainees to control and navigate an avatar within such AV environment. Within the AV environment, the user can conduct a set of interactions with the environment and accomplish multiple instruction and task-based training scenarios. These scenarios include detection of ten types of hazard and/or energy sources at three levels of severity. The energy sources which in SAVES are embedded in forms of 3D elements and 2D imagery are designed to elevate the safety awareness of the users, enable them to predict and identify various types of hazards, and assess their level of severity. To fully document the experience of the users, during each exercise, trainees’ choices, time for decision-making and corresponding prevention plan are documented in the system. The complete process of design, development, implementation and results analysis of SAVES is presented.
|Year of publication:
||Safety,Training,Virtual Reality,Hazard Recognition
Chen A,Golparvar-Fard M,Kleiner B (2013).
SAVES: a safety training augmented virtuality environment for construction hazard recognition and severity identification. CONVR 2013,