Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/105254
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Title: Efficiency of VR-based safety training for construction equipment : hazard recognition in heavy machinery operations
Authors: Shringi, A
Arashpour, M
Golafshani, EM
Rajabifard, A
Dwyer, T
Li, H 
Issue Date: Dec-2022
Source: Buildings, Dec. 2022, v. 12, no. 12, 2084
Abstract: Machinery operations on construction sites result in many serious injuries and fatalities. Practical training in a virtual environment is the key to improving the safety performance of machinery operators on construction sites. However, there is limited research focusing on factors responsible for the efficiency of virtual training in increasing hazard identification ability among novice trainees. This study analyzes the efficiency of virtual safety training with head-mounted VR displays against flat screen displays among novice operators. A cohort of tower crane operation trainees was subjected to multiple simulations in a virtual towards this aim. During the simulations, feedback was collected using a joystick to record the accuracy of hazard identification while a post-simulation questionnaire was used to collect responses regarding factors responsible for effective virtual training. Questionnaire responses were analyzed using interval type-2 fuzzy analytical hierarchical process to interpret the effect of display types on training efficiency while joystick response times were statistically analyzed to understand the effect of display types on the accuracy of identification across different types of safety hazards. It was observed that VR headsets increase the efficiency of virtual safety training by providing greater immersion, realism and depth perception while increasing the accuracy of hazard identification for critical hazards such as electric cables.
Keywords: Depth-perception
Emerging mixed reality technologies
Hazard identification
Heavy machinery operations
Safety training
Type-2 fuzzy AHP
Publisher: Molecular Diversity Preservation International (MDPI)
Journal: Buildings 
EISSN: 2075-5309
DOI: 10.3390/buildings12122084
Rights: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
The following publication Shringi A, Arashpour M, Golafshani EM, Rajabifard A, Dwyer T, Li H. Efficiency of VR-Based Safety Training for Construction Equipment: Hazard Recognition in Heavy Machinery Operations. Buildings. 2022; 12(12):2084 is available at https://doi.org/10.3390/buildings12122084.
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