Accidents resulting from poorly planned or setup work environments are a major concern within the construction industry. While traditional education and training of personnel offer well-known approaches for establishing safe work practices, serious games in virtual reality (VR) are increasingly being used as a complementary approach for active learning experiences. By taking full advantage of data collection and the interactions possible in the virtual environment, the education and training of construction personnel improves by using non-biased feedback and immersion.
This research presents a framework for the generation and automated assessment of VR data. The proposed approach is tested and evaluated in a virtual work environment consisting of multiple hazards. VR requires expensive hardware, technical knowledge and user acceptance to run the games effectively. An effort has been made to transfer the advantages VR gives to a physical setup. This is done using a light detection and ranging sensing system, which collects similar data and enables the same learning experiences.
Encouraging results on the participants’ experiences are presented and discussed based on actual needs in the Danish construction industry. An outlook presents future avenues towards enhancing existing learning methods.
The proposed method will help develop active learning environments, which could lead to safer construction work stations in the future, either through VR or physical simulations.
The utilization of run-time data collection and automatic analysis allows for better personalized feedback in the construction safety training. Furthermore, this study investigates the possibility of transferring the benefits of this system to a physical setup that is easier to use on construction sites without investing in a full VR setup.
This is a substantially extended and enhanced version of the paper presented at the 20th International Conference on Construction Applications of Virtual Reality (CONVR 2020). The authors would like to acknowledge the editorial contributions of Professor Nashwan Dawood and Dr Farzad Rahimian of Teesside University in the publication of this paper.
Jacobsen, E.L., Solberg, A., Golovina, O. and Teizer, J. (2022), "Active personalized construction safety training using run-time data collection in physical and virtual reality work environments", Construction Innovation, Vol. 22 No. 3, pp. 531-553. https://doi.org/10.1108/CI-06-2021-0113
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