Impact of environmental pollutants on work performance using virtual reality

Juwon Hong, Sangkil Song, Chiwan Ahn, Choongwan Koo, Dong Eun Lee, Hyo Seon Park, Taehoon Hong

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Virtual reality-based experiments were conducted to assess the impacts of environmental pollutants (i.e., noise, vibration, and dust) on work performance. In these experiments, concrete chipping work was performed in eight different exposure environments based on exposure to three environmental pollutants to measure data related to work performance: (i) work performance metrics, including work duration and accuracy; and (ii) mental workload. The relationships between data related to work performance and environmental pollutants were then analyzed using statistical techniques as follows: First, work duration was statistically significantly affected by dust, while work accuracy was significantly affected by vibration. Second, mental workload was statistically significantly affected by all three environmental pollutants, increasing with the number of environmental pollutants the workers exposed to. Third, all data related to work performance were found to be correlated with each other. These findings provide insights into improving work performance by managing environmental pollutants in the construction industry.

Original languageEnglish
Article number105833
JournalAutomation in Construction
Volume168
DOIs
StatePublished - 1 Dec 2024

Keywords

  • Construction work
  • Environmental pollutant
  • Mental workload
  • Statistical analysis
  • Virtual reality
  • Work performance

Cite this