Impact of environmental pollutants on work performance using virtual reality

被引:0
作者
Hong, Juwon [1 ]
Song, Sangkil [1 ]
Ahn, Chiwan [1 ]
Koo, Choongwan [2 ]
Lee, Dong-Eun [3 ]
Park, Hyo Seon [1 ]
Hong, Taehoon [1 ]
机构
[1] Yonsei Univ, Dept Architecture & Architectural Engn, Seoul, South Korea
[2] Incheon Natl Univ, Div Architecture & Urban Design, Incheon 22012, South Korea
[3] Kyungpook Natl Univ, Sch Architecture Civil Environm & Energy Engn, Daegu, South Korea
基金
新加坡国家研究基金会;
关键词
Environmental pollutant; Work performance; Mental workload; Virtual reality; Construction work; Statistical analysis; CONSTRUCTION; DUST; PRODUCTIVITY; VIBRATION; NOISE; SILICA;
D O I
10.1016/j.autcon.2024.105833
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
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.
引用
收藏
页数:12
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  • [11] The Effects of Bit Wear on Respirable Silica Dust, Noise and Productivity: A Hammer Drill Bench Study
    Carty, Paul
    Cooper, Michael R.
    Barr, Alan
    Neitzel, Richard L.
    Balmes, John
    Rempel, David
    [J]. ANNALS OF WORK EXPOSURES AND HEALTH, 2017, 61 (06) : 700 - 710
  • [12] Assessing Task Mental Workload in Construction Projects: A Novel Electroencephalography Approach
    Chen, Jiayu
    Taylor, John E.
    Comu, Semra
    [J]. JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT, 2017, 143 (08)
  • [13] Revealing the "Invisible Gorilla" in construction: Estimating construction safety through mental workload assessment
    Chen, Jiayu
    Song, Xinyi
    Lin, Zhenghang
    [J]. AUTOMATION IN CONSTRUCTION, 2016, 63 : 173 - 183
  • [14] Estimation of particulate matter exposure to construction workers using low-cost dust sensors
    Cheriyan, Daniel
    Choi, Jae-ho
    [J]. SUSTAINABLE CITIES AND SOCIETY, 2020, 59
  • [15] A review of research on particulate matter pollution in the construction industry
    Cheriyan, Daniel
    Choi, Jae-ho
    [J]. JOURNAL OF CLEANER PRODUCTION, 2020, 254
  • [16] Analysis of the effect of dust barriers on particulate matter dispersion from a construction site using CFD simulation
    Choi, Jinwoo
    Hong, Juwon
    Hong, Taehoon
    [J]. ENVIRONMENTAL POLLUTION, 2023, 338
  • [17] Optimal noise barrier arrangement for heavy equipment during earthwork using spatiotemporal data
    Choi, Jinwoo
    Hong, Juwon
    Hong, Taehoon
    [J]. AUTOMATION IN CONSTRUCTION, 2023, 150
  • [18] An automatic decision model for optimal noise barrier plan in terms of health impact, productivity, and cost aspects
    Choi, Jinwoo
    Hong, Juwon
    Kang, Hyuna
    Hong, Taehoon
    Park, Hyo Seon
    Lee, Dong-Eun
    [J]. BUILDING AND ENVIRONMENT, 2022, 216
  • [19] Balancing assembly line with skilled and unskilled workers
    Corominas, Albert
    Pastor, Rafael
    Plans, Joan
    [J]. OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE, 2008, 36 (06): : 1126 - 1132
  • [20] Assessing mental workload in virtual reality based EOT crane operations: A multi-measure approach
    Das, Souvik
    Maiti, J.
    Krishna, O. B.
    [J]. INTERNATIONAL JOURNAL OF INDUSTRIAL ERGONOMICS, 2020, 80