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. 2021 May 23;18(11):5573.
doi: 10.3390/ijerph18115573.

Exploring Fatalities and Injuries in Construction by Considering Thermal Comfort Using Uncertainty and Relative Importance Analysis

Minsu Lee  1 , Jaemin Jeong  1 , Jaewook Jeong  1 , Jaehyun Lee  1
Affiliations

Exploring Fatalities and Injuries in Construction by Considering Thermal Comfort Using Uncertainty and Relative Importance Analysis

Minsu Lee et al. Int J Environ Res Public Health. .

Abstract

Fatal injury and accidents in the construction industry occur under the influence of outdoor weather conditions such as temperature, humidity and wind speed in all four seasons. Previous research in this area has focused on hot and cold weather conditions: hot weather causes heat rash, heat cramps and heat fainting, while cold weather causes fatigue, lumbago, and cold finger sensations. However, other weather conditions are also associated with, and cause, fatal injury and accidents. Accordingly, this study analyzes injury and fatal accidents in the construction industry based on the physiological equivalent temperature (PET) as it pertains to thermal comfort using an uncertainty analysis. Furthermore, using a neural network, relative importance is analyzed considering injury and fatal accidents. This study is conducted in five steps: (i) Establishment of the database, (ii) Classification of accident types and weather conditions, (iii) Calculation of thermal comfort, (iv) Analysis of injury and fatal accidents based on thermal comfort, and (v) Calculation of the relative importance of thermal comfort during injury and fatal accidents. Via the research process, 5317 fatal incidents and 207,802 injuries are analyzed according to 18 accident types in all seasons. It was found that 'falls', were the most frequent fatal incident and injury (2804 fatal incidents and 71,017 injuries), with most of these occurring during the autumn season. The probabilities of injury and fatal accidents in the 'fall' category are 86.01% and 85.60%, respectively, in the outside comfort ranges. The contribution of this study can provide data for a database on safety management considering weather conditions.

Keywords: deep learning; fatal accident; monte carlo simulation; outdoor thermal comfort; physiological equivalent temperature.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Research framework.
Figure 2
Figure 2
Distribution of the physiological equivalent temperature for 10 years.
Figure 3
Figure 3
Distribution of physiological equivalent temperature from 2007 to 2016.
Figure 3
Figure 3
Distribution of physiological equivalent temperature from 2007 to 2016.
Figure 4
Figure 4
Examples of injury and fatal accidents in terms of thermal comfort.
Figure 5
Figure 5
Graph of monthly injury and fatal accidents in terms of accident type.
Figure 5
Figure 5
Graph of monthly injury and fatal accidents in terms of accident type.
Figure 6
Figure 6
Graph of injury and fatal accidents types based on PET ranges.
Figure 6
Figure 6
Graph of injury and fatal accidents types based on PET ranges.
Figure 7
Figure 7
Analysis of the probability distribution of fatal accident using a Monte Carlo simulation.
Figure 7
Figure 7
Analysis of the probability distribution of fatal accident using a Monte Carlo simulation.
Figure 8
Figure 8
Analysis of the probability distribution of injuries using a Monte Carlo simulation.
Figure 8
Figure 8
Analysis of the probability distribution of injuries using a Monte Carlo simulation.
Figure 9
Figure 9
Graph of the neural network of weighting factors.
See this image and copyright information in PMC

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