• Journal of the Society of Disaster Information
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• v.18 no.2
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• pp.269-279
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• 2022

Purpose: The purpose of this study is to develop a deep learning-based personal protective equipment detection model for disaster prevention at construction sites, and to apply it to actual construction sites and to analyze the results. Method: In the method of conducting this study, the dataset on the real environment was constructed and the developed personal protective equipment(PPE) detection model was applied. The PPE detection model mainly consists of worker detection and PPE classification model.The worker detection model uses a deep learning-based algorithm to build a dataset obtained from the actual field to learn and detect workers, and the PPE classification model applies the PPE detection algorithm learned from the worker detection area extracted from the work detection model. For verification of the proposed model, experimental results were derived from data obtained from three construction sites. Results: The application of the PPE recognition model to construction site brings up the problems related to mis-recognition and non-recognition. Conclusions: The analysis outcomes were produced to apply the object recognition technology to a construction site, and the need for follow-up research was suggested through representative cases of worker recognition and non-recognition, and mis-recognition of personal protective equipment.

• Journal of Environmental Health Sciences
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• v.47 no.1
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• pp.101-109
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• 2021

Objectives: The objectives of this study are to introduce the development process of work situations and types in the revised regulations on wearing personal protective equipment (PPE) for hazardous chemical handlers, analyze the implementation of the regulations, and then provide basic data for future education strategies. Methods: The development process of work situations for regulation was explained through a flowchart by year. In 2018, a survey of 30 chemical managers and 201 managers and handlers was conducted based on recognition of work situations and the related regulations. In 2019, 91 chemical managers and 204 handlers were surveyed to find the degree of compliance with regulations, direction for improvement of understanding the regulations, and training methods. Results: Only 78.0% of chemical managers and 66.7% of handlers said they were aware of the regulations (p<0.05). Just 79.0% of handlers knowing the regulations said they would wear PPE in compliance with these regulations. Therefore, the best way to make workers wear proper PPE in accordance with regulations is to strengthen the promotion of education on regulations. In order to improve the quality of education, 51.7% of managers and 33.3% of handlers cited educational content (video, ppt, etc.) as the top priority. Conclusion: This study suggested that more educational opportunities should be provided and educational content should be developed in order for workers handling hazardous chemicals to wear PPE as prescribed in regulations.

• Journal of the Korean Society of Safety
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• v.35 no.2
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• pp.17-27
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• 2020

To identify the relationship between types of employment(regular and non-regular group) and departments classification (administration, product and research group) and the levels of recognition of chemical substances, a total of 117 workers in cosmetics workplaces. Mainly, regular group and research group showed higher recognition of chemical substances (PPE, ventilation, chemical management, hazards in handling chemicals, skin contact) than non-regular group and administration, product group, but In some cases, production and administrative groups were high. Descriptive statistics(SAS ver9.2)was performed. the results of recognition of chemical substances were analyzed the mean and standard deviation by t-test, and anova, (P=0.05). These results cosmetics manufacturing workplaces have normal level of the perception of chemical substances. In most of the employment types, the regular workers showed high recognition, and the working departments showed high recognition in the research and production groups. Therefore, OEM and ODM cosmetics manufacturers regularly identify characteristics and needs of workplaces and workers, and suggest the development of experience and practiced education programs and risk assessment tools that can raise worker awareness.