• Journal of the Society of Disaster Information
• /
• v.18 no.1
• /
• pp.10-18
• /
• 2022

Purpose: For smooth performance of flood analysis due to heavy rain disasters at energy storage facilities in the Incheon area, field surveys, observational surveys, and pre-established reports and drawings were analyzed. Through the field survey, the characteristics of pipelines and rivers that have not been identified so far were investigated, and based on this, the input data of the SWMM model selected for inundation analysis was constructed. Method: In order to determine the critical duration through the probability flood analysis according to the calculation of the probability rainfall intensity by recurrence period and duration, it is necessary to calculate the probability rainfall intensity for an arbitrary duration by frequency, so the research results of the Ministry of Land, Transport and Maritime Affairs were utilized. Result: Based on this, the probability of rainfall by frequency and duration was extracted, the critical duration was determined through flood analysis, and the rainfall amount suggested in the disaster prevention performance target was applied to enable site safety review. Conclusion: The critical duration of the base was found to be a relatively short duration of 30 minutes due to the very gentle slope of the watershed. In general, if the critical duration is less than 30 minutes, even if flooding occurs, the scale of inundation is not large.

• Journal of the Society of Disaster Information
• /
• v.18 no.1
• /
• pp.146-153
• /
• 2022

Purpose: In the case of domestic port facilities, port structures that have been in use for a long time have many problems in terms of safety performance and functionality due to the enlargement of ships, increased frequency of use, and the effects of natural disasters due to climate change. A big data analysis method was studied to develop an approximate model that can predict the aging pattern of a port facility based on the maintenance history data of the port facility. Method: In this study, member-level maintenance history data for caisson-type quay walls were collected, defined as big data, and based on the data, a predictive approximation model was derived to estimate the aging pattern and deterioration of the facility at the project level. A state-based aging pattern prediction model generated through Gaussian process (GP) and linear interpolation (SLPT) techniques was proposed, and models suitable for big data utilization were compared and proposed through validation. Result: As a result of examining the suitability of the proposed method, the SLPT method has RMSE of 0.9215 and 0.0648, and the predictive model applied with the SLPT method is considered suitable. Conclusion: Through this study, it is expected that the study of predicting performance degradation of big data-based facilities will become an important system in decision-making regarding maintenance.

• Journal of the Society of Disaster Information
• /
• v.18 no.2
• /
• pp.269-279
• /
• 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 the Society of Disaster Information
• /
• v.17 no.2
• /
• pp.306-318
• /
• 2021

The dispatch law has a negative impact on safety management at construction sites as the command and command relationship to safety assistants of the original contractor are applied to the dispatch law. Purpose: The purpose is to study the importance and impact of safety management according to the dispatch law, and to propose a direction for safety management so that safety assistants can actively and proactively prevent accidents. In this study, we used AHP analysis techniques for experts to achieve the final goal and verified the suitability through logistic regression. Method: AHP analysis technique is used for experts and workers and logistic regression analysis is conducted. Result: The result of analyzing scenario data where the dispatch method can be applied showed the importance in the order of education (SkillUp education), management (work-time management) and direct instructions (feedback instruction). In logistic regression analysis, feedback is the factor that affects direct instruction, and in education management, the ratio of education management is 3.42 times lower than that of other groups when only the team leader of the company gives work instructions. Conclusion: The management of feedback and education is more important than anything else within the range in which the dispatch method is not applied, and the expansion of non-face-to-face online education is judged to avoid the violation of dispatch method because the expansion of non-face-to-face online education due to covid 19 recently has brought more various target for safety education.

• Journal of the Society of Disaster Information
• /
• v.19 no.1
• /
• pp.1-9
• /
• 2023

In order to carry out construction work, it is urgent to introduce a proper wage system so that the cost burden of projects that have been won due to bleeding competition among original government buildings based on low-priced bids can be transferred to subcontractors. Purpose: Construction with illegal multi-level industrial structure needs to improve the wage reduction environment leading to order (100%) → original contractor (80%) → subcontractor (65%) → load contractor (65%) and aims to ensure wages for end workers. Method: Investigate the current status of labor cost appropriate payment plan in the construction industry, and investigate the case of the appropriate wage system (P.W) in the United States. In addition, the effect and direction of the appropriate wage system are presented. Result: Individual minimum wage security was also mentioned in the Constitution, and many researchers suggested that only the introduction of an appropriate wage system could solve the problem of reducing worker labor and ensure quality and safety. Conclusion: The proper wage system in the construction industry will block illegal multi-level and illegal foreign work, improve the labor environment in the construction market, create an influx of young workers, and have a significant impact on the construction industry's competitive structure, safety, and quality.

• Journal of the Society of Disaster Information
• /
• v.19 no.1
• /
• pp.161-172
• /
• 2023

Safety education delivered to construction workers in a lecture manner has limitations in concentration and immersion, so delivery power and interest are low. In order to improve unstable behavior through education and prevent safety accidents, it is necessary to change the paradigm to hands-on education. Purpose: Experiential safety education aims to contribute to preventing accidents for construction workers by quickly recognizing risks, improving emergency response skills, and verifying the effectiveness of pre- and post-learning. Method: Based on a survey of workers who experienced the same work environment as the actual construction site, an opinion survey on the pre- and post-safety experience education and a variable measurement tool were planned, and a research hypothesis was established. Results: The Bayesian theory and MC simulation analysis were used to analyze the structural equation model, and the change in construction worker behavior was confirmed through the intended safety (A), non-experiential education in the sub-area of anxiety (B), average, standard deviation, and minimum and maximum values. Conclusion: The effect of education and industrial accidents are reduced only when construction workers are motivated to participate.

• Journal of the Society of Disaster Information
• /
• v.18 no.4
• /
• pp.817-827
• /
• 2022

The real-name safety management system is to indicate "safety" after inspection by construction personnel before workers use it for the purpose of preventing safety accidents caused by unsafe conditions in temporary facilities and temporary constructions installed at construction sites. Purpose: By implementing the real-name system for safety management at construction sites, the objective is to respond to the "Severe Accident Punishment Act" and to improve the level of safety management at the same time. Method: In this study, a hierarchical analysis model was produced through previous studies of actual conditions such as types of safety incidents and causality at construction sites. The AHP model was used to calculate integrated weights and rankings with a pairwise comparison questionnaire for experts. Conclusion: As a result of the analysis of the upper classes, construction machinery was evaluated the highest, and real-name management system was evaluated the lowest. As a result of the lower-level analysis, it was considered that opening doors for safety facility management, tower cranes for construction equipment, management under the "Occupational Safety and Health Act" under the real-name management system, and CEO duties for safety management organizations were the most important.

• Journal of the Society of Disaster Information
• /
• v.19 no.3
• /
• pp.519-531
• /
• 2023

With the aim of preventing safety accidents at construction sites, the company aims to create safe behaviors intended through variables called smart safety and health activities to help reduce industrial accidents. Purpose: It analyzes how smart safety and health activities affect accidents caused by unsafe behavior and changes in worker behavior, which is the root cause, and verifies the hypothesis that it helps prevent safety accidents and protect workers' lives. Method: Smart safety and health activities were selected as independent variables (X), and intended safety and anxiety, which are workers' behavioral intentions, were set as dependent variables (Y), attitude and subjective norms, and planned behavioral control as parameters (M). Exploratory factor analysis, discriminant validity analysis, and intensive validity analysis of safety and health activities were used to analyze the scale's reliability and validity. To verify the hypothesis of behavior change, the study was verified through Bayesian model analysis and MC simulation's probability density distribution. Result: It was found that workers who experienced smart safety and health activities at construction sites had the highest analysis of reducing unstable behavior and performing intended safety behavior. The research hypothesis that this will affect changes in worker behavior has been proven, the correlation between variables has been verified in the structural equation and path analysis of the research analysis, and it has been confirmed that smart safety and health activities can control and reduce worker instability. Conclusion: Smart safety and health activities are a very important item to prevent accidents and change workers' behavior at construction sites.

• Journal of the Society of Disaster Information
• /
• v.19 no.4
• /
• pp.806-814
• /
• 2023

Purpose: According to the Occupational Safety and Health Act of the Ministry of Employment and Labor, in order to prevent industrial accidents, the right to stop work must be exercised in the event of an imminent danger. This study conducted a fact-finding survey on whether employers fulfilled the right to suspend work in the workplace when an imminent danger, such as a typhoon, was encountered. Method: For two days from August 9 to October, when the impact of Typhoon Khanun No. 6 was significant, it was confirmed by wire whether or not the work suspension was carried out at the workplace, and the subjects of the survey were 1,649 construction sites, 830 manufacturing sites, and 278 other industries, for a total of 2,757 sites. Result: As a result of the fact-finding survey, 56% (1,555 locations) on August 9th and 77% (2,142 locations) on August 10th carried out full or partial work suspension. In particular, on August 10, when the typhoon landed, 40% of all workplaces completely stopped work. Conclusion: Through this study, it was confirmed that the right to suspend work by employers is being used in actual workplaces. In the future, when there is an imminent danger, in addition to the right to suspend work, flexible and telecommuting, working hour adjustments, etc. must be actively used to ensure the safety of workers and protect their lives.

• Journal of the Korean Geotechnical Society
• /
• v.40 no.3
• /
• pp.77-84
• /
• 2024

Aging and damaged underground utilities cause cavity and ground subsidence under roads, which can cause economic losses and risk user safety. This study used infrared cameras to assess the thermal characteristics of such cavities and evaluate their reliability using a CNN algorithm. PVC pipes were embedded at various depths in a test site measuring 400 cm × 50 cm × 40 cm. Concrete blocks were used to simulate road surfaces, and measurements were taken from 4 PM to noon the following day. The initial temperatures measured by the infrared camera were 43.7℃, 43.8℃, and 41.9℃, reflecting atmospheric temperature changes during the measurement period. The RP algorithm generates images in four resolutions, i.e., 10,000 × 10,000, 2,000 × 2,000, 1,000 × 1,000, and 100 × 100 pixels. The accuracy of the CNN model using RP images as input was 99%, 97%, 98%, and 96%, respectively. These results represent a considerable improvement over the 73% accuracy obtained using time-series images, with an improvement greater than 20% when using the RP algorithm-based inputs.