• Journal of the Society of Disaster Information
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• v.17 no.3
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• pp.535-542
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• 2021

Purpose: The purpose of this study is to prevent recidivism by recognizing the seriousness of recidivism against sexual offenders under the age of 13 and providing customized social adaptation services based on risk. Method: The study evaluate the efficiency of existing models and proposed model systems, and compare and review what features and operational differences exist from existing models. Result: The proposed model will collect data from related agencies on sexual violence offenders with a high risk of recidivism and classify them into three risk groups through risk algorithms to provide social adaptation services for each risk group. In addition, by monitoring primary social support matching data, storing and re-analyzing the results data to rematch social support services, the model differs from the existing model in preventing recidivism of sexual violence offenders from a long-term perspective. Conclusion: The proposed model of this study is meaningful in that it proposed the basic data of a response system to prevent recidivism from a long-term perspective of sexual offenders with the highest risk of recidivism by collecting and analyzing data on sexual offenders.

• Journal of the Society of Disaster Information
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• v.17 no.2
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• pp.351-364
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• 2021

Purpose: Fire load analysis was conducted to secure basic data for evaluating fire risk of educational facilities. In order to calculate the fire load through a preliminary survey, basic data related to the fire load of school facilities were collected. Method: The basic data were the definition and types of fire loads, combustion heat data for the calculation of fire loads. The fire load was evaluated by multiplying the combustion heat by the weight of the combustibles in the compartment when calculating the fire load. Result: As for the fixed combustible materials of A-elementary school, the floor was mainly made of wood, in consideration of emotion and safety in the classroom, music room, and school office, and the rest of the compartments were made of stone. The ceiling and walls were made of gypsum board and concrete, so they were not combustible. The typical inflammable items in each room were desks, chairs, and lockers in the classroom, and the laboratory equipment box and experimental tool box were the main components in the science room, and books, bookshelves, and reading equipment occupied a large proportion in the library room. Conclusion: 'The fire loads of A-elementary' schools according to the combustibles loaded were in the order of library, computer room, English learning room, teacher's office, general classroom, science hall, and music room.

• Journal of the Society of Disaster Information
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• v.18 no.1
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• pp.146-153
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• 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
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• v.18 no.4
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• pp.922-929
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• 2022

Purpose: The purpose of this paper is to develop a deep learning model to detect fire extinguishers in images taken from CCTVs in underground utility tunnels. Method: Various fire extinguisher images were collected for detection of fire extinguishers in the running-based underground utility tunnel, and a model applying the One-stage Detector method was developed based on the CNN algorithm. Result: The detection rate of fire extinguishers photographed within 10m through CCTV video in the underground common area is over 96%, showing excellent detection rate. However, it was confirmed that the fire extinguisher object detection rate drops sharply at a distance of 10m or more, in a state where it is difficult to see with the naked eye. Conclusion: This paper develops a model for detecting fire extinguisher objects in underground common areas, and the model shows high performance, and it is judged that it can be used for underground common area digital twin model synchronizing.

• Journal of the Society of Disaster Information
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• v.19 no.2
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• pp.334-343
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• 2023

Purpose: In this study, the cavity data found through ground cavity exploration was combined with underground facilities to derive a correlation, and the ground subsidence prediction map was verified based on the AI algorithm. Method: The study was conducted in three stages. The stage of data investigation and big data collection related to risk assessment. Data pre-processing steps for AI analysis. And it is the step of verifying the ground subsidence risk prediction map using the AI algorithm. Result: By analyzing the ground subsidence risk prediction map prepared, it was possible to confirm the distribution of risk grades in three stages of emergency, priority, and general for Busanjin-gu and Saha-gu. In addition, by arranging the predicted ground subsidence risk ratings for each section of the road route, it was confirmed that 3 out of 61 sections in Busanjin-gu and 7 out of 68 sections in Sahagu included roads with emergency ratings. Conclusion: Based on the verified ground subsidence risk prediction map, it is possible to provide citizens with a safe road environment by setting the exploration section according to the risk level and conducting investigation.

• Journal of the Society of Disaster Information
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• v.19 no.4
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• pp.984-992
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• 2023

Purpose: The core problem of this study is that there are no specific noise regulation standards for domestic blasting work. Currently, the domestic blasting work noise regulation standard has not been established separately, and the noise regulation standard of 80 decibels is corrected by 10 decibels to 70 decibels, which is the daily living noise standard. In contrast, many foreign countries have separate noise regulation standards specifically tailored to blasting work. Accordingly, it is intended to present international reasonable blasting noise standards by comparing domestic and foreign blasting work noise regulation standards. Mmethod: This study can be inferred as a comparative analysis of domestic and foreign noise regulation standards. Data on the current noise regulation standards during domestic blasting and noise regulation standards during blasting operations in the United States, the United Kingdom, Australia, Japan, and China are collected and analyzed. Results: According to the study, the noise regulation value during blasting work at domestic construction sites was not separately established, so it was not properly tailored to the specific and characteristics of blasting noise. In the case of overseas, a realistic noise regulation value was established so that a safer, more efficient and eco-friendly blasting method could be applied to the noise regulation value uniformly during blasting work. Conclusion: In this study, it is hoped that noise regulations will be established during reasonable blasting work, as shown in domestic and international comparative studies, and will be widely adopted without interfering with the introduction of efficient, economical, and eco-friendly blasting methods by complying well with blasting safety standards.

• Journal of the Society of Disaster Information
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• v.20 no.1
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• pp.192-198
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• 2024

Purpose: In order to establish a safety management system led by an orderer in the construction industry, the orderer should be positioned at the peak of the construction industry safety management system and a system that can effectively support safety supervisors who can assist the orderer's role should be reflected. Method: This study collected and analyzed data on the status of safety management of construction business owners through prior research on safety management of construction business owners and a survey on the actual condition of those involved in the construction business. Results: The top priority is to improve the safety awareness and safety management capabilities of the orderer, and through these efforts, the orderer-led safety management system will be established when a national consensus on the responsibility of the orderer, such as the Serious Accident Punishment Act and the Occupational Safety and Health Act, is formed in the event of an accident such as a serious accident. Conclusion: In order to establish a safety management system led by an orderer in the construction industry, it contributes to disaster prevention by positioning the orderer at the peak of the construction safety management system and reflecting a system that can effectively support safety supervisors who can assist the orderer's role.

• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1817-1826
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• 2022

After the hydrogen fluoride leak in Gumi in 2012, the government has been systemizing the disaster management system, such as responding to and managing chemical accidents. In particular, the Ministry of the Interior and Safety (MOIS) is in charge of evacuation of residents following chemical accidents based on the Framework Act on Management of Disaster and Safety. In this study, an application plan was presented to support and utilize the decision-making support for evacuation of residents after a chemical accident using the chemical accident investigation equipment of the National Disaster Management Research Institute (NDMI). In the equipment operation system for scientific information collection due to chemical accidents, the roles and purpose of use of long/short distance measurement equipment were presented according to regular and emergency situations. Using the data acquired through long/short distance measurement equipment, it can be used as basic data for resident evacuation decision-making by monitoring whether chemicals are detected in an emergency and managing data on detected substances by company in a regular situation. As a result of measuring chemical substances in order to verify on-site usability by equipment only for the regular operation system, it was confirmed that real-time detection of chemical substances is possible with long distance measuring equipment. In addition, it was confirmed that it was necessary to check the measurable distance and range of the equipment in the future. In the case of short distance measurement equipment, hydrocarbon-based substances were mainly detected, and it was confirmed that it was measured at a higher level in Ulsan-Mipo National Industrial Complex than in Onsan National Industrial Complex. It is expected that it can be used as basic data to support decision-making in the event of chemical accidents through continuous data construction in the future.

• Annual Conference of KIPS
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• 2017.04a
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• pp.661-664
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• 2017

Recently, during disasters occurrence, dealing with emergencies has been handled well by the early transmission of disaster relating notifications on social media networks (e.g., Twitter or Facebook). Intuitively, with their characteristics (e.g., real-time, mobility) and big communities whose users could be regarded as volunteers, social networks are proved to be a crucial role for disasters response. However, the amount of data transmitted during disasters is an obstacle for filtering informative messages; because the messages are diversity, large and very noise. This large volume of data could be seen as Social Big Data (SBD). In this paper, we proposed a big data platform for collecting and analyzing disasters' data from SBD. Firstly, we designed a collecting module; which could rapidly extract disasters' information from the Twitter; by big data frameworks supporting streaming data on distributed system; such as Kafka and Spark. Secondly, we developed an analyzing module which learned from SBD to distinguish the useful information from the irrelevant one. Finally, we also designed a real-time visualization on the web interface for displaying the results of analysis phase. To show the viability of our platform, we conducted experiments of the collecting and analyzing phases in 10 days for both real-time and historical tweets, which were about disasters happened in South Korea. The results prove that our big data platform could be applied to disaster information based systems, by providing a huge relevant data; which can be used for inferring affected regions and victims in disaster situations, from 21.000 collected tweets.

• Journal of Korea Multimedia Society
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• v.16 no.6
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• pp.667-677
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• 2013

With the huge success of Social Network Services, studies on social network analysis to extract the current issues or to track the symptoms of epidemic disease are being carried out actively. On Twitter, tweets reflect people's reaction to an event and users' individual status well, so it is possible to detect an event regarding a tweet as a sensory value. Recently, social signals are used to detect the spread of illness like the flu as well as the occurrence of disaster event like an earthquake in early stages. In this paper, we set up a cold as a target event and regarded tweets as Cold Signals. To evaluate the reliability of Cold Signals, we analyzed correlations between weather factors and the cold index provided by Korea Meteorological Administration.