• Journal of the Society of Disaster Information
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• v.19 no.1
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• pp.69-75
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• 2023

Purpose: The risk of disaster from extreme weather events is increasing due to the increase in occurrence and the strength of heavy rains and storms from continued climate change. To reduce these risks, emergency weather information customized for the characteristics of the information users and related circumstances should be provided. Method: A first-stage emergency weather information delivery system has been developed to provide weather information to the disaster-risk area residents and the disaster response personnel. Novel methods to apply artificial intelligence to identify emergencies have been studied. The relationship between special weather reports from meteorological administration and disaster-related news articles has been analyzed to identify the significance of a pilot study using text analytic artificial intelligence. Result: The basis to identify the significance of the relations between disaster-related articles and special weather reports has been established and the possibility of the development of a real-world applicable system based on a broader analysis of data has been suggested. Conclusion: Through direct alert delivery of weather emergency alerts, a weather emergency alert system is expected to reduce the risk of damage from extreme weather situations.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2022.10a
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• pp.57-58
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• 2022

지속되는 기후변화에 의한 풍수해의 발생 빈도와 강도가 증가함에 따라 풍수해 등 극한 기상현상이 지역 및 상황에 따라 재난으로 이어지는 위험성이 높아지고 있어 기상정보 사용자 및 환경에 따라 서로 다른 기상정보의 중요성과 필요성이 급증하고 있다. 이와 같은 수요를 맞추고자 기상 재난에 의한 피해 위험 지역 거주 주민과 재난 현장에서 재난에 대응하는 방재 관계기관 등 특정 사용자의 요구와 필요에 특화된 맞춤형 기상긴급정보를 다양한 매체의 특성에 맞게 즉각적으로 생성하여 전달하기 위한 기상긴급정보전달시스템이 개발되고 있으며 인공지능을 활용한 긴급성의 식별과 정보 생성 방안이 연구되고 있다.

• Journal of Sensor Science and Technology
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• v.32 no.3
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• pp.164-168
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• 2023

Accurate and reliable weather forecasts for temperature, relative humidity, and precipitation using advanced transformer models and IoT are essential in various fields related to global climate change. We propose a novel weather prediction device that integrates state-of-the-art transformer models and IoT techniques to improve prediction accuracy and real-time processing. The proposed system demonstrated high reliability and performance, offering valuable insights for industries and sectors that rely on accurate weather information, including agriculture, transportation, and emergency response planning. The integration of transformer models with the IoT signifies a substantial advancement in weather and climate modeling.

• Journal of Preventive Medicine and Public Health
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• v.52 no.2
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• pp.82-91
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• 2019

Objectives: Many studies have explored the relationship between short-term weather and its health effects (including pneumonia) based on mortality, although both morbidity and mortality pose a substantial burden. In this study, the authors aimed to describe the influence of meteorological factors on the number of emergency room (ER) visits due to pneumonia in Seoul, Korea. Methods: Daily records of ER visits for pneumonia over a 6-year period (2009-2014) were collected from the National Emergency Department Information System. Corresponding meteorological data were obtained from the National Climate Data Service System. A generalized additive model was used to analyze the effects. The percent change in the relative risk of certain meteorological variables, including pneumonia temperature (defined as the change in average temperature from one day to the next), were estimated for specific age groups. Results: A total of 217 776 ER visits for pneumonia were identified. The additional risk associated with a $1^{\circ}C$ increase in pneumonia temperature above the threshold of $6^{\circ}C$ was 1.89 (95% confidence interval [CI], 1.37 to 2.61). Average temperature and diurnal temperature range, representing within-day temperature variance, showed protective effects of 0.07 (95% CI, 0.92 to 0.93) and 0.04 (95% CI, 0.94 to 0.98), respectively. However, in the elderly (65+ years), the effect of pneumonia temperature was inconclusive, and the directionality of the effects of average temperature and diurnal temperature range differed. Conclusions: The term 'pneumonia temperature' is valid. Pneumonia temperature was associated with an increased risk of ER visits for pneumonia, while warm average temperatures and large diurnal temperature ranges showed protective effects.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2011.06a
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• pp.285-285
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• 2011

This project can know realtime localization, sea weather and so on. also send information and message for work efficiency. in the case of an emergency like fall into the water or absent without leave, let the other sailer positions will allow for a quick response. so this system can be great help to emergency responders will be able to play a major role.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.11
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• pp.7329-7334
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• 2015

This is to analyze of driver behavioral and the accident characteristics in rollover. The study period was January 2011 to May 2014 and the subject of study was 102 person who were drivers visited the emergency room. Research tool includes a damage information of the vehicle, accident mechanism, damage to the patient clinical information with the injury data from the ROAD Traffic Authority. For data analysis, SPSS 18.0 was used for t-test, ANOVA and Chi-square test. Injury Severity Score average score according to the vehicle type is 6.00 points in the smaller vehicle, at high vehicle 11.78 points, from the other vehicle that showed 14.70 points. Significant differences between the three groups did not show (P=.267). Men did not use a seat belt significantly compared to women(P=.007). Vehicle type and weather, this was no correlation with whether or not use the seat belt(P=.755, P=.793). But showed a tendency to smaller size vehicles drivers do not use a seat belt, the weather could see a little more inclined to use a seat belt rather than a sunny day. Finally, in rollover accidents as in other types of accident it was confirmed that the seat belt has a great influence on the damage.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.136-136
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• 2021

In this study, a deep convolutional neural network (DCNN) model is proposed for short-term precipitation forecasting using weather radar-based images. The DCNN model is a combination of convolutional neural networks, autoencoder neural networks, and U-net architecture. The weather radar-based image data used here are retrieved from competition for rainfall forecasting in Korea (AI Contest for Rainfall Prediction of Hydroelectric Dam Using Public Data), organized by Dacon under the sponsorship of the Korean Water Resources Association in October 2020. This data is collected from rainy events during the rainy season (April - October) from 2010 to 2017. These images have undergone a preprocessing step to convert from weather radar data to grayscale image data before they are exploited for the competition. Accordingly, each of these gray images covers a spatial dimension of 120×120 pixels and has a corresponding temporal resolution of 10 minutes. Here, each pixel corresponds to a grid of size 4km×4km. The DCNN model is designed in this study to provide 10-minute predictive images in advance. Then, precipitation information can be obtained from these forecast images through empirical conversion formulas. Model performance is assessed by comparing the Score index, which is defined based on the ratio of MAE (mean absolute error) to CSI (critical success index) values. The competition results have demonstrated the impressive performance of the DCNN model, where the Score value is 0.530 compared to the best value from the competition of 0.500, ranking 16^th out of 463 participating teams. This study's findings exhibit the potential of applying the DCNN model to short-term rainfall prediction using weather radar-based images. As a result, this model can be applied to other areas with different spatiotemporal resolutions.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.22 no.3
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• pp.1-7
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• 2014

The base of leisure air activities are consistently expanding and its demand is expected to increase attributed to GDP growth and people's interest in its activity. Utilizing Visual Flight Rule, light sport aircrafts and ultra-light aircrafts are not under the effect of air traffic control center, which resulted in passenger injury due to emergency landing for adverse weather conditions and technical issues after pulling into mountain area, ocean and even urban area. Such events encouraged safety consciousness toward leisure aircraft activities and developing a measure to prevent a recurrence of the accident. This research focuses on suggesting compositive system for preventive safety management system by providing user based Flight information service and operating effective system, necessary for leisure aircraft activities.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2023.11a
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• pp.75-76
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• 2023

연구목적:기존의 예·경보 발령 체계와는 별도로 지역 특성 및 상황에 따라 기상 관련 긴급정보를 적시에 발령하여 사용자가 신속히 대응할 수 있는 정보를 신속하게 제공할 필요가 있다. 연구방법: 업무의 신속한 적용과 효율성을 위하여 기상청 기운용 중인 선진예보시스템과 종합통보시스템, 그리고 방재기상 포탈 시스템과 연동하여 발생하는 다양한 기상정보와 이로부터 발생된 기상특보문(10종), CBS발송문 등을 연동하고, 위험 기상현상에 관한 기상 긴급 판단 기준을 결정한다. 연구결과:긴급기상정보의 발령 주무부처인 기상청이 운용하는 선진예보시스템과 연동하여 기상긴급정보 전달시스템이 개발되었고 기상긴급정보 자동 생성을 위한 판단 모듈과 메시지 자동생성 기능이 구현됨. 결론:현재 기운용중인 시스템과 효율적으로 연동하여 기상긴급정보의 판단 기준을 제공하고 이를 효율적으로 자동 생성하여 기존의 중계망을 통하여 신속한 제공이 가능하게 되어 긴급한 기상 상황에 의한 재난 피해를 대폭 줄 일 수 있을 것으로 기대된다.

• Journal of the Society of Disaster Information
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• v.16 no.2
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• pp.223-236
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• 2020

Purpose: In this study, a strong wind damage prediction function was developed in order to be used as a contingency during disaster management (preventive-preventive-response-recovery). Method: The predicted strong wind damage function proposed in this study took into account the re-enactment boy power, weather data and local characteristics at the time of damage. The meteorological data utilized the wind speed, temperature, and damage history observed by the Korea Meteorological Administration, the disaster year, and the recovery costs, population, vinyl house area, and farm water contained in the disaster report as factors to reflect the regional characteristics. Result: The function developed in this study reflected the predicted weather factors and local characteristics based on the history of strong wind damage in the past, and the extent of damage can be predicted in a short time. Conclusion: Strong wind damage prediction functions developed in this study are believed to be available for effective disaster management, such as decision making by policy-makers, deployment of emergency personnel and disaster prevention resources.