• Journal of the Society of Disaster Information
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• v.16 no.4
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• pp.650-657
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• 2020

Purpose: In this study, the effectiveness of pilot project of PLSP (Priority Lane and Signal Preference) system, which was operated in Cheongju City, was analyzed. Method: The priority signal was operated by a police officer switching to a blue signal when approaching a fire truck through CCTV, and the priority lane of emergency vehicles was displayed on the road to enable preferential traffic. VISSIM simulation analysis was performed for the 1.2km section (3.8km) of the pilot project section and vehicle data was analyzed for some of the test operation sections. Result: Simulation analysis shows that the moving speed of the emergency vehicle can be increased by 42 km/h with the introduction of PLSP, which can be increased by approximately twice the speed. Travel time was reduced by about 3 minutes, and considerable improvements of 69% compared to cities that are not operating was analyzed. The pilot operation of Cheongju City showed a time-shortening effect of about two minutes on average, with the average time reaching 4 minutes and 14 seconds in the first period and the average time reaching 5 minutes and 40 seconds in the second period. Conclusion: The system has been shown to be effective in minimizing time-to-site arrival of emergency vehicles.

• Journal of the Society of Disaster Information
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• v.18 no.3
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• pp.520-531
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• 2022

Purpose: Based on the risk evaluation of hydrogen fueling stations, this study aims to find a plan to strengthen management safety by examining profitability and management risk, which are major concerns of employers. Method: The risk evaluation was divided into 'acceptable risk' and 'allowable risk' over time from the stage of installation of hydrogen fueling stations, and compared and analyzed with the results of existing studies. Result: Existing studies have been appropriately applied to the risk assessment performed at the stage of installing hydrogen fueling stations. However, possible risks could be found at the operational stage. In other words, it was derived that an evaluation of management risk was also necessary. And through this, it was confirmed that the safety of hydrogen fueling stations was strengthened. Conclusion: The risk assessment that precedes the stage of installing hydrogen fueling stations is appropriate because significant results have been derived from the 'acceptable risk' assessment. However, the operator needs to evaluate the risks that may occur at the operating stage, that is, the 'allowable risks' and prepare countermeasures. Therefore, it is proposed to add management risk assessment items to build and operate safer hydrogen fueling stations.

• Journal of the Society of Disaster Information
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• v.19 no.3
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• pp.498-509
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• 2023

Purpose: This paper proposes a method detecting the falling of a maintenance worker in the underground utility tunnel, by applying deep learning techniques using CCTV video, and evaluates the applicability of the proposed method to the worker monitoring of the utility tunnel. Method: Each rule was designed to detect the falling of a maintenance worker by using the inference results from pre-trained YOLOv5 and OpenPose models, respectively. The rules were then integrally applied to detect worker falls within the utility tunnel. Result: Although the worker presence and falling were detected by the proposed model, the inference results were dependent on both the distance between the worker and CCTV and the falling direction of the worker. Additionally, the falling detection system using YOLOv5 shows superior performance, due to its lower dependence on distance and fall direction, compared to the OpenPose-based. Consequently, results from the fall detection using the integrated dual deep learning model were dependent on the YOLOv5 detection performance. Conclusion: The proposed hybrid model shows detecting an abnormal worker in the utility tunnel but the improvement of the model was meaningless compared to the single model based YOLOv5 due to severe differences in detection performance between each deep learning model

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.5
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• pp.667-674
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• 2023

In the event of a disaster occurring within a building, the prompt and efficient evacuation and rescue of occupants within the building becomes the foremost priority to minimize casualties. For the purpose of such rescue operations, it is essential to ascertain the distribution of individuals within the building. Nevertheless, there is a primary dependence on accounts provided by pertinent individuals like building proprietors or security staff, alongside fundamental data encompassing floor dimensions and maximum capacity. Consequently, accurate determination of the number of occupants within the building holds paramount significance in reducing uncertainties at the site and facilitating effective rescue activities during the golden hour. This research introduces a methodology employing computer vision algorithms to count the number of occupants within distinct building locations based on images captured by installed multiple CCTV cameras. The counting methodology consists of three stages: (1) establishing virtual Lines of Interest (LOI) for each camera to construct a multi-camera network environment, (2) detecting and tracking people within the monitoring area using deep learning, and (3) aggregating counts across the multi-camera network. The proposed methodology was validated through experiments conducted in a five-story building with the average accurary of 89.9% and the average MAE of 0.178 and RMSE of 0.339, and the advantages of using multiple cameras for occupant counting were explained. This paper showed the potential of the proposed methodology for more effective and timely disaster management through common surveillance systems by providing prompt occupancy information.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.10
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• pp.895-903
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• 2018

The purpose of this study is to conduct a comparative analysis on the mental health and health-related quality of life of the community residents who have been affected by the Sewol ferry disaster and to provide a basis for future aids for potential human-caused catastrophe. The study utilized the big data, Korean community health survey data of 3,632 (1,803 in 2018 and 1,829 in 2014) residents in Ansan and Jindo, a victimized community of Sewol ferry disaster, and compared the subjective level of health, amount of appropriate sleep, subjective stress level, stress consulting, depression, depression consulting, and health-related quality of life before and after the disaster. According to the findings, community residents who have been affected by the Sewol ferry disaster did not show any significant difference in terms of subjective health level, amount of appropriate sleep, subjective stress, and health-related quality of life. The study aims to serve as a foundational data for developing a prevention program or policy that aims to support future potential disasters by comparing the mental health and health-related quality of life of the victimized community before and after the disaster. The study suggests that the need for continuous monitoring of mental health and health-related quality of life of the victimized residents is significant, and further studies should be implemented in order to provide better supports for the local community.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.181-193
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• 2024

The increasing atmospheric imbalance caused by climate change leads to an elevation in precipitation, resulting in a heightened frequency of flooding. Consequently, there is a growing need for technology to detect and monitor these occurrences, especially as the frequency of flooding events rises. To minimize flood damage, continuous monitoring is essential, and flood areas can be detected by the Synthetic Aperture Radar (SAR) imagery, which is not affected by climate conditions. The observed data undergoes a preprocessing step, utilizing a median filter to reduce noise. Classification techniques were employed to classify water bodies and non-water bodies, with the aim of evaluating the effectiveness of each method in flood detection. In this study, the Otsu method and Support Vector Machine (SVM) technique were utilized for the classification of water bodies and non-water bodies. The overall performance of the models was assessed using a Confusion Matrix. The suitability of flood detection was evaluated by comparing the Otsu method, an optimal threshold-based classifier, with SVM, a machine learning technique that minimizes misclassifications through training. The Otsu method demonstrated suitability in delineating boundaries between water and non-water bodies but exhibited a higher rate of misclassifications due to the influence of mixed substances. Conversely, the use of SVM resulted in a lower false positive rate and proved less sensitive to mixed substances. Consequently, SVM exhibited higher accuracy under conditions excluding flooding. While the Otsu method showed slightly higher accuracy in flood conditions compared to SVM, the difference in accuracy was less than 5% (Otsu: 0.93, SVM: 0.90). However, in pre-flooding and post-flooding conditions, the accuracy difference was more than 15%, indicating that SVM is more suitable for water body and flood detection (Otsu: 0.77, SVM: 0.92). Based on the findings of this study, it is anticipated that more accurate detection of water bodies and floods could contribute to minimizing flood-related damages and losses.

• Korean Journal of Remote Sensing
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• v.37 no.5_2
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• pp.1235-1243
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• 2021

Geostationary Ocean Color Imager 2 (GOCI-II) on Geo-KOMPSAT-2 (GK2B)satellite was developed as a mission successor of GOCI on COMS which had been operated for around 10 years since launch in 2010 to observe and monitor ocean color around Korean peninsula. GOCI-II on GK2B was successfully launched in February of 2020 to continue for detection, monitoring, quantification, and prediction of short/long term changes of coastal ocean environment for marine science research and application purpose. GOCI-II had already finished IAC and IOT including early in-orbit calibration and had been handed over to NOSC (National Ocean Satellite Center) in KHOA (Korea Hydrographic and Oceanographic Agency). Radiometric calibration was periodically conducted using on-board solar calibration system in GOCI-II. The final calibrated gain and offset were applied and validated during IOT. And three video parameter sets for one day and 12 video parameter sets for a year was selected and transferred to NOSC for normal operation. Star measurement-based INR (Image Navigation and Registration) navigation filtering and landmark measurement-based image geometric correction were applied to meet the all INR requirements. The GOCI2 INR software was validated through INR IOT. In this paper, status and results of IOT, radiometric calibration and INR of GOCI-II are analysed and described.

• Journal of Korea Water Resources Association
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• v.54 no.7
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• pp.535-544
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• 2021

Agricultural water occupies 48% of water demand, and management of agricultural reservoirs is essential for water resources management within agricultural basins. For more efficient use of agricultural water, monitoring the distribution of water resources in agricultural reservoirs and agricultural basins is required. Therefore, in this study, three threshold determination methods (i.e., fixed threshold, Otsu threshold, Kittler-Illingworth (KI) threshold) were compared to detect terrestrial water bodies using Sentinel-1 images for 3 years from 2018 to 2020. The purpose of this study was to evaluate methods for determining threshold values to more accurately estimate the reservoir area. In addition, by analyzing the relationship between the water surface and water storage at the Edong, Gosam, and Giheung reservoirs, water storage based on the SAR image was estimated and validated with observations. The thresholding method for detecting a waterbody was found to be the most accurate in the case of the KI threshold, and the water storage estimated by the KI threshold indicated a very high agreement (r = 0.9235, KGE' = 0.8691). Although the seasonal error characteristics were not observed, the problem of underestimation at high water levels may occur; the relationship between the water surface and the water storage could change rapidly. Therefore, it is necessary to understand the relationship between the water surface area and water storage through ground observation data for a more accurate estimation of water storage. If the use of SAR data through water resources satellites becomes possible in the future, based on the results of this study, it is judged that it will be beneficial for monitoring water storage and managing drought.

• The Journal of Engineering Geology
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• v.30 no.4
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• pp.469-483
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• 2020

The results of long-term groundwater level and quality monitoring can be used not only as the basic data for evaluating the impact of various disasters including climate change and establishing responses, but also as key data for predicting and managing geological disasters such as earthquakes. Some countries use groundwater level and quality monitoring for researches to predict earthquakes and to assess the impacts of the earthquake disaster. However, a few cases in Korea report on individual groundwater quality factors (i.e., dissolved ions) observed before and after the earthquakes, being different from other countries. To establish the abnormality criteria for groundwater quality in Pohang, groundwater samples were collected and analyzed five times from 14 agricultural or private wells existing in Shingwang-myeon and Heunghae-eup. As a result of the analysis, it was found that Ca2+ was the dominant cation in Shingwang-myeon, while Na+ was the dominant cation in Heunghae-eup. The elevated NO3- concentration in Shingwang-myeon is contributed to the agricultural activity in the area. A high concentration of Fe was detected in a well on Heunghae-eup; the concentration exceeded the drinking water standard by nearly 100 times. Relatively higher dissolved ions were observed in the groundwater of Heunghae-eup, and it is considered as the result of the flow velocity difference and water-rock reaction accompanying the difference in bedrock and sediment characteristics. The groundwater of Shingwang-myeon appeared to be most affected by the weathering of granite and silicates, while that of Heunghae-eup was mainly affected by the weathering of silicates and carbonate. The background concentrations (baselines) of groundwater Shingwang-myeon and Heunghae-eup was identified through the survey; however, the continuous monitoring is required to monitor the possible changes and the repeatability of seasonal variation.

• Journal of Korean Society of Disaster and Security
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• v.6 no.3
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• pp.43-48
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• 2013

This paper focused on the continuing the citizen safety, the contributing the local economy's activation, and the improving the safe and the social walfare on the civil environment. Seoul metropolitan nominated the model village the Buggaja 2 dong of the Seodaemoon-gu for the making safe village in the 2013. It is designed the village map for the safe life, discovered the dangerous factor about the various and social facilities which is a road, a walking way, a school, a enjoy place for the children, a Thema place, the leasure place, facilities etc., and improved the model village for the incident's and accident's reduction education and training from 2011 to 2013. The results on the discovering and improving activities by the resilient safe monitoring activity, in the 2011 the village is reduced the 23 people from the 151 people to the 128 people in the dead number into the total citizen 34,000 during a year, is showed the excellent values, which the dead people reduced the 23 people in the village, which the safe-life result was over the 12.8% in the national average. For the making resilient city, for the supporting the visitors which it looks around the safe-life model village, the tracking road map is designed, and the tenth safe life factors is showed.