• 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.

• Economic and Environmental Geology
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• v.55 no.4
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• pp.421-428
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• 2022

This study analyzes emerging earthquake and space use technologies from the latest Korean and Japanese scientific and technological foresights in 2022 and 2019, respectively. Unlike the earthquake prediction and early warning technologies presented in the 2017 study, the emerging earthquake technologies in 2022 in Korea was described as an earthquake/complex disaster information technology and public data platform. Many detailed future technologies were presented in Japan's 2019 survey, which includes largescale earthquake prediction, induced earthquake, national liquefaction risk, wide-scale stress measurement; and monitoring by Internet of Things (IoT) or artificial intelligence (AI) observation & analysis. The latest emerging space use technology in Korea and Japan were presented in more detail as robotic mining technology for water/ice, Helium-3, and rare earth metals, and manned station technology that utilizes local resources on the moon and Mars. The technological realization year forecasting in 2019 was delayed by 4-10 years from the prediction in 2015, which could be greater due to the Corona 19 epidemic, the declaration of carbon neutrality in Korea and Japan in 2020 and the Russo-Ukrainian War in 2022. However, it is required to more active research on earthquake and space technologies linked to information technology.

• Journal of the Society of Disaster Information
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• v.17 no.4
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• pp.794-801
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• 2021

Purpose: The effectiveness of the transport vehicle management system of the Chemical Substances Control Act will be studies and used as basic data for future system improvement plans. Method: After the enforcement of the Chemical Substances Control Act, the effectiveness for the transport vehicle management system was studies by comparing the transport plan, guidance and inspection status, safety training completion management, ect., and the reduction rate of chemical accidents. Results: The average number of chemical accidents in transport vehicles nationwide is 20 each year. And It is decreasing with the stabilization of the Chemical Substances Control Act('15.1.1). The first reason for the decrease in chemical accidents is the increase in submission of transport plans. Second, as the guidance and inspection rate increased every year, the shipper company's management of transport companies was naturally strengthened. Finally, it is judged that chemical accident caused by transport vehicles decrease through safety education. Conclusion: The current tranport vehicle management system of the Chemical Substances Control Act is effective. However, further research is needed to improve the practical and efficient transport vehicle management system.

• 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

• Journal of the Society of Disaster Information
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• v.20 no.1
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• pp.93-105
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• 2024

Purpose: This study aims to quantitatively determine the impact on nearby risidents by selecting the amount of chemicals emitted from the workplace among the substances subject to the chemical emission plan and predicting the concentration with the atmospheric diffusion program. Method: The selection of research materials considered half-life, toxicity, and the presence or absence of available monitoring station data. The areas discharged from the materials to be studied were selected as the areas to be studied, and four areas with floating populations were selected to evaluate health risks. Result: AERMOD was executed after conducting terrain and meteorological processing to obtain predicted concentrations. The health hazard assessment results indicated that only dichloromethane exceeded the threshold for children, while tetrachloroethylene and chloroform appeared at levels that cannot be ignored for both children and adults. Conclusion: Currently, in the domestic context, health hazard assessments are conducted based on the regulations outlined in the "Environmental Health Act" where if the hazard index exceeds a certain threshold, it is considered to pose a health risk. The anticipated expansion of the list of substances subject to the chemical discharge plan to 415 types by 2030 suggests the need for efficient management within workplaces. In instances where the hazard index surpasses the threshold in health hazard assessments, it is judged that effective chemical management can be achieved by prioritizing based on considerations of background concentration and predicted concentration through atmospheric dispersion modeling.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.123-125
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• 2015

Wireless ad hoc network which is comprised of wireless nodes that have the limited communication range is utilized to monitoring disaster area, tracing object, and tactical system. But in the case of wireless node on the ground, a network performance decrease because wireless channel is affected from obstacle or the node deployment is restricted. In this paper, we consider wireless network based on UAV(Unmanned Aerial Vehicle) which has little spatial constraint and quickly deploy a position. We implement test-bed included ground nodes and UAV, and measure throughput and PDR(Packet Delivery Ratio) according to the usage of UAV. We show that network performance is improved by relaying data on UAV.

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.4 s.38
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• pp.79-84
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• 2006

Change detection is a core functions of remote sensing. It can be widely used in public business such as land monitoring, demage assessment from disaster, growth analysis of cities, etc. However, it seems that the change detection using satellite imagery has not been fully used in public business. For the person who are in charge of public business, it would not be easy to implement the change detection because various functions are combined into it. So, to promote the use of the change detection in public business, the standard, the process and the method for the change detection in public business should be established. Also, the software which supports that would be very useful. This study aims to promote the use of satellite imagery in public business by building up the change detection process which are suitable for general public business and developing the change detection software to support the process. The software has been developed using ETRI Components for Satellite Image Processing to support the interoperability.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.405-406
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• 2012

A sensor network is composed of a large number of sensor nodes which have sensing, computation and wireless communication capabilities. The sensor node sends such collected data, usually via radio transmitter, to a command center (sink) either directly or through a data concentration center (a gateway). These sensor networks can be used for various application areas such as health, military, home network, managing inventory, monitoring disaster areas and so on. Moreover, owing to the rapid growth of mobile technology, high-performance smartphones are widespread and in increasing cases are utilized as a terminal device. In this paper, we propose a home management system using smartphone and sensor networks.

• Journal of the Korea Society of Computer and Information
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• v.25 no.6
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• pp.57-64
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• 2020

Video surveillance is consists of cameras, transmission devices, storage and playback devices, and is used for crime prevention and disaster monitoring. Recently, it has been spreading to a wide variety of fields, and has developed into an intelligent video surveillance system that can automatically recognize or track characteristic objects of people and things. The purpose of this study was to investigate the cases of video surveillance service applying the latest technology by dividing it into the home, public, and private sectors. also this study tried to investigate and research what advantage it brings from a business perspective. By looking at the cases introduced in this study, it was confirmed that the viedo security service is developing intelligently, such as excellent compatibility with CCTV, multiple video surveillance, CCTV screen motion detection, and alarm through automatic analysis.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.819-834
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• 2022

Artificial Intelligence (AI) techniques have been effectively used for image classification, object detection, and image segmentation. Along with the recent advancement of computing power, deep learning models can build deeper and thicker networks and achieve better performance by creating more appropriate feature maps based on effective activation functions and optimizer algorithms. This review paper examined technical and academic trends of Convolutional Neural Network (CNN) and Transformer models that are emerging techniques in remote sensing and suggested their utilization strategies and development directions. A timely supply of satellite images and real-time processing for deep learning to cope with disaster monitoring will be required for future work. In addition, a big data platform dedicated to satellite images should be developed and integrated with drone and Closed-circuit Television (CCTV) images.