• Proceedings of the Korea Contents Association Conference
• /
• 2006.05a
• /
• pp.322-326
• /
• 2006

There are the road of the artificial government property and rivers of the natural government property in representative Public Facilities applied National Reimbursement Law. Art.5. Doctrine on Responsibility of Public Facilities. Recently damage of a people has frequently been occurring caused by the flood of rivers and the flood disaster, and a people tends to request national reimbursement regarded it not as a natural disaster but as a man-made disaster. Especially the flood repeatedly occurred by the flood of rivers and destructive of the embankment of rivers, and it is also occurring in repairing rivers. Therefore a nation have to take responsibility of compensation for damage because of defect of conservation of rivers, and pay attention to improving the facilities of conservation and at the same time expand the range of responsibility. Thus the range of this study limits the national reimbursement of conservation of rivers among National Reimbursement Law. Art.5. Compensation for Damages on Defect about an Establishment and Management of public Facilities. Within this range, the objection of this study is to seek controversial issues and solutions, which belong with national reimbursement responsibility about conservation of rivers, as every principle of law and precedent coming under natural government property about compensation for damages caused by defect of conservation of rivers is analyzed and examined.

• Journal of Convergence for Information Technology
• /
• v.10 no.8
• /
• pp.53-59
• /
• 2020

This paper relates to an IoT device system that detects sound source and estimates the sound source location. More specifically, it is a system using a sound source direction detection device that can accurately detect the direction of a sound source by analyzing the difference of arrival time of a sound source signal collected from microphone sensors, and track the generation direction of a sound source using an IoT sensor. As a result of a performance test by generating a sound source, it was confirmed that it operates very accurately within 140dB of the acoustic detection area, within 1 second of response time, and within 1° of directional angle resolution. In the future, based on this design plan, we plan to commercialize it by improving the reliability by reflecting the artificial intelligence algorithm through big data analysis.

• Journal of the Society of Disaster Information
• /
• v.15 no.1
• /
• pp.153-164
• /
• 2019

Purpose: This paper aims to derive improvement measures, in terms of legal and technical aspects, which can reduce effectively the casualties caused by drowing accidents. Method: Firstly, we checked the status of drowing accident management and carried out the interview of field private safety guards. field private safety guards. In addition, surveys were conducted on safety personnel and managers. Based on survey results, we are lastly analyzed the specific problems and reviews the improvement measures from technical and legal aspects. Result: As an analytical result, it was considered that supplementary supporting tools such as CCTV, monitoring devices using IoT and artificial intelligence technologies were necessary to prevent drowning accident, and qualification with limited authority should be added to the private safety guard because of the lack of regulation. Conclusion: In order to manage water safety effectively, a comprehensive water safety management system should be established that integrates people and equipment through systemic education of security personnel, authorization of enforcement, and introduction of surveillance equipment.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.18 no.2
• /
• pp.355-360
• /
• 2023

Fire is a disaster that causes irreversible damage to many people due to personal injury and property damage. Various fire detection equipments are installed around us to detect and cope with it quickly. However, due to various problems such as artificial, environmental, and aging, fire detection equipment is activated even though it is not a actual fire, and there are many problems such as delaying the support to the necessary fire scene. In this paper, we analyze the non-fire alarm of the fire detection equipment and propose a system that enables the field staff to check the scene situation through the video as a way to prevent the mobilization due to the misinformation by checking the fire. The purpose of the present invention is to stably cope with a disaster by suggesting a customized automatic guidance system which induces a rapid evacuation by sending an evacuation guidance notification to a range of a fire occurrence neighboring area, and supports a rapid and accurate processing by a rapid dispatch of a firefighter, rather than a wide range of guidance such as an existing emergency disaster guidance letter when it is determined to be an actual fire through the confirmation procedure.

• Journal of Platform Technology
• /
• v.11 no.6
• /
• pp.79-88
• /
• 2023

Recently, industrial accidents have continued to increase due to the industrialization, and worker safety management is recognized as essential to reduce losses due to hazardous factors at work places. To manage the safety of workers, it is required to apply customized safety management artificial intelligence technology that takes into account the characteristics of industrial sites, and a service for real-time risk detection and response to workers depending on the situation based on safety accident types and risk analysis for each task and process. The proposed safety management service consists of worker devices to acquire sensor data, edge devices to collect from IoT-based sensors, and a voice chatbot to support workers' disaster response. The voice chatbot plays a major role in interacting with workers at disaster sites to respond to risks. This paper focuses on real-time risk response using an IoT-based system and voice chatbot on a server for work safety according to the worker's situation. A Scenario-based voice chatbot is used to process responses at the edge level to provide safety management services.

• Korean Journal of Remote Sensing
• /
• v.37 no.6_3
• /
• pp.1965-1974
• /
• 2021

Satellite remote sensing approach can be actively used for forest monitoring. Especially, it is much meaningful to utilize Korea multi-purpose satellites, an independently operated satellite in Korea, for forest monitoring of Korea, Recently, several studies have been performed to exploit meaningful information from satellite remote sensed data via machine learning approaches. The forest information produced through machine learning approaches can be used to support the efficiency of traditional forest monitoring methods, such as in-situ survey or qualitative analysis of aerial image. The performance of machine learning approaches is greatly depending on the characteristics of study area and data. Thus, it is very important to survey the best model among the various machine learning models. In this study, the performance of deep neural network to classify artificial or natural forests was analyzed in Samcheok, Korea. As a result, the pixel accuracy was about 0.857. F1 scores for natural and artificial forests were about 0.917 and 0.433 respectively. The F1 score of artificial forest was low. However, we can find that the artificial and natural forest classification performance improvement of about 0.06 and 0.10 in F1 scores, compared to the results from single layered sigmoid artificial neural network. Based on these results, it is necessary to find a more appropriate model for the forest type classification by applying additional models based on a convolutional neural network.

• Journal of the Society of Disaster Information
• /
• v.7 no.4
• /
• pp.266-272
• /
• 2011

This study is focused on guard major collegians who are composed of factor in medical emergency system. In the case of cardiac failure, it is to make its basic data develop its education program of CPR which can increase the patient's survival rate before his hospitalization. The subject of study is composed of 120 persons who are 94 boy-collegians(78.3%) and 26 girl-collegians(21.7%) in sex and 66 first-grade collegians(55.0%) and 54 second-grade collegians(45.0%) in a school year. There is significant difference in the practices of artificial respiration and the thorax pressure after the education of basic CPR in sex(p<0.01). The practices of artificial respiration in boy-collegians($93.72{\pm}4.21$) is higher than in girl-collegians($82.31{\pm}6.36$) and the practices of thorax pressure in boy-collegians($92.45{\pm}4.44$) is higher than in girl-collegians($88.08{\pm}6.49$). The satisfaction degree of boy-collegians($4.33{\pm}0.59$) is higher than that of girl-collegians($3.73{\pm}0.67$) after theory & practice education of basic CPR(p<0.01). It is necessary to develop the education program and educate its knowledge & technology in proportion to collegians characteristics of sex and school year. Also, education authorities should develop a subject of the accident provided the practical education of CPR for guard major collegians.

• Journal of the Society of Disaster Information
• /
• v.19 no.1
• /
• pp.44-59
• /
• 2023

Purpose: In the event of mass casualties, triage must be done promptly and accurately so that as many patients as possible can be recovered and returned to the battlefield. However, medical personnel have received many tasks with less manpower, and the battlefield for classifying patients is too complex and uncertain. Therefore, we studied an artificial intelligence model that can assist and replace medical personnel on the battlefield. Method: The triage model is presented using reinforcement learning, a field of artificial intelligence. The learning of the model is conducted to find a policy that allows as many patients as possible to be treated, taking into account the condition of randomly set patients and the medical capability of the military hospital. Result: Whether the reinforcement learning model progressed well was confirmed through statistical graphs such as cumulative reward values. In addition, it was confirmed through the number of survivors whether the triage of the learned model was accurate. As a result of comparing the performance with the rule-based model, the reinforcement learning model was able to rescue 10% more patients than the rule-based model. Conclusion: Through this study, it was found that the triage model using reinforcement learning can be used as an alternative to assisting and replacing triage decision-making of medical personnel in the case of mass casualties.

• Journal of the Society of Disaster Information
• /
• v.18 no.4
• /
• pp.883-890
• /
• 2022

Purpose: Currently, in the case of domestic fire fighting facility design, it is difficult to secure highquality manpower due to low design costs and overheated competition between companies, so there is a limit to improving the fire safety performance of buildings. Accordingly, AI-based firefighting design solutions were studied to solve these problems and secure leading fire engineering technologies. Method: Through AutoCAD, which is widely used in existing fire fighting design, the procedures required for basic design and implementation design were processed, and AI technology was utilized through the YOLO v4 object recognition deep learning model. Result: Through the design process for fire fighting facilities, the facility was determined and the drawing design automation was carried out. In addition, by learning images of doors and pillars, artificial intelligence recognized the part and implemented the function of selecting boundary areas and installing piping and fire fighting facilities. Conclusion: Based on artificial intelligence technology, it was confirmed that human and material resources could be reduced when creating basic and implementation design drawings for building fire protection facilities, and technology was secured in artificial intelligence-based fire fighting design through prior technology development.

• Journal of Korean Society of Forest Science
• /
• v.108 no.2
• /
• pp.208-215
• /
• 2019

The goal of this study was to analyze the reactivity of a volumetric water content sensor (soil moisture sensor) and tensiometer and to review their use in the early detection of a shallow landslide. We attempted to demonstrate shallow and rapid slope collapses using three different soil ratios under artificial rainfall at 120 mm/h. Our results showed that the measured value of the volumetric water-content sensor converged to 30~37%, and that of the tensiometer reached -3~-5 kPa immediately before the collapse of the soil under all three conditions. Based on these results, we discussed a temporal range for early warnings of landslides using measurements of the volumetric water content sensors installed at the bottom of the soil slope, but could not generalize and clarify the exact timing for these early warnings. Further experiments under various conditions are needed to determine how to use both sensors for the early detection of shallow landslides.