• Disaster and Security
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• v.5 no.1
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• pp.38-46
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• 2015

최근 들어 전국의 곳곳에서 화재가 발생하여 귀중한 인명과 재산을 잃는 대형 참사(慘事)로 이어지고 있다. 화재가 발생했을 때에 초기진화(初期鎭火) 및 인명(人命)의 대피시간(待避時間)인 소위 골든타임은 대략 5분정도이다. 또한 화재사고를 직접체험하게 되면 패닉(panic)현상을 초래하여 우왕좌왕, 혼란의 블랙홀(Black hole)에 함몰(陷沒)되게 마련이다. 의정부 아파트 화재에서처럼 대부분의 골목길은 많은 차량들이 주차되어 소방차 긴급출동에 장애가 되고 있는 실정이다. 보편적으로 화재발생 시 소방대는 5분 내에 출동을 목표로 훈련을 한다. 하지만 화재현장에서 소방대에 화재신고가 신속히 이루지지 못하는 지체시간(遲滯時間)을 감안하면 소방대가 현장에 도착하여 진압작업을 개시하는 시점에는 이미 골든타임을 벗어나 화재가 확산되어 있는 상황인 것이다. 그러므로 골든타임을 감안(勘案)하여 소방대의 출동이전에 자체적으로 초기진압을 할 수 있는 방재시스템을 구축(構築)하여야 하는 것이다. 이에 소방대의 도착이전의 골든타임 이내에 자체적으로 조기진압 및 피난을 할 수 있어야 할 것이며, 다만 출동한 소방대는 인접한 건물이나, 주유소 등으로의 연소 확산(延燒 擴散)을 방지하는 역할로 개념(槪念)을 정리할 필요가 있는 것이다. 소방관련 법령 및 화재안전기준 등은 수시로 개정 발전 되어 오늘날에 이르렀다, 하지만 아직까지도 불합리하고 모순된 규정 등이 곳곳에 산재해 있다. 이에 틀에 박힌 고정관념에서 벗어나 보다 논리적이고 합리적이며 현장여건에 부합하는 선진화된 소방제도를 구축하여 화재참사로부터 국민의 생명과 재산보호는 물론 그 손실을 최소화하기 위한 선진화된 소방관련 제도로 정착시켜야 할 것이다.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.4
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• pp.127-134
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• 2012

This study analyzed the present status of services by fire-suppression mobilization time of fire station where is located in Jinju city, by using network analysis of GIS targeting fire station(five 119 safety centers, one 119 division) in Jinju city area. As a result, it was indicated to be 15.9% in the ratio with less than 5 minutes of mobilization time, 34.7% in the ratio with less than 8 minutes, 94% in the ratio with less than 20 minutes out of the whole fire service area in Jinju city. Even districts with more than 20 minutes were analyzed to reach 6%. Especially, to solve vulnerability to approach the fire service in uptown districts(Jinseong, Jisu, Sabong, Ilbanseong, the whole area of Ibanseong), the 119 division is installed more to be operated. However, accessibility is still remaining in low level. Also, in case of 119 safety center of Cheonjeon, the national industrial complex and the general industrial complex are being formed on a large scale. However, analyzing the fire service level in the corresponding area, the districts with more than 8 minutes and less than 20 minutes were existing broadly. In consequence of analyzing the fire service area in Jinju city with the fire-suppression mobilization time as the above, the fire service level is failing to escape largely from the status prior to the urban-rural consolidation compared to what the jurisdictional area was largely expanded by which the administrative districts were integrated by the urban-rural consolidation in locally small-and medium-sized city. Thus, there is a need of a measure for improving this.

• Fire Science and Engineering
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• v.34 no.1
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• pp.121-126
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• 2020

The aim of this study is to suggest ways to capitalize on the golden period for timely response to fire and emergency victims. To implement a system to effectively capitalize on the golden period, there is a need for policy measures as well as legal and social consensus. Precedent research has relentlessly mentioned the need for and feasibility of the priority traffic system for emergency vehicles. To this end, the present study involved an analysis of pilot cases of the priority traffic signal system for emergency vehicles introduced in a city during 26 days, from April 3 to 28, 2017. Out of 58 cases registered with the local 1-1-9 fire house, the number of cases that took advantage of the priority traffic system stood at 16 in response to fire and 11 to first-aid operations. Owing to the system, on average, the response time reduced by 3 min and 50 s in case of fire and by 3 min and 30 s for first aid. There were four complaints registered owing to traffic congestion, and the number of car accidents declined to one from six over the same period in the previous year. Based on these findings, it is safe to say that the priority traffic signal system would be effective for emergency vehicles to capitalize on the golden period if issues identified during the pilot run are resolved.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.222-224
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• 2022

Korea has more than 2,000 fires and more than 2,000 casualties every year. This study takes measures to facilitate the incorporation of 119 fire trucks by judging vehicles or standing signs using real-time image reading YOLO5 before the fire trucks arrive at the fire site. It is possible to shorten the time to extinguish a fire by photographing a fire site, transmitting the situation of the site, and analyzing the components of smoke to determine the type of fire. As a result, it is expected that it will be able to minimize casualties by keeping the golden time.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.4
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• pp.452-459
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• 2018

Conventional fire fighting robots are controlled by a remote control to monitor the fire scene or to suppress the fire. However, this method has a problem that it takes a long time to prepare robot and input it to fire place in the golden time after the fire, so that it can not sufficiently serve as a fire fighting robot. Using the autonomous driving fire monitoring robot, when a fire signal is generated, in conjunction with a fire receiver a moving robot takes a video of the fire scene and delivers the image to the fire department, so that the fire fighter can decide if it is real fire or not. Thereby it is possible to prevent a sudden spread of an accident by providing a quick judgment opportunity and at the same time suppressing the fire early. In this paper, we propose an architecture of the autonomous mobile fire monitoring robot and the communication protocol required for the robot to work with the fire receiver. A communication protocol is designed to control multiple fire monitoring robots in real time, and a communication with a fire receiver is designed as a hierarchical network to serve as an interface of an Ethernet network using wireless Wi-Fi. The fire monitoring robot and the wireless communication of the fire receiving period are implemented and the effectiveness of the operation is confirmed through the field test.

• Journal of Platform Technology
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• v.9 no.3
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• pp.44-51
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• 2021

In general, golden time refers to the most important time in the initial response to accidents such as saving lives or extinguishing fires. The golden time varies from disaster to disaster, but is aimed at five minutes in terms of fire and first aid. However, for the actual site, the average dispatch time for ambulances is 9 minutes and the average transfer time is 17.6 minutes, which is quite large compared to the golden time. There are various causes for this delay, but the main cause is traffic jams. In order to solve the problem, the government has established emergency car concession obligations and secured golden time to prioritize ambulances in places with the highest accident rate, but it is not a solution in rush hour when traffic is increasing rapidly. Therefore, this paper proposed a deep learning-based emergency vehicle priority signal system using collected sound data by installing sound sensors on traffic lights and conducted an experiment to classify frequency signals that differ depending on the distance of the emergency vehicle.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.556-559
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• 2020

최근 태풍, 지진, 산불, 산사태, 전쟁 등 다양한 재난 상황으로 인한 인명피해와 자금 손실이 꾸준히 발생하고 있고 현재 이를 예방하고 복구하기 위해 많은 인력과 자금이 소요되고 있는 실정이다. 이러한 여러 재난 상황을 미리 감시하고 재난 발생의 빠른 인지 및 대처를 위해 본 논문에서는 인공지능 기반의 재난 드론 시스템을 설계 및 개발하였다. 본 연구에서는 사람이 감시하기 힘든 지역에 여러 대의 재난 드론을 이용하며 딥러닝 기반의 최단 경로 알고리즘을 적용해 각각의 드론이 최적의 경로로 효율적 탐색을 실시한다. 또한 드론의 근본적 문제인 배터리 용량 부족에 대한 문제점을 해결하기 위해 Ant Colony Optimization (ACO) 기술을 이용하여 각 드론의 최적 경로를 결정하게 된다. 제안한 시스템 구현을 위해 여러 재난 상황 중 산불 상황에 적용하였으며 전송된 데이터를 기반으로 산불지도를 만들고, 빔프로젝터를 탑재한 드론이 출동한 소방관에게 산불지도를 시각적으로 보여주었다. 제안한 시스템에서는 여러 대의 드론이 최적 경로 탐색 및 객체인식을 동시에 수행함으로써 빠른 시간 내에 재난 상황을 인지할 수 있다. 본 연구를 바탕으로 재난 드론 인프라를 구축하고 조난자 탐색(바다, 산, 밀림), 드론을 이용한 자체적인 화재진압, 방범 드론 등에 활용할 수 있다.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.4
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• pp.117-122
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• 2021

In recent years, human damage and loss of money due to various disasters such as typhoons, earthquakes, forest fires, landslides, and wars are steadily occurring, and a lot of manpower and funds are required to prevent and recover them. In this paper, we designed and developed a disaster drone system based on artificial intelligence in order to monitor these various disaster situations in advance and to quickly recognize and respond to disaster occurrence. In this study, multiple disaster drones are used in areas where it is difficult for humans to monitor, and each drone performs an efficient search with an optimal path by applying a deep learning-based optimal path algorithm. In addition, in order to solve the problem of insufficient battery capacity, which is a fundamental problem of drones, the optimal route of each drone is determined using Ant Colony Optimization (ACO) technology. In order to implement the proposed system, it was applied to a forest fire situation among various disaster situations, and a forest fire map was created based on the transmitted data, and a forest fire map was visually shown to the fire fighters dispatched by a drone equipped with a beam projector. In the proposed system, multiple drones can detect a disaster situation in a short time by simultaneously performing optimal path search and object recognition. Based on this research, it can be used to build disaster drone infrastructure, search for victims (sea, mountain, jungle), self-extinguishing fire using drones, and security drones.