• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.4
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• pp.87-90
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• 2008

This research is to study and analyze our country's management of disasters, the present condition of cultural heritages bases on the examples of temples, and Japan's safety management prevention of buddhist temple. As a result, this research aims to how to improve the temple fire prevention system. To improve the anti-fire system of temples, it is important to make new laws about fire lose to minimize cultural property lose. Secondly, to protect self-contained type fire alarm device, with aerosol type hand propelled fire extinguishers to prevent fire lose. Lastly, construction work of electric engineer is necessary to prevent temple fire loses.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.10a
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• pp.314-319
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• 2005

Nowadays, there so many fire accidents happened in subways and tunnels, buildings. In this paper, the behaviors of subway damaged by fire, the fire protection techniques for evaluating subway structures stability are presented. To protect the tunnel by fire, flame detector method is resonable.

• Fire Science and Engineering
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• v.31 no.1
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• pp.50-57
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• 2017

The present article discusses the response characteristics of smoke detector chamber due to dust and wind velocity. Although situations have improved in terms of early sensing of fires as the smoke detectors are applied indoors, studies tend to place insufficient focus on the side effects and malfunction that can be caused by diversified life dust produced indoors and environmental requirements, etc. Therefore, in the present study, 4 types of photoelectric smoke detectors with different forms and structures of smoke chamber were selected as the experimental objects, and dust test was conducted with fly ash, talcum powder and fiber dust as experiment samples to study indoor applicability of the smoke detectors in terms of their response to diversified dust and wind velocity. Also, to observe response characteristics due to pollution level inside the smoke chamber, wind velocity for dust test were set additionally at 0.25 m/s, 0.5 m/s, and 1.0 m/s. Based to the experimental results, fly ash, talcum powder, and fiber dust (black hair powder) were found to be suitable at the dust test reference wind velocity conditions of 0.25 m/s for both operation test and non-operation test after dust application. On the other hand, under the harsh wind velocity conditions of 0.5 m/s and 1.0 m/s, malfunction of unwanted alarm was observed in non-operation tests in the case of fly ash and talcum powder, and non-operation was confirmed to occur in the case of fiber dust as the alarm failed to operate normally in operation tests.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.4
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• pp.343-350
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• 2016

In this paper, We proposed a realtime smoke detection using hidden markov model and DWT. The smoke type is not clear. The color of the smoke, form, spread direction, etc., are characterized by varying the environment. Therefore, smoke detection using specific information has a high error rate detection. Dynamic Object Detection was used a robust foreground extraction method to environmental changes. Smoke recognition is used to integrate the color, shape, DWT energy information of the detected object. The proposed method is a real-time processing by having the average processing speed of 30fps. The average detection time is about 7 seconds, it is possible to detect early rapid.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.7-15
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• 2022

Since the direct and indirect damage caused by the fire in the underground utility tunnel will cause great damage to society as a whole, it is necessary to make efforts to prevent and control it in advance. The most of the fires that occur in cables are caused by short circuits, earth leakage, ignition due to over-current, overheating of conductor connections, and ignition due to sparks caused by breakdown of insulators. In order to find the cause of fire at an early stage due to the characteristics of the underground utility tunnel and to prevent disasters and safety accidents, we are constantly managing it with a detection system using image analysis and making efforts. Among them, a case of developing a fire detection system using CCTV-based deep learning image analysis technology has been reported. However, CCTV needs to be supplemented because there are blind spots. Therefore, we would like to develop a high-performance acoustic-based deep learning model that can prevent fire by detecting the spark sound before spark occurs. In this study, we propose a method that can collect sound in underground utility tunnel environments using microphone sensor through development and experiment of prototype module. After arranging an acoustic sensor in the underground utility tunnel with a lot of condensation, it verifies whether data can be collected in real time without malfunction.

• Current Industrial and Technological Trends in Aerospace
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• v.4 no.1
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• pp.100-107
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• 2006

민간 무인기의 용도는 수색 및 구조, 환경 및 공해감시, 기상 측정, 화재 및 재난의 조기감지, 국경 및 해양정찰, 항공촬영과 지도제작, 농약살포 그리고 교통감시 등 사람이 수행하기 힘든 3D 임무 및 우리의 실생활에 도움을 줄 수 있는 새로운 용도로 개발되고 있다. 그러나 향후 무인항공기의 상업적 성공 여부는 민간 공역으로의 진입 여부에 달려 있으며, 공역 내에서의 자유로운 임무수행을 위해서는 안전성 확보를 위한 감항당국의 인증이 필수요소이다. 이에 항공선진국 들은 민간 무인기의 신뢰성 누적과 인증을 위한 실현 가능한 방법부터 법제도 정비에까지 많은 연구를 수행 중에 있다. 본 글에서는 최근 항공선진국들의 무인항공시스템의 신뢰성 추세와 인증동향 그리고 향후 발전 방향에 대하여 제시한다.

• Proceedings of the Korea Contents Association Conference
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• 2017.05a
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• pp.383-384
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• 2017

재난 재해 조기 예 경보시스템은 산불, 홍수, 지진, 화재, 붕괴, 가스 누출 등 다양한 재난 재해가 발생할 확률이 있거나 발생하였을 경우 다양한 매체를 이용하여 신속하게 이와 관련된 정보를 전파하는 시스템을 의미한다. 재난 재해 조기 예 경보시스템은 기후 변화와 현대 사회의 발전의 고도화로 각종 다양한 재난 재해의 발생이 매년 급증하고 있어 이에 대해 국민의 생명과 재산을 보호하기 위해 필요성이 날로 증가하고 있으며, 이와 관련된 재난통신, 단말기, 시스템의 시장규모는 지속적으로 빠르게 성장하고 있다. 최근 들어 IoT를 이용한 다양한 센서 디바이스를 활용하여 재난 재해 상황, 기상상황, 전염병 상황정보 등을 광범위하게 감지하고 분석함으로써 미래 적용 가능성이 상당히 높게 나타나고 있다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.07a
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• pp.660-661
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• 2020

본 논문에서는 기존 인공 신경망 기반 시계열 학습 기법인 Recurrent Neural Network (RNN)의 많은 연산량 및 고 사양 시스템 요구를 개선하기 위해 랜덤 포레스트 (Random Forest)기반의 새로운 시계열 학습 기법을 제안한다. 기존의 RNN 기반 방법들은 복잡한 연산을 통해 높은 성능을 달성하는 데 집중하고 있다. 이러한 방법들은 학습에 많은 파라미터가 필요할 뿐만 아니라 대규모의 연산을 요구하므로 실시간 시스템에 적용하는데 어려움이 있다. 따라서 본 논문에서는, 효율적이면서 빠르게 동작할 수 있는 시계열 다층 랜덤 포레스트(Time series Multilayered Random Forest)를 제안하고 산불 조기 탐지에 적용해 기존 RNN 계열의 방법들과 성능을 비교하였다. 다양한 산불화재 실험데이터에 알고리즘을 적용해본 결과 GPU 상에서 방대한 연산을 수행하는 RNN 기반 방법들과 비교해 성능적인 한계가 존재했지만 CPU 에서도 빠르게 동작 가능하므로 성능의 개선을 통해 다양한 임베디드 시스템에 적용 가능하다.

• Journal of Korea Multimedia Society
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• v.17 no.3
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• pp.287-293
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• 2014

Early fire detection is very important to avoid loss of lives and material damage. The conventional smoke detector sensors have difficulties in detecting smoke in large outdoor areas. The video-based smoke detection can overcome these drawbacks. This paper proposes a new smoke detection method in video sequences. It uses the ratio of variation rate of subband energy in the wavelet transform domain. In order to reduce the false alarm, candidate smoke blocks are detected by using motion, decrease of chromaticity and the average intensity of block in the YUV color space. Finally, it decides whether the candidate smoke blocks are smokes or not by using their temporal changes of subband energies in the wavelet transform domain. Experimental results show that the proposed method noticeably increases the accuracy of smoke detection and reduces false alarm compared with the conventional smoke detection methods using wavelets.

• Fire Science and Engineering
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• v.32 no.4
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• pp.25-34
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• 2018

This study investigated the development of a fire alarm system with evacuation lighting and voice alarm functions. The performance of a fire detector and system with independently built-in evacuation lighting and voice alarm functions was confirmed for early recognition of fire and to allow visibility of the evacuation route in the event of fire. This new system satisfied model recognition and product testing technological standards with 1.62 lx average illumination, 89.7 dB average sound and 86.1 dB average voice. From additionally testing the evacuation performance of this new system, it was confirmed that the evacuation time decreased by 63.08% to 67.82% under the experimental conditions compared to conventional systems. The new system can minimize fire damage by setting off voice alarms to prevent failure of fire recognition and by flashing emergency lighting to secure the minimum required visibility range for evacuation. Therefore, it is considered that it will be utilized as a fire alarm system with appropriateness and usefulness by considering people with hearing or visual impairment.