• Journal of IKEEE
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• v.23 no.1
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• pp.242-248
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• 2019

Fire flame and smoke detection algorithm studies are challenging task in computer vision due to the variety of shapes, rapid spread and colors. The performance of a typical sensor based fire detection system is largely limited by environmental factors (indoor and fire locations). To solve this problem, a deep learning method is applied. Because it extracts the feature of the object using several methods, so that if a similar shape exists in the frame, it can be detected as false postive. This study proposes a new algorithm to reduce false positives by using frame similarity before using deep learning to decrease the false detection rate. Experimental results show that the fire detection performance is maintained and the false positives are reduced by applying the proposed method. It is confirmed that the proposed method has excellent false detection performance.

• Fire Science and Engineering
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• v.30 no.2
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• pp.19-26
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• 2016

In this study, we conducted a low temperature operating test and miniature tunnel model test to study the fire detection capability and properties of an early fire detection system using an optical sensor linear detector that can be installed in harsh environments such as tunnel or utility-pipe conduits which are becoming the major and national infrastructure facilities. The test showed that the optical sensor linear detector was the only one functioned properly among five thermal detectors installed at a low temperature of $-20^{\circ}C$ for 5 days. To study were analyzed adaptability of optical sensor linear detector in the windy tunnel, the operating properties of the optical sensor linear detector when the wind velocity was varied between 0 m/s and 1 m/s in a miniature tunnel model. The temperature change was high when the wind velocity was 0 m/s.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2013.04a
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• pp.128-129
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• 2013

화재 현장에는 소방대원의 생명에 위협이 될 수 있는 다양한 연소가스가 발생하며, 소방대원의 안전에 다양한 연소가스의 농도를 실시간으로 측정하는 것은 매우 중요하다. 현재 무선통신 기술의 발달과 센서 기술의 발전으로 저전력, 소형의 센서를 이용하여 무선으로 화재현장의 온습도조건, 발생가스의 농도, 소방대원의 생체신호를 화재현장의 지휘센터로 보내주는 기술의 개발이 진행되고 있다. 이러한 추세에 맞추어 측정된 가스의 농도를 실시간으로 지휘센터로 송수신하는 기술의 연구가 활발히 진행 중이다. 본 연구는 화재환경에서 주로 발생되는 CO, NO2, NH3를 위주로한 고온의 환경에서 농도를 측정하기 위한 방법에 대한 연구이다.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.9
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• pp.847-854
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• 2014

The paper presented a method of early fire detection based on the environmental characteristics inside the nacelle of wind turbine generator system(WTGS). The rising rates of the temperature and smoke density were used as the parameters for early fire detection. By considering the characteristics of temperature and smoke density of a nacelle, this method is very reliable and can minimize the possibility of a malfunction of fire detection. The performance of the method was tested through sets of experiments by using nacelle simulator.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2018.11a
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• pp.346-347
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• 2018

This study is a case study on ship zone identification for the generalization of fire safety module in Korean e-Navigation system and assessed the method of dividing the area of the ship based on the location of the fire detector of the target ship.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2015.07a
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• pp.326-327
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• 2015

본 논문에서는 화재의 움직임 정보에 기반하여 역동적인 화재를 감지하는 기법을 제안한다. 우선 감시 카메라와 같은 고정형 감시 장치로부터 얻어진 색 정보를 분리하기 쉬운 좌표계로 변환하고 이전에 수집된 데이터들로부터 얻어진 사전 정보로부터 화염 영역을 추출한다. 또한 화염 영역의 가장자리가 움직임이 매우 크다는 사실에 기반하여 광흐름 벡터로 얻어진 시간적 분산값을 이용한 움직임 모델을 생성한다. 화염 영역은 움직임 모델과 결합되며 오탐을 걸러내기 위해 충분한 양의 화재 영역이 중첩될 때 최종적으로 화재를 판별한다. 본 논문에서 제안한 방법은 실험 결과에서 우수한 탐지 능력을 보인다.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.4
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• pp.41-53
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• 2018

Recently, the development of machine learning technology has led to the application of deep learning technology to existing image based application systems. In this context, some researches have been made to apply CNN (Convolutional Neural Network) to the field of fire detection. To verify the effects of existing preprocessing and feature extraction methods on fire detection when combined with CNN, in this paper, the recognition performance and learning time are evaluated by changing the VGG19 CNN structure while gradually increasing the convolution layer. In general, the accuracy is better when the image is not preprocessed. Also it's shown that the preprocessing method and the feature extraction method have many benefits in terms of learning speed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.6
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• pp.1506-1514
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• 2015

In this paper, we proposed a forest fires prediction and detection system. It could provide a situation of fire prediction and detection methods using context awareness sensor. A fire occurs wide range of sensing a fire in a single camera sensor, it is difficult to detect the occurrence of a fire. In this paper, we propose an algorithm for real-time by using a temperature sensor, humidity, Co2, the flame presence information acquired and comparing the data based on multiple conditions, analyze and determine the weighting according to fire in complex situations. In addition, it is possible to differential management of intensive fire detection and prediction for required dividing the state of fire zone. Therefore we propose an algorithm to determine the prediction and detection from the fire parameters as an temperature, humidity, Co2 and the flame in real-time by using a context awareness sensor and also suggest algorithm that provide the path of fire diffusion and service the secure safety zone prediction.

• Fire Science and Engineering
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• v.11 no.2
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• pp.45-53
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• 1997

In this article, the Fuzzy Logic as the principle of the multcriteria fire detector is used to determine whether the fire takes out or not. The main contents of this method as follow; most of all, the degree of the fire is represented as the type of the Fuzzy, and then it is possible to examine whether the fire takes out or not by the principle of the Fuzzy Logic. The input fators of the Fuzzy fire detector are temperature sensor, smoke sensor, light sensor applied to digital type. On the result of this study, the first, the number of the case of the nonfire alarm which is represented in the existing fire detector is reduced, and the second, the applicability of the fuzzy detector is demonstrated by the test.

• Fire Science and Engineering
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• v.13 no.4
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• pp.13-19
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• 1999

Currently, conventional fire prevention facility installation standard is based on the use and size of the domestic theaters. In the study, theaters with 1,900 seats were examined to suggest a suitable method to adapt a better fire preventing system. The proposed systems are as follow. - 100% of backup pressed-water outlet device, considering waterproof pressure for fire prevention facility at the top floor. - The supplement of the side wall type header and a large caliber outlet header for stage open sprinkler. - Subdividing a installation rule for special detector and implementing the latestdetector. - Installation of fire curtain for dividing stage area and auditorium area, and also the method of installation of fire curtain.