• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.4C
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• pp.388-396
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• 2009

This paper proposes a new fire-smoke detection method by using extracted features from camera images and pattern recognition technique. First, moving regions are detected by analyzing the frame difference between two consecutive images and generate candidate smoke regions by applying smoke color model. A smoke region generally has a few characteristics such as similar color, simple texture and upward motion. From these characteristics, we extract brightness, wavelet high frequency and motion vector as features. Also probability density functions of three features are generated using training data. Probabilistic models of smoke region are then applied to observation nodes of our proposed Dynamic Bayesian Networks (DBN) for considering time continuity. The proposed algorithm was successfully applied to various fire-smoke tasks not only forest smokes but also real-world smokes and showed better detection performance than previous method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.8
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• pp.1581-1586
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• 2016

In this paper, we propose a central disaster monitoring system of the forest fire. This system provides the safe-zone and detection to reduce the suppression efforts. In existing system, it has a few providing the predicting of wildfire spread model and speed through topography, weather, fuel factor. This paper focus on the forest fire diffusion model and predictions of the path identified to ensure the safe zone. Also we have considering the forest fire of moving direction and speed for fire suppression and monitering. The proposed algorithm could provide the technique to analyze the attribute information that temperature, wind, smoke measured over time. This proposed central observing monitoring system could provide the moving direction of spred out forecast wildfire. This observing and monitering system analyze and simulation for the moving speed and direction forest fire, it could be able to predict and training the forest fire fighters in a given environment.

• The Journal of Korean Association of Computer Education
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• v.13 no.6
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• pp.99-104
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• 2010

USN Fire Prevention System is an intelligent system that detects the fire through the value which has got from a sensor such as temperature, humidity, intensity of illumination, acceleration, carbon dioxide(CO2) and so on. And then send it to the operator also use the algorithmic fire detection to operate fire extinguish system on. It is among U-Disaster Prevention System which has prevented fire lately. Configuration of the packet was designed to make the most of lightweight and fast processing for low power consumption. Recently listed in the encryption algorithm is applied each DES, 3DES, AES and HIGHT. So objective was to faster encryption than encryption of high-performance finally domestic standard encryption algorithm HIGHT were suitable for the fire prevention system needed frequent sensing time.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.521-525
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• 2009

In this paper, we introduce fire detection system and software learning algorithm that recognize fire patterns. Flame patterns means that periodical and consistent pattern about general conception of fire, and to process it with the definition. Learning algorithm for flame pattern recognition that we propose is the method which is faster and more exactly than existing algorithm. Also, we trying to elicit the method through experiment result and by applying it, we show the validity of an early fire warning system.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.2
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• pp.206-211
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• 2011

In this paper, a fire detection algorithm based on video processing is proposed. At the first stage, background image extracted from CCTV video input signal, and then foreground image were separated by differencing CCTV input signal from background image. At the second stage, candidated area were extracted by using color information from foreground image. At the final stage, smoke or flame characteristic area were separated by using Gaussian mixture modeling applied to candidated area, and then fire can be detected. Through real experiments at the inner room, it is shown that the proposed system works well.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.42 no.3
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• pp.19-24
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• 2005

Arc Fault Current is an electric discharge which is occurred in two opposite electrode. In this paper, arc current control algorithm is designed for the interruption of arc fault current which is occurred in the local electric network. This arc is one of the main causes of electric fire. Arc fault in electrical network has the characteristics of low current, high impedance and high frequency. Conventional arc current controller does not have the arc current interrupt function. Hence, Controller of arc current is designed for the interruption of arc fault current which has the modified arc characteristics.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.77-79
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• 2022

A large amount of related images are required to detect images with variable shapes. Therefore, in this paper, fire images among images with variable shapes are multiplied through GAN algorithms, and detection rates when AI learning is performed using this image are compared to analyze whether the multiplied images are suitable for learning data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.427-430
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• 2007

Many victims and property damages are caused in fires every year. In this paper, flame and smoke detection algorithm by using image processing technique is proposed to early alarm fires. The first decision of proposed algorithms is to check candidate of flame region with its unique color distribution distinguished from artificial lights. If it is not a flame region then we can check to candidate of smoke region by measuring difference of brightness and chroma at present frame. If we just check flame and smoke with only simple brightness and hue, we will occasionally get false alarms. Therefore we also use motion information about candidate of flame and smoke regions. Finally, to determine the flame after motion detection, activity information is used. And in order to determine the smoke, edges detection method is adopted. As a result of simulation with real CCTV video signal, it is shown that the proposed algorithm is useful for early fire recognition.

• Korean Journal of Remote Sensing
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• v.35 no.1
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• pp.39-55
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• 2019

In this study, we have proposed an improved method to detect forest fires by correcting the reflected signals of day images using the middle-wavelength infrared (MWIR) channel. The proposed method is allowed to remove the reflected signals only using the image itself without an existing data source such as a land-cover map or atmospheric data. It includes the processing steps for calculating a solar-reflected signal such as 1) a simple correction model of the atmospheric transmittance for the MWIR channel and 2) calculating the image-based reflectance. We tested the performance of the method using the MODIS product. When compared to the conventional MODIS fire detection algorithm (MOD14 collection 6), the total number of detected fires was improved by approximately 17%. Most of all, the detection of fires improved by approximately 30% in the high reflection areas of the images. Moreover, the false alarm caused by artificial objects was clearly reduced and a confidence level analysis of the undetected fires showed that the proposed method had much better performance. The proposed method would be applicable to most satellite sensors with MWIR and thermal infrared channels. Especially for geostationary satellites such as GOES-R, HIMAWARI-8/9 and GeoKompsat-2A, the short acquisition time would greatly improve the performance of the proposed fire detection algorithm because reflected signals in the geostationary satellite images frequently vary according to solar zenith angle.

• 전자공학회논문지 IE
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• v.48 no.3
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• pp.26-32
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• 2011

This paper proposed that the method be searched for optimal route of evacuation by algorithm using potential field in specific situation, fire. When robot met an obstacle to be indicated it to ignition point, the installed sensor could be detected the point in restricted area. In according as the data of a fire detection sensor and a sensor complex in a building, the information was transmitted to server which computed optimal route of evacuation by algorithm using potential field. After that, it was able to blow a siren and mark the safe-path with using wireless device such as smart-phone. It was confirmed that the proposed method in functional test, fire emergency evacuation algorithm using potential field, was advanced in circumstance of simulation.