• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.11
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• pp.7964-7970
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• 2015

In enclosed areas such as railway tunnels, the heat and smoke generated by a fire can pose a tremendous risk to the life of passengers. To prevent or mitigate such scenarios, fire detectors are installed for early fire detection. This numerical study is preformed for establishing the method of detecting performance of fire detectors installed on railway tunnels. Numerical analysis are conducted using the fire dynamics simulator, developed by the NIST. The temperature of the tunnel walls is determined using the assumed exterior structure of the tunnel. In addition, the detection times of detectors installed at different locations in the tunnel are obtained for different sizes of the fire source, and the results are compared and analyzed.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.11
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• pp.607-614
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• 2016

In this paper, we propose an intelligent fire learning and detection system using convolutional neural networks (CNN). Through the convolutional layer of the CNN, various features of flame and smoke images are automatically extracted, and these extracted features are learned to classify them into flame or smoke or no fire. In order to detect fire in the image, candidate fire regions are first extracted from the image and extracted candidate regions are passed through CNN. Experimental results on various image shows that our system has better performances over previous work.

• Journal of the Korean Society of Safety
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• v.37 no.3
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• pp.16-23
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• 2022

This study aims to provide a fundamental material for identifying fire and no-fire signals using the detection signal characteristics of IoT-based fire-detection systems. Unlike analog automatic fire-detection equipment, IoT-based fire-detection systems employ wireless digital communication and are connected to a server. If a detection signal exceeds a threshold value, the measured values are saved to a server within seconds. This study was conducted with the detection data saved from seven fire accidents that took place in traditional markets from 2020 to 2021, in addition to 233 fire alarm data that have been saved in the K institute from 2016 to 2020. The saved values demonstrated variable and continuous VC-Signals. Additionally, we discovered that the detection signals of two fire accidents in the K institution had a VC-Signal. In the 233 fire alarms that took place over the span of 5 years, 31% of smoke alarms and 30% of temperature alarms demonstrated a VC-Signal. Therefore, if we selectively recognize VC-Signals as fire signals, we can reduce about 70% of false alarms.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.628-629
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• 2018

Recently, residential spaces in urban areas have changed into multi - family residential spaces. There is a feature that smoke is charged when a fire occurs here. Also, the evacuation route and the direction of the outflow of smoke are the same, and the possibility of inhaling the smoke of the evacuees is very high. When fighting fire in a narrow residential space such as a dwelling in a downtown area, exploration is the most important. For this purpose, we implement EO / IR sensor which can be mounted on firefighter 's helmet and can be used for fire detection. By using the EO / IR operation test, we can derive the results that can be used for research and development of the fire search sensor.

• Journal of the Korean Society of Tobacco Science
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• v.28 no.2
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• pp.152-157
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• 2006

A new procedure has been developed for the quantitation of aromatic amines in mainstream cigarette smoke. Two solid-phase extraction (SPE) clean up steps, using a different retention mechanisms, are required to process the samples. The first step used a cation-exchange cartridge, followed by a second step that used a cartridge with a hydrophobic retention character. The aromatic amines eluted from the second SPE cartridge are derivatized with pentafluoropropionic anhydride. This new method have advantages over other reported techniques, being sensitive, robust, and easily automated. The detection limits were ranged from 0.12 ng/mL for 1-aminonaphthalene to 0.16 ng/mL for 3-aminobiphenyl and the recoveries were from 97 to 106%. Compared with other reports for analysis of 2R4F reference cigarette, this method shows a close analytical data and good repeatability.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.11
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• pp.2759-2764
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• 2014

Smoke detector is commonly used to reduce fire detection time. However, technical problems regarding its inaccuracy of laser beam-receiving point on the surface of the sensor associated with incoming interference are identified when the laser transmitter and receiver are installed at a distance of about 100m. In this paper, we propose the auto focus alignment algorithm with high precision to adjust tilting angle of lasers caused by environmental interference so that solve existing issues using multi-level worm gear set.

• Journal of the Korea Safety Management & Science
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• v.25 no.4
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• pp.67-72
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• 2023

Human and material damage can be reduced if the risk is evaluated by engineering analysis of fire combustion products, smoke concentration, and smoke movement speed in the event of a fire in apartment houses and officetels. In this study, a lot of research on related safety evaluation in the basement needs to be studied and reflected in design, so experimental research was conducted to analyze the flow of smoke through computer simulation and provide analysis data through evacuation safety evaluation. First of all, the five-story underground parking lot subject to simulation has a large floor area, which is advantageous for improving evacuation safety performance, but it uses temperature detectors to increase detection time and fire spread speed. Second, it was analyzed that the evacuation time at all evacuation ports did not exceed the evacuation time, and as the time from the start of evacuation to the evacuation time was 216.9% compared to the travel time, it was evaluated that the safety performance of the evacuation was secured. Third, the above simulation results are a comprehensive safety evaluation based on the non-operation of fire extinguishing facilities in the fire room to increase safety, which means that smoother evacuation safety performance can be secured by linking fire extinguishing facilities.

• Journal of Korea Multimedia Society
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• v.18 no.3
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• pp.359-367
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• 2015

In this paper, we propose intelligent fire learning and detection system using hybrid visual attention mechanism of human. Proposed fire learning system generates leaned data by learning process of fire and smoke images. The features used as learning feature are selected among many features which are extracted based on bottom-up visual attention mechanism of human, and these features are modified as learned data by calculating average and standard variation of them. Proposed fire detection system uses learned data which is generated in fire learning system and features of input image to detect fire.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.250-251
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• 2013

In this paper, we would like to extract criminals doing this criminal offense to smoke in elevators. Extraction method detect difference value using modified color-$X^2$-test and it was normalized. Next, we find frames that has occurred scene change in successive frames using the four-step algorithm of scene change detection. Finally, we present the method of smoking image retrieval and extraction in stored large amount of video.

• Fire Science and Engineering
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• v.34 no.1
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• pp.37-46
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• 2020

This is a basic research on potential application of fire detection by measuring fire detection tendency of indoor air quality measurement factors. In this study, operation experiment using smoke detector sensitivity tester and paper fire experiment specified in UL 268 standards were conducted to evaluate the fire detection tendency of indoor air quality measurement factors. Based on the cross-substitution of values measured in the paper fire experiment, PM10 (excluding average) and HCHO (excluding average and maximum) for the indoor air quality meter (IAQ); PM1.0, PM2.5, and PM10 for IAQ S2; and CO (excluding the average and maximum) for combustion gas analyzers showed consistent tendency despite changes in the measured values for smoke generation under all experimental conditions. In particular, PM10 and CO are considered the most applicable fire detection factors among the factors measured in the experiment.