• Journal of Sensor Science and Technology
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• v.23 no.5
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• pp.342-348
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• 2014

This paper introduced a novel multi-gas sensor detector with simple signal processing algorithm. This device was evaluated by investigating the characteristics of combustible materials using fire-generated smell and smoke. Plural sensors including TGS821, TGS2442, and TGS260X were equipped to detect carbon monoxide, hydrogen gas, and gaseous air contaminants which exist in cigarette smoke, respectively. Signal processing algorithm based on the difference of response times in fire-generated gases was implemented with early and accurately fire detection from multiple gas sensing signals. All fire experiments were performed in a virtual fire chamber. The cigarette, cotton fiber, hair, polyester fiber, nylon fiber, paper, and bread were used as a combustible material. This analyzing software and sensor controlling algorithm were embedded into 8-bit micro-controller. Also the detected multiple gas sensor signals were simultaneously transferred to the personnel computer. The results showed that the air pollution detecting sensor could be used as an efficient sensor for a fire detector which showed high sensitivity in volatile organic compounds. The proposed detecting algorithm may give more information to us compared to the conventional method for determining a threshold value. A fire detecting device with a multi-sensor is likely to be a practical and commercial technology, which can be used for domestic and office environment as well as has a comparatively low cost and high efficiency compared to the conventional device.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.305-306
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• 2006

To avoid the large scale of damage when fire occurs in the tunnel, it is necessary to have a system to minimize the damage, and early discovery of the problem. In this paper, we have proposed algorithm using the image processing, which is the high-speed detection for the occurrence of fire or smoke in the tunnel. The fire detection is different to the forest fire detection as there are elements such as car and tunnel lightings and other variety of elements different from the forest environment. Therefore, an indigenous algorithm should be developed.The two algorithms proposed in this paper, are able to complement with each other and also they can detect the exact position, at the earlier stay of detection. In addition, by comparing properties of each algorithm throughout this experiment, we have proved the propriety of algorithm.

• Proceedings of the Korea Multimedia Society Conference
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• 2012.05a
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• pp.284-286
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• 2012

There has been increasing attention about the prevention and counter-measure of disasters. Particularly, for the case of fire disaster, early detection reduces the damage caused by fire significantly and effective detection method is important. Since most existing detectors need to be located at a close distance to fire, analyzing camera images to find fire becomes active research topic. In this paper, we analyze the color characteristics of fire images in various color spaces and report the experimental detection results. The best result is 77.8% success rate in YIQ space.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.2
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• pp.331-336
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• 2017

The need for early fire detection technology is increasing in order to prevent fire disasters. Sensor device detection for heat, smoke and fire is widely used to detect flame and smoke, but this system is limited by the factors of the sensor environment. To solve these problems, many image-based fire detection systems are being developed. In this paper, we implemented a system to detect fire and smoke from camera input images using a convolution neural network. Through the implemented system using the convolution neural network, a feature map is generated for the smoke image and the fire image, and learning for classifying the smoke and fire is performed on the generated feature map. Experimental results on various images show excellent effects for classifying smoke and fire.

• Fire Science and Engineering
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• v.27 no.5
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• pp.15-18
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• 2013

This paper is concerned with the Performance and Reliability Certification for fire detection system in outdoor area such small and middle sized cultural assets, natural monument and outdoor facilities. Especially, if a fire were to occur in vulnerable area, it is difficulty to detect a fire. therefore we propose a high efficiency and low cost unmanned fire detection system in capable of an early detection regardless spontaneously fire or firebug. for Adoption of Intelligent Fire Detection System with movable and unmanned function breaking from the existing Conventional Fire Detection System, this Range of R&D includes the Performance test, Function test, Field test, Flame Detection test and EMI/EMS Compliance test. the Result data of Performance test, Function test and Field test is generally good during 3 months. also we checked that thermal variation test and EMI/EMS compliance test are good result data within allowable range. As a result of general test, we verified improvement results that the measure distance of fire detection extend 75 m, the Power of waiting time increase 4 hours, the Power of operation time increase 3 days and the context awareness with video as well as sensors.

• Journal of Sensor Science and Technology
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• v.32 no.3
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• pp.187-193
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• 2023

Previous research has explored early expression of fire signs before the burning of insulation. To achieve this, typically, automatic inspections are used to detect gas emitted from odor capsules at electrical connection points; additionally, early fire signs can be expressed using visual inspection of changes in the appearance of temperature caps. However, early detection of electrical fire is often difficult because only specific inspections, which are not complex, are performed. Therefore, in this paper, we present complex inspection techniques, such as visual inspection, odor inspection, and automatic inspection, and propose a showing material of fire signs that can solve conventional problems. In addition, this study examines the conditions under which the candidate material for the showing material is designed, the composition of the candidate material selected based on the designed conditions, the manufacturing means used to produce the showing material considering the temperature for early expression of fire signs, and the performance of the produced showing material. Furthermore, we analyze various effects that can occur through the proposed display material.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.411-414
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• 2009

Many victims and property damages are caused in fires every year. In this paper, intelligent fire-detection systems with embedded fire-detection algorithms for early fire detection and alarm is proposed to reduce fire damages by using image processing technique, high speed digital signal processor(DSP) technique, and information technique. The fire detection algorithms used for the proposed systems consist of flame and smoke detection algorithms. If flame or smoke is detected respectively, the corresponding alarm signal can be transferred to management computer. And if flame and smoke is detected simultaneously, the fire alarm signal shall be generated. Through several experiments in the physical environment, it is shown that the proposed system works well without malfunction.

• Information Systems Review
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• v.12 no.2
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• pp.89-104
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• 2010

Recently, ubiquitous sensor network (USN) has been applied to many areas including environment monitoring. A few studies applied the USN to disaster prevention and emergency management, in particular, aiming to conserve cultural heritage. USN is an useful technology to do online real-time monitoring for the purpose of early detection of the fire which is a critical cause of damage and destruction of cultural heritages. It is necessary to online monitor the cultural heritages that human has a difficulty to access or their external appearance and beauty are important, by using the USN. However, there exists false warning from USN-based monitoring systems without human intervention. In this paper, we presented an alternative to resolve the problem by applying ontology. Our intelligent fire early detection systems for conserving cultural heritages are based on ontology and inference rules, and tested under laboratory environments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.6018-6033
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• 2018

Fires are a common cause of catastrophic personal injuries and devastating property damage. Every year, many fires occur and threaten human lives and property around the world. Providing early important sign for early fire detection, and therefore the detection of smoke is always the first step in fire-alarm systems. In this paper we propose an automatic smoke detection system built on camera surveillance and image processing technologies. The key features used in our algorithm are to detect and track smoke as moving objects and distinguish smoke from non-smoke objects using a convolutional neural network (CNN) model for cascade classification. The results of our experiment, in comparison with those of some earlier studies, show that the proposed algorithm is very effective not only in detecting smoke, but also in reducing false positives.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1027-1028
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• 2008

In this paper, we proposed image-processing technique for automatic real-time fire and smoke detection in tunnel fire environment. To minimize false detection of fire in tunnel we used motion information of video sequence. And this makes it possible to detect exact position of event in early stage with detection, test, and verification procedures. In addition, by comparing false detection elimination results of each step, we have proved the validity and efficiency of proposed algorithm.