• Journal of Convergence Society for SMB
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• v.6 no.3
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• pp.37-41
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• 2016

In this paper, we propose a fire alarm system that utilizes Wi-Fi to alarm multiple people at once. This system, based on Arduino, uses smoke, flame and temperature sensor units to sense fire and send detection data to a server via wireless communication system. The server uses stored data to relay current fire situations gathered from nearby sensors to smartphones. It also automatically reports the fire using location data from sensors. Using this system, we were able to retrieve fire alarm from sensors via push notification of our smartphone. We also confirmed the establishment of linkage with sensors and automatic report of fire via SMS. From this result, the possibility of sending real-time notifications via the Internet toward nearby smartphones about disasters such as conflagration has been proven to be feasible.

• Journal of the Korea Society of Computer and Information
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• v.25 no.7
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• pp.9-16
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• 2020

In this paper, we propose a prototype design and implementation of a fire detection algorithm using multiple sensors. The proposed topic detection system determines fire by applying rules based on data from multiple sensors. The fire takes about 3 to 5 minutes, which is the optimal time for fire detection. This means that timely identification of potential fires is important for fire management. However, current fire detection devices are very vulnerable to false alarms because they rely on a single sensor to detect smoke or heat. Recently, with the development of IoT technology, it is possible to integrate multiple sensors into a fire detector. In addition, the fire detector has been developed with a smart technology that can communicate with other objects and perform programmed tasks. The prototype was produced with a success rate of 90% and a false alarm rate of 10% based on 10 actual experiments.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.1
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• pp.9-18
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• 2010

Our country has so large mountain area that the tunnel construction is inevitable and the need of incident detection that provides safe management of tunnels is increasing. In this paper, we suggest a tunnel incident detection system using computer vision techniques, which can detect the incidents in a tunnel and provides the information to the tunnel administrative office in order to help safe tunnel operation. The suggested system enhances the processing speed by using simple processing algorithm such as image subtraction, and ensures the accuracy of the system by focused on the incident detection itself rather than its classification. The system is also cost effective because the video data from 4 cameras can be simultaneously analyzed in a single PC-based system. Our system can be easily extended because the PC-based analyzer can be increased according to the number of cameras in a tunnel. Also our web-based structure is useful to connect the other remotely located tunnel incident systems to obtain interoperability between tunnels. Through the experiments the system has successfully detected the incidents in real time including dropped luggage, stoped car, traffic congestion, man walker or bicycle, smoke or fire, reverse driving, etc.

• Journal of the Korea Society of Computer and Information
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• v.18 no.10
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• pp.89-95
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• 2013

Smoking in elevators is a criminal offense that is included in a misdemeanor. Because of that smoking in elevators can be very critical for our growing children and weak women. 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-X2-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. In the experiment, we show process and number of scene change detection, and the number of video searched per retrieval time. The extracted smoking video is to submit as evidence for the police or court.

• ETRI Journal
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• v.42 no.4
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• pp.480-490
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• 2020

More than 42 000 fires occur nationwide and cause over 2500 casualties every year. There is a lack of specialized equipment, and rescue operations are conducted with a minimal number of apparatuses. Through-the-wall radars (TTWRs) can improve the rescue efficiency, particularly under limited visibility due to smoke, walls, and collapsed debris. To overcome detection challenges and maintain a small-form factor, a TTWR system-on-chip (SoC) and its architecture have been proposed. Additive reception based on coherent clocks and reconfigurability can fulfill the TTWR demands. A clock-based single-chip infrared radar transceiver with embedded control logic is implemented using a 130-nm complementary metal oxide semiconductor. Clock signals drive the radar operation. Signal-to-noise ratio enhancements are achieved using the repetitive coherent clock schemes. The hand-held prototype radar that uses the TTWR SoC operates in real time, allowing seamless data capture, processing, and display of the target information. The prototype is tested under various pseudo-disaster conditions. The test standards and methods, developed along with the system, are also presented.

• Journal of the Korean Society of Safety
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• v.16 no.1
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• pp.1-8
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• 2001

All objects emit thermal radiation and this radiation is the basis of the techniques used to detect flames. The usual phenomena occurring in the initial stage of the fire are generally invisible products of a combustion and visible smoke. Liquid or gaseous materials do not undergo a smoldering stage so that fires develop very rapidly. Also, the heat generated by the initial flames is usually not sufficient to activate a heat detector. In this case the most effective criterion for automatic fire detection is the flame. According to the fire regulation of korea, the compulsory standard provided that a flame detector shall be installed in a place that the attachment height of detector is higher than 20 m, chemical plants, hangar, refinery, etc.. The results of the research and development are discriminated between a flame and other radiant emitters, developed a UV detector tube contains an inert gas which absorbs UV radiation, developed PZT pyroelectric element is based on the use of photovoltanic cell, developed IR band-pass filter that only allow a 4.3 $\mu\textrm{m}$ radiation wavelength to reach the sensors and developed UV-IR combination flame detector combined into a single detection device.

• 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.

• IE interfaces
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• v.19 no.1
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• pp.43-52
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• 2006

In order to make best use of NC machine tools with minimal labor costs, they need to be in operation 24 hours a day without being attended by human operators except for setup and tool changes. Thus, unattended machining is becoming a dream of every modern machine shop. However, without a proper mechanism for real-time monitoring of the machining processes, unattended machine could lead to a disaster. Investigated in this paper are ways to using PC camera as a real-time monitoring system for unattended NC milling operations. This study defined five machining states READY, NORMAL MACHINING, ABNORMAL MACHINING, COLLISION and END-OF-MACHINING and modeled them with DEVS (discrete event system) formalism. An image change detection algorithm has been developed to detect the table movements and a flame and smoke detection algorithm to detect unstable cutting process. Spindle on/off and cutting status could be successfully detected from the sound signals. Initial experimentation shows that the PC camera could be used as a reliable monitoring system for unattended NC machining.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.6
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• pp.1257-1262
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• 2018

In this paper, a deep learning method is proposed to detect the fire effectively by using video of surveillance camera. Based on AlexNet model, classification performance is compared according to kernel size and stride of convolution layer. Dataset for learning and interfering are classified into two classes such as normal and fire. Normal images include clouds, and foggy images, and fire images include smoke and flames images, respectively. As results of simulations, it is shown that the larger kernel size and smaller stride shows better performance.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.2043-2048
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• 2011

According to the statistical report from National Emergency Management Agency (NEMA) in Korea, the accident rate of closed switchboards in power systems occupies over 40%. In this paper, an integrated sensor module for monitoring the condition of closed switchboards is described. The sensor module monitors electro-magnetic (EM) wave, ultra-violet (UV) ray, heat and smoke generated by electrical discharges or insulation breakdown. The effective detection ranges were decided from experiment results; 100 kHz~10 MHz for EM wave, 220 nm~395 nm for UV ray and 0~$150^{\circ}C$ for heat, respectively. The prototype sensor module includes all functions above-mentioned in one device.