• Proceedings of the Korean Society of Disaster Information Conference
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• 2022.10a
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• pp.429-430
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• 2022

본 논문에서는 일산화탄소 센서와 미세먼지 센서를 이용하여 연기농도에 따른 감도시험을 수행하였다. 일산화탄소 센서와 미세먼지 센서는 광전식감지기 감도시험 챔버 내에서 발생시킨 연기농도에 따라 감지반응이 있었으며, 다양한 화재정보를 제공을 위해 가스 센서 및 미세먼지 센서가 기술기준 도입이 필요할 것으로 사료된다.

• Proceedings of the KAIS Fall Conference
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• 2011.05a
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• pp.393-395
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• 2011

기존의 화재 감시 시스템은 보통 연기, CO 혹은 온도와 온도의 변화량을 가지고 화재 여부를 판단하였다. 대부분의 각각의 센서에서 측정된 값을 가지고 미리 설정한 값과 비교하여 기준을 넘었을 경우에 화재라고 결정한다.건물 내부에 화재가 발생하였을 경우에는 연기와 고열로 인하여 접근이 어려울 경우가 대부분이다. 사람의 손이 닿지 않는 경우에 화재 감시반 센서모듈을 통하여 고열과 가득한 연기로 인한 내부 환경을 판정하여서 화재상황을 인식하는 방식을 제안한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.497-498
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• 2018

In the fire scene, it is difficult to see 1m ahead because of power failure, smoke and toxic gas, even with thermal imaging camera and Xenon searchlight. Analysis of the smoke particles in the fire scene shows that even if the smoke is $5{\mu}m$ or less in wavelength, it is difficult to obtain a front view when using a conventional thermal imaging camera if the visual distance exceeds 1 meter. In the case of black smoke with a particle wavelength of $5{\mu}m$ or more, a space permeation sensor technology using various sensors other than a single sensor is required because chemical materials, gas, and water molecules are mixed. Firefighters need a smoke detection technology for smoke detection and spatial information visualization for forward safety view.In this paper, we design the interface of the information processing system with 32bit CPU core and peripheral circuit. We also implemented and simulated the interface with Lidar sensor. Through this, we provide interface that can implement information processing system of human enhancement fire helmet in the future.

• 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.

• 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.

• Fire Science and Engineering
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• v.28 no.2
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• pp.54-63
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• 2014

The purpose of this study is to test the adaptability of the CO sensor as a fire detector by analyzing its sensing characteristics on fire. In order to test the applicability, we designed and made a fire testing ground whose size is similar to that regulated by UL 268, carried out real fire tests suggested by UL 268, and conducted a comparison analysis on the sensing characteristics between the CO sensor and a photoelectric smoke detector by different types of fire source. The experiment result to the sensing characteristics of the CO sensor is about twice to three times faster than that of the photoelectric smoke detector, proceeding with incomplete combustion such as paper and wood fire source in the initial fire. Especially in case of wood smoldering fire, sensing characteristics of the CO sensor is very excellent.

• The KIPS Transactions:PartC
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• v.13C no.3 s.106
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• pp.311-316
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• 2006

We propose the optical sensor network using optical CDMA with bipolar receiver and modified Pseudorandom Noise codes which are widely used in the wireless communication network. We numerically analyze the performances in the optical sensor network. In the proposed network, multiple access interferences between two sensors are suppressed by performing synchronization between the optical encoder and the optical decoder and adjusting the delay times of optical delay lines. Numerical simulations confirm that the performance can be acquired by suppressing the beat noise among optical signals as the number of sensors increases.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.499-500
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• 2014

화재발생 시 인명 안전을 위하여 초기의 화재감지가 매우 중요한 요인이다. 특히 도로터널, 지하철역사 등 광범위 폐쇄공간에서 연기에 의한 질식사 등 2차 피해의 발생위험이 높다. 이에 최근 광범위 공간에서 적외선 레이저를 활용한 원거리 연기검출 화재탐지기에 대한 연구가 진행되고 있다. 이러한 레이저 기반 원거리 연기검출장치는 이격(100m 이상) 설치되는 레이저 발신기와 수신기의 레이저 포인트가 정확히 정합되어야 한다. 아울러, 레이저 발신기와 수신기 사이의 거리에 비례하여 레이저 초점의 이동거리가 매우 민감하게 변화하므로 이를 정확히 정합하기 위한 고정밀 제어장치가 필요하다. 따라서 본 논문에서는 복수개의 레이저 발신모듈과 복수개의 조도센서(CdS)를 통해 초점의 정합을 자동 추적할 수 있는 알고리즘을 설계, 구현하였다. 이는 초기 레이저 초점의 설정과 이후 외부환경에 따른 초점의 틀어짐을 자동 보정하여 다양한 레이저 인식 장치에 적용될 것으로 사료된다.

• Journal of Korea Multimedia Society
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• v.17 no.3
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• pp.287-293
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• 2014

Early fire detection is very important to avoid loss of lives and material damage. The conventional smoke detector sensors have difficulties in detecting smoke in large outdoor areas. The video-based smoke detection can overcome these drawbacks. This paper proposes a new smoke detection method in video sequences. It uses the ratio of variation rate of subband energy in the wavelet transform domain. In order to reduce the false alarm, candidate smoke blocks are detected by using motion, decrease of chromaticity and the average intensity of block in the YUV color space. Finally, it decides whether the candidate smoke blocks are smokes or not by using their temporal changes of subband energies in the wavelet transform domain. Experimental results show that the proposed method noticeably increases the accuracy of smoke detection and reduces false alarm compared with the conventional smoke detection methods using wavelets.

• Korean Journal of Food Science and Technology
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• v.49 no.2
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• pp.162-167
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• 2017

A Katsuobushi smoking machine was developed and evaluated to determine its benzo(a)pyrene reducing effect. The machine was equipped with two heaters for smoking and chamber heating. The smoke-generating system was equipped with a cadmium sulfide (CdS) smoke sensor, an on/off controller, and a rotating feeder with a smoke inlet. Raw bonito was steamed and then smoked under three smoke levels. After smoking at $45^{\circ}C$ for 108 h, the benzo(a)pyrene concentrations were 5.87, 7.83, and $11.41{\mu}g/kg$ at the low, middle, and high smoke levels, respectively. The benzo(a)pyrene concentrations after low-level smoking at 45, 65, and $85^{\circ}C$ for 108 h were 5.87, 4.82, and $3.27{\mu}g/kg$, respectively. Accordingly, the optimal conditions for benzo(a)pyrene reduction were a lower smoke level and higher smoking temperature. These optimal smoking conditions can be implemented with the newly developed machine, but is not possible using a conventional Katsuobushi smoking machine.