• Proceedings of the Safety Management and Science Conference
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• 2013.04a
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• pp.409-420
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• 2013

본 연구에서는 인천광역시의 37개 사업장(공장)을 대상으로 작업현장의 소음을 측정 및 분석하여 소음이 화재경보음 인지에 미치는 영향을 분석하였다. 측정결과 평균소음이 95.8dB(A)나왔다. 이는 국내 경보장치 음량기준(화재경보음 발생장치에서 1m떨어진 곳에서 90dB이상)보다 5.8dB(A)높게 나왔다. 미국방화협회(NFPA)에 따르면 암소음(기기음)이 85dB(A)이거나 이상일 경우 화재경보음 인지정도가 미흡하기 때문에 다른 방법을 강구하도록 되어 있다. 또한 화재경보음은 암소음보다 15dB(A) 높아야 한다고 하고 있다. 따라서 주변의 환경을 무시한 획일적인 화재경보음 설계에 대해서 제도적 및 법적 개선이 필요하다고 사료된다.

• Fire Science and Engineering
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• v.19 no.4 s.60
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• pp.64-68
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• 2005

In this paper, we studied fire position recognition and alarm system when we acquired CCDcamera image of fire region and position. We proposed effectively extraction system of boundary of fire region using RED Filtering, and applied 2-graylevel image method to fire boundary extraction. Finally we can make system of fire position and region using mask extraction and matching for fire recognition. For the purpose of experiment result, we effectively recognized that the tire occurrence position and region have steadily spread.

• Journal of the Semiconductor & Display Technology
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• v.23 no.1
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• pp.110-116
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• 2024

Despite the continuous advancement of science and technology, fire accidents continue to occur without decreasing over time, so there is a constant need for a system that can accurately detect fires at an early stage. However, because most existing fire detection systems detect fire in the early stage of combustion when smoke is generated, rapid fire prevention actions may be delayed. Therefore we propose an early fire detection system that can perform early fire detection at a reasonable cost using LSTM, a deep learning model based on multi-gas sensors with high selectivity in the early stage of decomposition rather than the smoke generation stage. This system combines multiple gas sensors to achieve faster detection speeds than traditional sensors. In addition, through window sliding techniques and model light-weighting, the false alarm rate is low while maintaining the same high accuracy as existing deep learning. This shows that the proposed fire early detection system is a meaningful research in the disaster and engineering fields.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2002.11a
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• pp.165-171
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• 2002

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.04a
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• pp.497-498
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• 2012

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.426-429
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• 2007

When a fire happens in builds or apartments, peoples are tend to be caught in dangerous situations owing to the failure of searching escape route to the outside. In this work, an efficient fire detection and alarm system which makes it possible for the escapers to take adequate actions is proposed. The proposed system consists of two parts. One is fire detection modules which are located at each compartments in a building. The other is fire warning modules equipped with portable flashes having ability of visual/voice warning. Fire detection information is transmitted between each modules wirelessly. In this work, an efficient communication protocol for sensor network-based fire detection system is proposed and its feasibility is verified by practical experiments using MANGO ZDK Development tools

• Journal of the Semiconductor & Display Technology
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• v.20 no.3
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• pp.161-166
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• 2021

To prevent accidents caused by changes in the surrounding environment or other factors, various protection facilities are installed at the photovoltaic connection module. The main causes of fire are sparks due to foreign substances inside the photovoltaic connection module through high temperature rise and dew condensation in the photovoltaic connection module, and fire due to heat from the power diode. The proposed method can predict the fire by measuring flame, carbon dioxide, carbon monoxide, temperature, humidity, input voltage, and current on the photovoltaic connection module, and when the fire conditions are reached, fire alarm and power off can be sent to managers and users in real time to prevent fire in advance.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.9
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• pp.953-958
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• 2015

Raspberry Pi is a credit card-sized computer with support for a large number of input and output peripherals. This makes it the perfect platform for interaction with many different devices and for usage in a wide range of applications. When combined with Wi-Fi, it can communicate remotely, therefore increasing its suitability for the construction of wireless sensor nodes. In addition, data processing and decision-making can be based on artificial intelligence, what is performed in developed testbed on the example of monitoring and determining the confidence of fire. In this paper, we demonstrated the usage of Raspberry Pi as a sensor web node for fire-safety monitoring in a building. When the UV-flame sensors detect a flame as thin as that of a candle, the Raspberry Pi sends a push-message to notify the assigned smartphone of the on-site situation through the GCM server. A mobile app was developed to provide a real-time video streaming service in order to determine a false alarm. If an emergency occurs, one can immediately call for help.

• Journal of Information Processing Systems
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• v.13 no.3
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• pp.590-598
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• 2017

Recently, there has been an increase in the number of hazardous events, such as fire accidents. Monitoring systems that rely on human resources depend on people; hence, the performance of the system can be degraded when human operators are fatigued or tensed. It is easy to use fire alarm boxes; however, these are frequently activated by external factors such as temperature and humidity. We propose an approach to fire detection using an image processing technique. In this paper, we propose a fire detection method using multichannel information and gray level co-occurrence matrix (GLCM) image features. Multi-channels consist of RGB, YCbCr, and HSV color spaces. The flame color and smoke texture information are used to detect the flames and smoke, respectively. The experimental results show that the proposed method performs better than the previous method in terms of accuracy of fire detection.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2012.04a
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• pp.147-150
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• 2012

This study restoration worker for dispersion relay in R-Type fire alarm system. Restoration worker very good instrument for an fire system inspector. When inspector check for fire system someone need reset for fir system to normal state. This chain of action is frequent and troublesome. In this case, If we can automatic reset for fire system it's restoration worker. This paper settlement on the problem for reset fire system. Design, make grabber for restoration worker. The test offer proof possibility restoration worker.