• 디지털산업정보학회논문지
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• 제19권4호
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• pp.117-126
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• 2023

Traditional markets, formed naturally, often feature aged buildings and facilities that are susceptible to fire. However, the lack of adequate fire detection systems in these markets can easily lead to large-scale fires upon ignition. Therefore, this study was conducted with the aim of detecting fires in traditional markets, utilizing thermal imaging cameras for data collection and the YOLOv8 model for object detection experiments. Data were collected in the night markets within traditional markets of xx city and by simulating fire scenarios. A comparative analysis of the Nano and XL models of YOLOv8 revealed that the XL model is more effective in detecting fires. The XL model not only demonstrated higher accuracy in correctly identifying flames but also tended to miss fewer fires compared to the Nano model. In the case of objects other than flames, the XL model showed superior performance over the Nano model. Taking all these factors into account, it is anticipated that with further data collection and improvement in model performance, a suitable fire detection system for traditional markets can be developed.

• 한국컴퓨터정보학회논문지
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• 제25권7호
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• pp.9-16
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• 2020

본 연구에서는 다중 센서를 사용하여 화재 감지를 수행하는 알고리즘을 제안하고 시스템을 구현하였다. 제안하는 알고리즘은 다중 센서의 데이터를 기반으로 규칙을 적용하여 화재를 판정한다. 화재 발생은 약 3~5분의 시간이 걸리며 이 시간은 화재 감지의 최적 시간이다. 이는 잠재적 화재 발생을 적시에 식별하는 것이 화재 관리에 중요하다는 것을 의미한다. 국내의 경우 화재 국가 법령에 따라 대부분 건물에 화재경보기 설비를 장착하고 있다. 그러나 현재 사용하는 화재 감지 장치는 연기나 열을 감지하는 하나의 센서에 의존하기 때문에 허위 경보에 매우 취약하다. 최근에는 IoT의 기술 발달로 화재 감지기에 여러 개의 센서를 통합할 수 있다. 또한, 화재 감지기는 다른 물체와 통신을 할 수 있으며 프로그램된 작업을 수행할 수 있는 스마트 기술이 개발되었다. 제작된 프로토타입은 10건의 실제 실험을 기준으로 90%의 성공률과 10%의 거짓 경보율을 기록했다.

• 해양환경안전학회지
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• 제25권4호
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• pp.476-481
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• 2019

화재의 초기 검출은 인명과 재화의 손실을 최소화하기 위한 중요한 요소이다. 불꽃과 연기를 신속하면서 동시에 검출해야 하며 이를 위해 영상 기반의 화재 검출에 관한 연구가 다양하게 진행되고 있다. 기존의 화재 검출은 불꽃과 연기의 특징을 추출하기 위해 여러 알고리즘을 거쳐서 화재의 검출 유무를 판단하므로 연산량이 많이 소모되었으나, 딥러닝 알고리즘인 합성곱 신경망을 이용하면 별도의 과정이 생략되므로 신속하게 검출할 수 있다. 본 논문에서는 선박 기관실에서 화재 영상을 녹화한 데이터로 실험을 수행하였다. 불꽃과 연기의 특징을 외각 상자로 추출한 후 합성곱 신경망 중 하나인 욜로(YOLO)를 이용하여 학습하고 결과를 테스트하였다. 실험 결과를 검출률, 오검출률, 정확도로 평가하였으며 불꽃은 0.994, 0.011, 0.998, 연기는 0.978, 0.021, 0.978을 나타내었고, 연산시간은 0.009s를 소모됨을 확인하였다.

• 한국가스학회지
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• 제16권6호
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• pp.107-114
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• 2012

화재감지 시스템은 화재발생 시 위험 감지 및 전파를 위해 사용되고 있는데, 현재 사용 중인 대부분의 화재감지 시스템은 실보와 비화재보의 가능성으로부터 오동작이 빈번하게 발생한다. 본 연구에서는 화재감지의 신뢰성 개선을 위해 열 감지기, 연기 감지기 및 일산화탄소 농도 감지기의 3가지 독립정보를 통합적으로 이용하여 화재를 감지하는 알고리즘을 제안하고, LabVIEW를 이용하여 test bed를 구축하여 검증하였다. 즉, NIST의 Fire Research Division에서 제공하는 상황별 센서 측정 데이터를 이용하여 시뮬레이션을 진행하였으며, 실보와 비화재보의 가능성을 저감시키는 것을 확인할 수 있었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권10호
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• pp.3475-3489
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• 2014

Here we present a simple flame detection method for an infrared (IR) thermal camera based real-time fire surveillance digital signal processor (DSP) system. Infrared thermal cameras are especially advantageous for unattended fire surveillance. All-weather monitoring is possible, regardless of illumination and climate conditions, and the data quantity to be processed is one-third that of color videos. Conventional IR camera-based fire detection methods used mainly pixel-based temporal correlation functions. In the temporal correlation function-based methods, temporal changes in pixel intensity generated by the irregular motion and spreading of the flame pixels are measured using correlation functions. The correlation values of non-flame regions are uniform, but the flame regions have irregular temporal correlation values. To satisfy the requirement of early detection, all fire detection techniques should be practically applied within a very short period of time. The conventional pixel-based correlation function is computationally intensive. In this paper, we propose an IR camera-based simple flame detection algorithm optimized with a compact embedded DSP system to achieve early detection. To reduce the computational load, block-based calculations are used to select the candidate flame region and measure the temporal motion of flames. These functions are used together to obtain the early flame detection algorithm. The proposed simple algorithm was tested to verify the required function and performance in real-time using IR test videos and a real-time DSP system. The findings indicated that the system detected the flames within 5 to 20 seconds, and had a correct flame detection ratio of 100% with an acceptable false detection ratio in video sequence level.

• International Journal of Control, Automation, and Systems
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• 제4권1호
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• pp.70-76
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• 2006

The objective of this paper is to propose a reference model of a fire detection and monitoring system using MS/TP protocol. The reference model is designed to satisfy the requirements of response time and flexibility. The reference model is operated on the basis of BACnet, a standard communication protocol for building automation systems. Validity of the reference model was examined using a simulation model. This study also evaluated the performance of the BACnet-based fire detection and monitoring system in terms of network-induced delay. Simulation results show that the reference model satisfies the requirements of the fire detection and monitoring system.

• 한국정밀공학회지
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• 제31권9호
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• pp.847-854
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• 2014

The paper presented a method of early fire detection based on the environmental characteristics inside the nacelle of wind turbine generator system(WTGS). The rising rates of the temperature and smoke density were used as the parameters for early fire detection. By considering the characteristics of temperature and smoke density of a nacelle, this method is very reliable and can minimize the possibility of a malfunction of fire detection. The performance of the method was tested through sets of experiments by using nacelle simulator.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2006년도 하계종합학술대회
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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.

• 제어로봇시스템학회논문지
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• 제10권8호
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• pp.734-741
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• 2004

This paper presents a network based fire detection system using CAN, in order to evaluate feasibility of home automation protocol for smart home. In general, because a traditional fire detection system has an analog transmission method with 4-20mA current, it has several shortcomings such as weakness to noise. Hence, as an alternative to the traditional system, this paper presents the architecture of CAN based fire detection system and the design method of CAN communication network. Also, the performance of the suggested system is evaluated through an experimental testbed. Especially, CAN has several advantages such as low cost and easiness of implementation compared to Ethernet or ARCNET, which are low layer of BACNet. Therefore, if CAN is adopted as low layer of BACNet, the home automation system is implemented more effectively.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2018년도 전력전자학술대회
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• pp.267-269
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• 2018

This paper is a study to solve the malfunction of Fire Detection System and to react swiftly in case of fire. if a fire occurs because of malfunction of the fire receiver, it may not be possible to respond appropriately. in order to solve this problem, Fire Detection System using IoT, the manager studied the method of confirming the fire occurrence with mobile phone Application. We propose a wireless Fire Detection System by building a server and a client using a micom and a mobile phone application. This is to reduce the damage caused by the fire.