• Journal of Multimedia Information System
• /
• v.4 no.2
• /
• pp.79-82
• /
• 2017

Smoke and fire have different shapes and colours. This article suggests a fully connected system which is used two features using Adaboost algorithm for constructing a strong classifier as linear combination. We calculate the local histogram feature by gradient and bin, local binary pattern value, and projection vectors for each cell. According to the histogram magnitude, this paper applied adapted weighting value to improve the recognition rate. To preserve the local region and shape feature which has edge intensity, this paper processed the normalization sequence. For the extracted features, this paper Adaboost algorithm which makes strong classification to classify the objects. Our smoke detection system based on the proposed approach leads to higher detection accuracy than other system.

• Korean Journal of Remote Sensing
• /
• v.36 no.5_1
• /
• pp.775-784
• /
• 2020

Recent global warming and anthropogenic activities have caused more frequent and massive wildfires with longer durations and more significant damages. MODIS has been monitoring global wildfires for almost 20 years, and GK2A and Himawari-8 are observing the wildfires in East Asia 144 times a day. However, the spatial resolution of 1 to 2 km is not sufficient for the detection of small and medium-size active fires, and therefore the studies on the active fire detection using high-resolution images are essential. However, there is no official product for the high-resolution active fire detection. Hence, we implemented the active fire detection algorithm of Landsat 8 and carried out a high-resolution-based detection of active fires in Australia in 2019, followed by the comparisons with the products of Himawari-8 and MODIS. Regarding the intense fires, the three satellites showed similar results, whereas the weak igniting and extinguishing fires or the fires in narrow areas were detected by only Landsat 8 with a 30m resolution. Small-sized fires, which are the majority in Korea, can be detected by the high-resolution satellites such as Landsat 8, Sentinel-2, Kompsat-3A, and the forthcoming Kompsat-7. Also, a comprehensive analysis together with the geostationary satellites in East Asia such as GK2A, Himawari-8, and Fengyun-3 will help the interoperability and the improvement of spatial and temporal resolutions.

• Journal of the Society of Disaster Information
• /
• v.18 no.4
• /
• pp.922-929
• /
• 2022

Purpose: The purpose of this paper is to develop a deep learning model to detect fire extinguishers in images taken from CCTVs in underground utility tunnels. Method: Various fire extinguisher images were collected for detection of fire extinguishers in the running-based underground utility tunnel, and a model applying the One-stage Detector method was developed based on the CNN algorithm. Result: The detection rate of fire extinguishers photographed within 10m through CCTV video in the underground common area is over 96%, showing excellent detection rate. However, it was confirmed that the fire extinguisher object detection rate drops sharply at a distance of 10m or more, in a state where it is difficult to see with the naked eye. Conclusion: This paper develops a model for detecting fire extinguisher objects in underground common areas, and the model shows high performance, and it is judged that it can be used for underground common area digital twin model synchronizing.

• Journal of Digital Convergence
• /
• v.10 no.7
• /
• pp.141-152
• /
• 2012

The typical evacuation guidance system based on fire detectors, which is being widely used in theaters and large buildings, is often operated in an analog manner. In case of fire, it often causes the system to lose a wired line or wireless fire detection sensor, resulting in the difficulty of transmitting signals from a wired or wireless fire detection sensor to the main fire monitoring device. Accordingly, this paper has proposed the broadcasting system for disaster management, having an efficient evacuation guidance plan when a disaster occurs. The system reacts to an emergency situation along with fire alarm sirens in real time. We have implemented the above system by means of a simulation program that prints the evacuation guidance information (e.g., location and time of fire, and evacuation path) on an LCD located in a building through the fire sensor network in case of an emergency (e.g., actual fire). We have developed the simulation system by using mathematical algorithms, such as the optimal path search and the fire smoke diffusion algorithm. This simulation program considers the structure of a building and the location where the fire has initially occurred, applying it to the simulator.

• Journal of Satellite, Information and Communications
• /
• v.9 no.4
• /
• pp.91-96
• /
• 2014

This paper proposed an adaptive threshold method for detecting flame candidate regions in a infrared image and it adapts according to the contrast and intensity changes in the image. Conventional flame detection systems uses fixed threshold method since surveillance environment does not change, once the system installed. But it needs a adaptive threshold method as requirements of surveillance system has changed. The proposed adaptive threshold algorithm uses the dynamic behavior of flame as featured parameter. The test result is analysed by comparing test result of proposed adaptive threshold algorithm and conventional fixed threshold method. The analysed data shows, the proposed method has 91.42% of correct detection rate and false detection is reduced by 20% comparing to the conventional method.

• The KIPS Transactions:PartB
• /
• v.16B no.6
• /
• pp.463-470
• /
• 2009

In this paper, we propose the advanced fire-flame detection algorithm using camera image for better performance than previous sensors-based systems which is limited on small area. Also, previous works using camera image were depend on a lot of heuristic thresholds or required an additional computation time. To solve these problems, we use statistical values and divide image into blocks to reduce the processing time. First, from the captured image, candidate flame regions are detected by a background model and fire colored models of the fire-flame. After the probability models are formed using the change of luminance, wavelet transform and the change of motion on time axis, they are used for membership function of fuzzy logic. Finally, the result function is made by the defuzzification, and the probability value of fire-flame is estimated. The proposed system has shown better performance when it compared to Toreyin's method which perform well among existing algorithms.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.21 no.5
• /
• pp.453-456
• /
• 2016

The major causes of electrical fire in low-voltage distribution lines are classified into short-circuit fault, overload fault, electric leakage, and electric contact failure. The special principal factor of the fire is electric arc or spark accompanied with such electric faults. This paper studies the development of an electric fire prevention system with detection and alarm of that in case of parallel arc fault occurrence in low-voltage distribution lines. The proposed system is designed on algorithm sensing the instantaneous voltage drop of line voltage at arc fault occurrence. The proposed detector has characteristics of high-speed operation responsibility and superior system reliability from composition using a large number of semiconductor devices. A new sensing control method that shows the detection of parallel arc fault is sensed to ripple voltage drop through a diode bridge full-wave rectifier at electrical accident occurrence. Some experimental tests of the proposed system also confirm the practicality and validity of the analytical results.

• Journal of KIISE:Software and Applications
• /
• v.37 no.9
• /
• pp.712-721
• /
• 2010

This paper proposes a new fire-flame detection method using probabilistic membership function of visual features and Fuzzy Finite Automata (FFA). First, moving regions are detected by analyzing the background subtraction and candidate flame regions then identified by applying flame color models. Since flame regions generally have continuous and an irregular pattern continuously, membership functions of variance of intensity, wavelet energy and motion orientation are generated and applied to FFA. Since FFA combines the capabilities of automata with fuzzy logic, it not only provides a systemic approach to handle uncertainty in computational systems, but also can handle continuous spaces. The proposed algorithm is successfully applied to various fire videos and shows a better detection performance when compared with other methods.

• Journal of the Korean Society of Safety
• /
• v.34 no.3
• /
• pp.15-20
• /
• 2019

As industry is progressing and standards of living are improved, the demand of electrical energy is expected to grow 8-9% annually. Therefore, the importance of electrical fire prevention technology with the ability of the power supply is being emphasized. According to the statistics of fire in Korea, fire occurred about 45,000 cases annually, and electrical fire possessed about 20%. The electrical fire by poor contact has increased gradually, can be connected as great fire to secondarily induce short circuit and earth fault. Then analysis of heating causes of electrical connections between copper and copper alloy is needed. Also, detection and analysis algorithm of oxide at copper alloy are necessary. In this research, in order to understand the characteristics of oxide growth with rising resistance and heating, it is demonstrated that the oxide at electrical connections can cause fire due to arcing.

• Journal of the Korean Society of Safety
• /
• v.37 no.4
• /
• pp.28-35
• /
• 2022

This study is aimed to develop a safety diagnosis system for fire pumps that detects normal and abnormal signals for the stable operation of the system. Hence, the following activities were carried out: first, a threshold value was identified for the normal operation and six abnormal operations (adherence of impeller, absence of water source, separation of pump and motor, run-stop operation, air inflow into the casing, and reverse-phase loss of the power line) reflecting changes in the current, flow and pressure of fire pumps; secondly, based on the identified signals, an algorithm capable of detecting three abnormal signals was developed and in terms of hardware, a current, pressure and flow sensor suitable for the analogue input values of NI-6009 was designed and installed. This combination of the hardware and software is applicable as a diagnosis system to ensure the stable operation of fire pumps.