Abstract
Fire outbreak is a major issue in oil wells, forests, houses, industries all over the world. The damage caused by these types of accidents is tremendous towards nature and humankind. After these incidents, the need for an application for fire detection has increased. However various fire detection systems use temperature or smoke sensors which takes more response time. Moreover, these systems are expensive and are not widely effective, when the fire is placed far away from the detectors. This led to various alternatives such as computer vision, image processing techniques. One of the cost-effective methods would be the usage of surveillance cameras to detect the fire to inform the relevant parties. The proposed research work suggests a method to use surveillance cameras to monitor the occurrence of fire anywhere within the camera range. In this method, an RGB color pattern and motion detection technologies are used to detect the fire by background subtraction method. The choice capacity of fire-pixels is concluded by the force and immersion of the R part. It has been used that finds the boundary of the moving region in the color segmented image and calculates the number of fire pixels in this area. At that point, a fire identification framework is created dependent on this technique to identify fire effectively to spare life and property from fireperil.
Highlights
Fire accident, especially in industries, buildings and in oil wells causes severe damage to many lives of people
There is an increase in the need for fire detection based on image processing and computer vision for such devices
Based color model, which is a combination of Gaussian models in RGB space derived from a training collection of fire pixels, Chen's fire classification system was combined with the motion detection technique of the current methods
Summary
Especially in industries, buildings and in oil wells causes severe damage to many lives of people. In order the ionize the particle inside the detector it takes more time Apart from this, they are a few methods in image processing to detect the fire such as rule-based algorithm, edge detection, etc. There is an increase in the need for fire detection based on image processing and computer vision for such devices This method is installed in the CCTV camera, UAVS, etc. Cv-based fire detection systems consist of three stages: fire pixel recognition, moving object segmentation, and candidate area analysis This procedure is dependent on two factors: the form of the region and the region's time-related shifts. J based color model, which is a combination of Gaussian models in RGB space derived from a training collection of fire pixels, Chen's fire classification system was combined with the motion detection technique of the current methods. 3.1.3 WIFI Module The ESP8266 WIFI module is used to transmit the signal for response and reflex to cease fire accident
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