Abstract
It is important for fire detectors to operate quickly in the event of a fire, but existing conventional fire detectors sometimes do not work properly or there are problems where non-fire or false reporting occurs frequently. Therefore, in this study, HSV color conversion and Harris Corner Detection were used in the image pre-processing step to reduce the incidence of false detections. In addition, among the detected corners, the vicinity of the corner point facing the upper direction was extracted as a region of interest (ROI), and the fire was determined using a convolutional neural network (CNN). These methods were designed to detect the appearance of flames based on top-pointing properties, which resulted in higher accuracy and higher precision than when input images were still used in conventional object detection algorithms. This also reduced the false detection rate for non-fires, enabling high-precision fire detection.
Highlights
In the case of fire, death is more often caused by the inhalation of toxic substances such as carbon monoxide than by direct injury caused by burns
Existing sensor-based fire detectors include flame detectors that detect infrared (IR) and ultraviolet (UV) energy, and heat detectors that detect heat sources. These sensor-based fire detection methods are limited in indoor environments, and the more sensitive such detectors are to IR, UV, and heat, the more they react to other factors, resulting in unnecessary manpower consumption due to the malfunction of alarms
The proposed method to increase the detection accuracy of a flame was divided into two main procedures
Summary
In the case of fire, death is more often caused by the inhalation of toxic substances such as carbon monoxide than by direct injury caused by burns. Existing sensor-based fire detectors include flame detectors that detect infrared (IR) and ultraviolet (UV) energy, and heat detectors that detect heat sources. These sensor-based fire detection methods are limited in indoor environments, and the more sensitive such detectors are to IR, UV, and heat, the more they react to other factors, resulting in unnecessary manpower consumption due to the malfunction of alarms. There are limitations, such as the inability to provide information about the location and size of fires, and frequent false fire alarms if the physical sensor is close to the source of the fire, or in contrast, if there are factors that make the operation of the fire detector too sensitive. If actual fires occur in a wide range of areas such as large factories and mountains, early fire detection is difficult with existing sensor-based fire detection systems
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