DETECTION OF FOREST FIRE AND FIREHAWKS USING DEEP LEARNING PLATFORM AND IOT

Abstract: Forest fire is a most seen forest tragedy. Specially in some particular areas, such as high altitude region, once fire comes, it is not only resulting in huge revenue failures, and  it causes more death. So, real-time good vision is useful, and decreasing it into the less task in fire optimizaion. Comparatively  to old temperature-sensed smoke sensor, photo detection has more uses. Used in huge areas , and it can provide photo details. What is more, in huge space, temperature or smoke technology cannot obtain smoke and temperature information faster, so it is impossible in detect fast. Most common  UV and single band IR detectors are applied globally. They are confned by implementation stage. And they are reason for false alertings.Two band IR detection can reduce daylight, light and other sources, and other uses  of dust proof, water proof, and antielectric features. Therefore they are widely used in large areas and below buildings.  The paper has Two band IR fire detection is used on large altitude fire sensing in early time.

Keywords: Deep learning, Internet of Things, Fire detection and Object recognition, Sensors, Zigbee, Micro-controller, Raspberry Pi.