A forest smoke recognition system based on deep learning

Forests, as vital ecological resources of the Earth, frequently witness devastating wildfires that pose enormous threats to the environment, ecosystems, and human life. To mitigate the losses caused by forest fires, it is imperative to enhance fire prediction and control measures, with video surveillance technology playing a pivotal role in fire watch. Focusing on the extraction of prominent features from wildfire videos and the application of deep learning techniques, the system employs unmanned aerial vehicles (UAVs) to acquire navigational video data in forest areas, integrating multiple payloads for real-time forest fire detection. The project enhances methods for identifying smoke from forest fires in videos, ensuring a stable and reliable forest fire monitoring system alongside real-time data acquisition.