Early Forest Fire Detection Using Machine Learning Algorithms

Pradeep Kumar G, Rahul R, Ravindharan N

Accuracy, KNN Algorithm, Random Forest Algorithm, Segmentation.

Apart from inflicting tragic loss of lives and valuable natural and individual properties as well as thousands of hectares of forest and many homes forest fires are an excellent menace to ecologically healthy big forests and to the atmosphere.  Every year, thousands of fire across the world cause disasters on the far side live and outline. This issue has been the analysis interest for several years, there are a large quantity of good studied solutions accessible out there for testing or maybe prepared to be used to resolve this downside. Forest and concrete fires are major problem for several countries within the world. Currently, there are many different solutions to detect the forest fires. People are using sensors to detect the fire. But this case is not possible for large acres of forest. In this paper, we discuss a new approach for fire detection, in which modern technologies are used. In particular, we propose a platform that is the Artificial Intelligence. The computer vision methods for recognition and detection of smoke and fire, based on the still images or the video input from the cameras. Machine learning for finding the output. The accuracy is based on the algorithms which we are going to use and the datasets and splitting them into train set and test set.