“FIRE SIGHT: HARNESSING MACHINE LEARNING MODELS TO ANTICIPATE WILD FIRES”

Machine Learning

Fighting forest fires requires the use of crucial tools, such as the Fire in the Forest Prediction. Due to the depletion of water supplies, this serious environmental issue exacerbates water pollution and global warming. One of the most important components of averting disastrous events is fire detection. It is anticipated that predicting forest fires will lessen the damage that they inflict in the future. In this research, presented a machine learning-based forest fire prediction system,The goal is to create a precise and trustworthy model that takes into account a variety of environmental elements in order to predict the likelihood of forest fires. The crucial components, such as temperature, humidity, wind speed, vegetation indices, and past fire trends, are then extracted from this data through processing and analysis. With the use of machine learning algorithms and this data, able to train a predictive model to comprehend the complex relationships that exist between the input variables and the frequency of forest fires. In order to support effective forest management and environmental preservation, the study's findings can be utilized to develop real-time systems for predicted forest fires.now two methods were identified and used to anticipate wild fires which decision tree ,random forest.in accuracy aspect random forest is results gave 71.42% than decision tree.

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