Forest Fire Probability Prediction based on Humidity and Temperature

Forest fire is a major environmental issue, causing destruction of natural resources and loss of life. This study aims to predict the probability of forest fires based on three key environmental factors: humidity, oxygen levels, and temperature. By analyzing the relationship between these factors and the likelihood of forest fires, this study hopes to provide valuable insights for forest management and fire prevention strategies. The proposed approach uses these factors to create a predictive model to identify areas at high risk for forest fires and provide early warning, thereby reducing the risk of forest fires and their negative impacts on the environment and communities. Those areas can make use of this model to predict the probability of forest fire occurrence based on the temperature, humidity and oxygen level of the current weather detected in the risky regions. Finally, the system has the potential to be scalable and can be adapted to different types of forests and environmental conditions, making it a versatile tool for forest fire management. The results of this study provide valuable insights into the development of effective and efficient forest fire prediction systems.