IoT Sensor and Deep Neural Network based Wildfire Prediction System

Forests, one of the most valuable and necessary resources and protect earth's ecological balance, are a natural habitat to animals and forest products are vital in our lives in many direct and indirect ways. But wildfires can cause critical damage to grounds and many other resources like properties, human life, wildlife in superabundant amounts. Wildfires burn acres of land and destroy everything in their paths in mere minutes. Wildfire destroys homes, animals, trees and plants, wildlife as well as vegetation. The effects of wildfires are numerous and wide-ranging. it causes a hugely significant impact on the economy, environment, heritage and social fabric of rural areas. Naturally caused wildfires can be predicted using factors[3] like temperature, humidity, soil moisture, pressure and many more. In this paper, the prediction of forest fires by machine learning using some operational monitoring over a region and encountering changes in climate using different sensors are advocated. The Wildfire Prediction System (WiPreSy) monitors and records changes in climatic parameters and predicts the intensity of forest fire based on real-time data, thus avoiding the massive loss due to forest fires.