A Review on Fire Detection System through Machine Learning

There has been an increased incidences of fire and fire related damages all across the world. There has also been an increase in the number of forest fires across the world. Studies show that the wildfires are becoming increasingly powerful and deadlier in the recent years. The increase in the number of incidences across the world warrants the implementation of an effective fire mitigation strategy to combat such occurrences. The first step for the prevention and reduction of such instances is the detection of fire in a timely and effective manner. Therefore, there is the need for a fire detection system that is highly accurate and can be reliable as a fire detection system. The conventional approaches towards fire detection utilize expensive sensors that are slow to respond and have a large error of detection. This survey paper outlines effective techniques that have been used for the purpose of achieving fire detection. The analysis of the approaches have been effective in the design of our methodology that utilizes the paradigm of Convolutional Neural Networks and Decision Tree. This approach will be elaborated further in the upcoming editions of this research.