Forest Fire Detection and Acoustic Based Fire Extinguisher

Abstract

Forest fire is an important issue due to global warming now-a- days. Forest fire causes tragic loss of lives. Primitives’ tribeslosts the livelihood. Modern technologies based on sensors are developed to sense the fire but it is impossible for large acres of forest. In this paper, detection of fire using machine learning and effective extinguishing of fire is based on acoustic method. This approach can detect fire at early stage using KNN algorithm by image processing. There is no assumption of data, KNN algorithm is simple and easy to understand and used for classification and regression. Forest fire detection are difficult to recognize earlier and suppression methods are limited for vast areas. The problems in using sensors are limited to temperature range, cross sensitivity of other gases. This paper is based on artificial intelligence in an application of machine learning in which the features and parameters are trained and tested. Acoustic based extinguishing doesn’t need any maintenance and more resources.  By using the proposed techniques environment disaster is controlled, economical and physical loss of living being were preserved. KNN algorithm is the easiest algorithm used in machine learning for the purpose of classifying and regressing the images.