Forest Fire Prediction Using Image Processing And Machine Learning

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Mohana Kumar S , Sowmya B J , Priyanka S , Ruchita Sharma , Shivank Tej , Spoorthi Ashok Karani

Abstract

Forest-fires are real threats to human lives, environmental systems and infrastructure. It is predicted that forest fires could destroy half of the world’s forests by the year 2030. The only efficient way to minimize the forest fires damage is to adopt early fire detection mechanisms. Thus, forest-fire detection systems are gaining a lot of attention. Predicting the source and spread of forest fires could have impressive advantages for human wellbeing and life, the economy and the climate. This could assist with recognizing regions with higher danger - for instance, with restricted asset, the specialists could decide to zero in on observing explicit regions. In this study, image processing based has been used due to several reasons such as quick development of digital cameras' technology, the camera can cover huge regions with amazing outcomes, the reaction season of picture handling strategies is superior to that of the current sensor frameworks, and the general expense of the picture preparing frameworks is lower than sensor frameworks.

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