Prediction and Detection of Forest Fires based on Deep Learning Approach

Authors

  • S. Gayathri
  • P.V. Ajay Karthi
  • Sourav Sunil

DOI:

https://doi.org/10.47750/pnr.2022.13.S03.071

Keywords:

Forest fires, CNN, Prediction, Detection, Deep Learning.

Abstract

Forest fires are one of the crucial disrupting impact parts inside the overall forest climate, and it causes various levels of adverse consequences on the natural climate, resources, human prosperity, economy, etc.. Climatic changes impact are a few of the results of such pulverization. Generally, forest fires happen due to human exercises. In order to control the annihilation caused by forest fires, we try to identify forest fires at their beginning so that it does not spread. In this paper we have proposed a method, using image processing module and grey scaling for detecting of forest fires using deep learning based algorithms, CNN. After the fire is being detected, an alert is sent to control team of the forest along with location. We have also integrated Google’s Firebase for sending alerts through notifications of mobile or iot devices. This paper principally engaged concerning brief prologue to the backwoods fire, related work about different strategies and frameworks in timberland fires, conversation on computerized reasoning and AI calculations and followed by forecast and location frameworks are audited.

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Published

2022-09-22

Issue

Section

Articles

How to Cite

Prediction and Detection of Forest Fires based on Deep Learning Approach. (2022). Journal of Pharmaceutical Negative Results, 429-433. https://doi.org/10.47750/pnr.2022.13.S03.071