Abstract: Forest fires have become one of the most serious issues. Forest fires have a significant influence on ecosystems and have a significant impact on greenhouse gas and aerosol levels in the atmosphere. Wildfires have devastated a large quantity of forest and wildlife as a result of these fires. Forest fires are caused by two major factors: global warming caused by an increase in the average temperature of the earth, and human irresponsibility. Predictions must be made to discover sections of land that have the potential to burn and lead to a large forest fire based on meteorological conditions in order to prevent forest fires. Our suggested system will focus on parameters such as temperature, humidity, and other variables that contribute to wildfires. There are a variety of fire detection algorithms available, each with its own approach to the problem.
Keywords: Training, satellites, wind speed, forestry, predictive models, decision trees,wind forecasting.
Cite:
Kavitha. R, Iraniyan Pandian, Kumaran. M, "PREDICTING WILDFIRES USING MACHINE LEARNING TECHNIQUES", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 13, no. 2, 2024, Crossref https://doi.org/10.17148/IJARCCE.2024.13240.
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DOI:
10.17148/IJARCCE.2024.13240
