About 

This is the TreeHacks 2019 project by Michelle Xu, Kevin Chen, Hannah Zhang, and Jason Zhu! Our web app gives people the power to predict the presence of wildfires in an area.

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Earlier this year, California suffered from one of the most devastating wildfire seasons, resulting in billions of dollars in damages as well as dozens of lives being lost. Our goal is to better prepare people living in wildfire-prone regions to disasters like this. We want to inform people about how easily a wildfire can occur in a given area with the right conditions and how to react to a wildfire in the case that it happens.

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Our primary algorithm runs on a naive logistic regression model, powered by python. It takes in three parameters from a given region: the average humidity, the wind average wind speed, and the average temperature over the past month and outputs whether that region is at risk of a wildfire. If so, our web app will direct you to a list of resources that help you determine the best way to prepare for the wildfire, or it will simply inform you that you are not at risk. 

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This project was developed in the course of one weekend at TreeHacks 2019 at Stanford University, so the algorithm is in its beta stages still. We hope to continually improve our algorithm and web application to help people better understand the implications of wildfire season.