Xtinguish

Wildfire Hotspots
Historical analysis
AI chat to help locate wildfires
Fire Alert overview

Inspiration

Wildfires have become more frequent and intense over the years causing massive damages to ecosystems, property and peoples lives. The inspiration of this application was to make a faster, smarter and more efficient way to wildfire responses. Xtinguish was built to optimize firefighter resources and predict zones at high risks for wildfires, using AI. the goal of this project was to help decision makers with real time data and predictive analytics to minimize the impacts of wildfires.

What it does

The app has three different pages that show the user different telemetry about wildfires. The deployment page shows how many resources need to be sent to a wildfire, the predictor page shows when future wildfires will happen and the live tracker, tracks current wildfires.

How we built it

The app was built using Docker which is the container for the app. The app is split into 4 sections, frontend, backend, ML service and MongoDB database. The backend has 3 section, which is the model , the route and the server. The model models the data object, the route controls the API data flow, and the server hosts the server. The ML service is a python file that contains a python file that runs the script for our AI functionalities. And MongoDBB stores the data for forecasted environmental and historical values for wildfires.