Our team's ICHack 2026 Code!
After a sleepless night, multiple Claude sessions, and 3.14 mental breakdowns, we delivered a project!
Wildfires are bad. They destroy homes and habitats, pollute the air, harm people’s health, cost a lot of money, and release carbon that worsens climate change. What if we could create something that not only predicts the spread of wildfire events, but also predicts how mitigation strategies would help improve the safety of the community?
That's where we come in.
We created mathematical models to predict wildfire spread based on historical data, using statistical techniques such as Monte Carlo and Percolation models. These allow us to replicate the spread of fires in our targeted area, California.
It doesn't stop there! Using our models, we can test out mitigation strategies such as clearing tree lines and retardant areas, and evaluate their effect as a deterrent for spread.
Checkout the rest of our details on Devpost: click moi!
Terminal 1:
cd backend
pixi run runTerminal 2:
cd frontend
npm i
npm run dev