Spent our first session setting up the entire architecture for Climate Shield.
Instead of just building a static map, we built a live data bridge.
We successfully connected a Python backend engine using FastAPI to NASA’s live EONET satellite network, pulling in over 6,000 active global wildfires!
To bypass cloud firewalls and handle messy data, we engineered a custom data-cleaning filter.
Then, we linked the coordinates to the OpenWeatherMap API to calculate real-time wind speed and direction.
Right now, the frontend map isn’t just displaying fire locations—it is actively rendering dynamic Risk Vectors (yellow trajectory lines) showing exactly where the wind is driving the fire spread.
Next up: building the AI hazard scoring system!