EcoNaut
Forecasting harmful algal blooms in the Pacific, in near real time.
Solo build · On-going
Data fused
Satellite + Ocean Buoys
Forecast horizon
7 days
Pacific regions
Live dashboard
Problem
My inspiration began while surfing - the water didn't smell right. I later found out it was due to high levels of bacteria from an algal bloom. These blooms can harm marine ecosystems, so I wanted to build something that could help people and wildlife avoid them.
Approach
Ingested NASA MODIS ocean-color imagery and NOAA buoy telemetry into PostgreSQL, engineered lag and rolling-window features, trained an XGBoost classifier for bloom events and a Prophet model for SST drift, and served it behind a Flask API feeding a React dashboard.
In short
Full-stack app for Pacific ocean anomaly detection. Ingests NASA MODIS and NOAA buoys, engineers time series features, and uses XGBoost for algal bloom forecasts. Flask backend, PostgreSQL, React dashboard.
Stack
- TypeScript
- React
- Python
- Flask
- PostgreSQL
- XGBoost
- Prophet
- Time-Series Forecasting