Hall of Works The Trial , Case study
Ember Sentinel : Real-time Forest Fire Detection AI
A Random Forest model embedded with Arduino hardware that predicts forest fire risk at the edge from live temperature, humidity and smoke sensors.
- Python
- Scikit-learn
- Random Forest
- Arduino
- PySerial
- C/C++
- Sensors
The Foe , The problem
Forest fires spread fastest in the first minutes, often far from any connectivity.
The Arms , Approach and stack
- Random Forest model trained on a curated tropical forest fire dataset.
- Arduino microcontroller reading temperature, humidity and smoke sensors.
- PySerial bridge feeding live readings to the model for edge predictions.
