Case study
AURA / hardware
ESP32 USB serial (or mock CSV) → Flask → SQLite. Live-only Sensor Lab ingest for temp, humidity, and IR.
Local lab- Python
- Flask
- pyserial
- SQLite
- scikit-learn
- Chart.js
- ESP32
What exists
- AURA | Smart Irrigation System & ML Forecaster: ESP32 USB serial (or mock CSV) → Flask → SQLite
- Estimates pump water use; next-calendar-day liters with scikit-learn Linear Regression (naive fallback if fewer than 3 days)
- Glassmorphism dashboard, Chart.js, light/dark, CSV export
- Settings: flow rate, soil threshold, daily budget alert
- Binds 127.0.0.1:5000
- Sensor Lab: live-only ESP32 ingest (no mock): temp, humidity, IR yes/no
- Dashboard on 127.0.0.1:5001; disconnect clears/freezes live charts
Architecture
Animated diagram of the system from documented facts.
Stack
- Python
- Flask
- pyserial
- SQLite
- scikit-learn
- Chart.js
- ESP32
Status
Local lab
Local lab systems. Strong hardware+software story. Not a SaaS farm product.