Risk Streamlit is a solar maintenance monitoring system built on a rule-based logic approach and hosted with Streamlit.
Its main purpose is to classify the operational state of a solar system into Normal, Low Risk, High Risk, or Critical, helping operators quickly identify issues and take preventive action.
- Real-time monitoring: Pulls live sensor data via Supabase integration
- Rule-based classification: Transparent logic for risk levels (Normal, Low, High, Critical)
- Interactive dashboards: Streamlit-powered UI for easy visualization and decision-making
- Scalable design: Ready to expand with more sensors or advanced models
- Python for backend logic
- Streamlit for interactive dashboards
- Supabase for real-time data ingestion from sensors
risk_streamlit/
│
├── app.py # Main Streamlit application
├── Risk_classer.py # Rule-based risk classification logic
├── .streamlit/ # Streamlit configuration
├── .devcontainer/ # Development container setup
└── requirements.txt # Python dependencies
You can try the live demo here:
👉 Risk Streamlit App
- Sensors → Supabase (real-time ingestion) → Risk Streamlit → Dashboard visualization
- Add machine learning models for predictive risk assessment
- Expand sensor integration for broader solar system monitoring
- Enhance visual analytics with historical trend tracking
Contributions are welcome!
- Fork the repo
- Create a new branch (
feature/your-feature) - Commit changes
- Open a Pull Request
This project is licensed under the MIT License. See LICENSE for details.