{"id":25813271,"url":"https://github.com/pavanreddy565/reservoir_intelligence","last_synced_at":"2026-04-06T21:31:50.723Z","repository":{"id":279549386,"uuid":"939174951","full_name":"pavanreddy565/Reservoir_intelligence","owner":"pavanreddy565","description":"💧 Reservoir Intelligence forecasts water storage \u0026 demand using ML 🧠 (LSTMs, GRUs), Plotly 📊, \u0026 Supabase 💾. Supports policymaker decisions 🌍. 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It integrates historical water usage, climate projections, and external factors to provide actionable insights.\n\n## Features\n\n- **Dashboard Visualization**: Displays real-time reservoir levels and trends using Plotly for interactive plots.\n- **Forecasting Models**: Predicts future **storage levels** and **outflow rates** using deep learning models like **LSTMs, GRUs, and Bidirectional GRUs**.\n- **Supply-Demand Estimation**: Analyzes whether the water supply meets the demand based on historical and forecasted data.\n- **Comparative Analysis**: Evaluates traditional models (ARIMA, SARIMA) against neural network-based approaches.\n- **Decision Support**: Provides insights for policymakers to optimize **water management strategies** and **plan infrastructure**.\n\n## Installation \u0026 Usage\n\n### Prerequisites\nEnsure you have Python installed on your system. If not, download it from [python.org](https://www.python.org/downloads/).\n\n### Steps to Set Up\n\n1. Clone the repository:\n   ```bash\n   git clone https://github.com/yourusername/reservoir-intelligence.git\n   ```\n\n2. Navigate to the project directory:\n   ```bash\n   cd reservoir-intelligence\n   ```\n\n3. Create and activate a virtual environment:\n   ```bash\n   pip install virtualenv\n   python -m venv myVenv\n   .\\myVenv\\Scripts\\activate\n   ```\n\n4. Install dependencies:\n   ```bash\n   pip install -r requirements.txt\n   ```\n\n5. Run the dashboard:\n   Open a new terminal, navigate to the project directory, and execute:\n   ```bash\n   python app.py\n   ```\n\n6. Access the dashboard by navigating to `http://127.0.0.1:5500/` in your web browser.\n\n### Notes\n- The system uses **Supabase** for data storage, ensuring seamless integration of real-time data.\n- Interactive visualizations are powered by **Plotly**.\n\n## Technologies Used\n\n- **Python, Flask** – Backend \u0026 API handling\n- **Plotly** – Data visualization\n- **PyTorch** – Deep learning models\n- **Pandas, NumPy** – Data processing\n- **Supabase** – Data storage and management\n\n## Contribution\n\nContributions are welcome! Feel free to submit issues or pull requests. Please ensure your contributions align with the project's goals and coding standards.\n\n## License\n\nThis project is licensed under the MIT License. See the [LICENSE](LICENSE) file for more details.\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpavanreddy565%2Freservoir_intelligence","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpavanreddy565%2Freservoir_intelligence","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpavanreddy565%2Freservoir_intelligence/lists"}