Reservoir Intelligence

Reservoir Intelligence is a machine learning-powered system designed to forecast water storage levels and assess supply-demand balance for effective water resource management. It integrates historical water usage, climate projections, and external factors to provide actionable insights.

Features

• Dashboard Visualization: Displays real-time reservoir levels and trends using Plotly for interactive plots.
• Forecasting Models: Predicts future storage levels and outflow rates using deep learning models like LSTMs, GRUs, and Bidirectional GRUs.
• Supply-Demand Estimation: Analyzes whether the water supply meets the demand based on historical and forecasted data.
• Comparative Analysis: Evaluates traditional models (ARIMA, SARIMA) against neural network-based approaches.
• Decision Support: Provides insights for policymakers to optimize water management strategies and plan infrastructure.

Installation & Usage

Prerequisites

Ensure you have Python installed on your system. If not, download it from python.org.

Steps to Set Up

1. Clone the repository:

   git clone https://github.com/yourusername/reservoir-intelligence.git

2. Navigate to the project directory:

   cd reservoir-intelligence

3. Create and activate a virtual environment:

   pip install virtualenv
   python -m venv myVenv
   .\myVenv\Scripts\activate

4. Install dependencies:

   pip install -r requirements.txt

5. Run the dashboard: Open a new terminal, navigate to the project directory, and execute:

   python app.py

6. Access the dashboard by navigating to http://127.0.0.1:5500/ in your web browser.

Notes

• The system uses Supabase for data storage, ensuring seamless integration of real-time data.
• Interactive visualizations are powered by Plotly.

Technologies Used

• Python, Flask – Backend & API handling
• Plotly – Data visualization
• PyTorch – Deep learning models
• Pandas, NumPy – Data processing
• Supabase – Data storage and management

Contribution

Contributions are welcome! Feel free to submit issues or pull requests. Please ensure your contributions align with the project's goals and coding standards.

License

This project is licensed under the MIT License. See the LICENSE file for more details.