https://github.com/pavanreddy565/reservoir_intelligence
💧 Reservoir Intelligence forecasts water storage & demand using ML 🧠 (LSTMs, GRUs), Plotly 📊, & Supabase 💾. Supports policymaker decisions 🌍. Easy setup, Flask backend, open for contributions! ✨ #WaterManagement #AI
https://github.com/pavanreddy565/reservoir_intelligence
flask machine-learning plotly python pytorch supabase
Last synced: 3 months ago
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💧 Reservoir Intelligence forecasts water storage & demand using ML 🧠 (LSTMs, GRUs), Plotly 📊, & Supabase 💾. Supports policymaker decisions 🌍. Easy setup, Flask backend, open for contributions! ✨ #WaterManagement #AI
- Host: GitHub
- URL: https://github.com/pavanreddy565/reservoir_intelligence
- Owner: pavanreddy565
- License: mit
- Created: 2025-02-26T05:40:43.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-02-26T05:53:21.000Z (over 1 year ago)
- Last Synced: 2025-02-26T06:28:46.334Z (over 1 year ago)
- Topics: flask, machine-learning, plotly, python, pytorch, supabase
- Language: HTML
- Homepage:
- Size: 0 Bytes
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# 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](https://www.python.org/downloads/).
### Steps to Set Up
1. Clone the repository:
```bash
git clone https://github.com/yourusername/reservoir-intelligence.git
```
2. Navigate to the project directory:
```bash
cd reservoir-intelligence
```
3. Create and activate a virtual environment:
```bash
pip install virtualenv
python -m venv myVenv
.\myVenv\Scripts\activate
```
4. Install dependencies:
```bash
pip install -r requirements.txt
```
5. Run the dashboard:
Open a new terminal, navigate to the project directory, and execute:
```bash
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](LICENSE) file for more details.