UrbanFlowOptimization aims to optimize urban traffic systems through advanced data analytics and algorithmic modeling. The project focuses on minimizing congestion, improving travel times, and supporting smart city infrastructure by analyzing real-time and historical mobility data.
- Real-time traffic data processing
- Predictive congestion modeling
- Route and flow optimization algorithms
- Visualization dashboard for decision support
- Scalable and modular architecture
- Languages: Python
- Libraries/Frameworks: Pandas, NumPy, scikit-learn, Matplotlib
- Tools: Jupyter Notebook, Git
- Data Sources: Simulated or real urban traffic datasets
- Python 3.8+
- pip
- Virtualenv (optional but recommended)
git clone https://github.com/Sadiq0909/UrbanFlowOptimization.git
cd UrbanFlowOptimization
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
pip install -r requirements.txt