TranscendFlow: Smart City Traffic Patterns 🚗

This Streamlit application, TranscendFlow, analyzes smart city traffic patterns using machine learning techniques.

Overview ℹ️

TranscendFlow provides insights into traffic patterns at different junctions in a smart city. It utilizes Linear Regression to predict future traffic based on historical data and adjusts predictions for special occasions, weekends, and holidays.

Usage 🚀

1. Open the TranscendFlow application.
2. Select a junction from the sidebar options.
3. View actual traffic data and predicted traffic data for the selected junction.
4. Check the adjusted test predictions for the selected junction.

Working Video 🎥

Watch the working video here.

Files 📁

• train_aWnotuB.csv: Training dataset.
• test_BdBKkAj.csv: Test dataset.

Implementation Details 🛠️

Libraries Used 📚

• Pandas: For data manipulation.
• Streamlit: For building interactive web applications.
• Matplotlib: For data visualization.
• Scikit-learn: For machine learning models.

Features

• Load and preprocess the training and test datasets.
• Adjust predictions based on special occasions, weekends, and holidays.
• Predict future traffic using Linear Regression.
• Display actual and predicted traffic data for the selected junction.

Contribution 🤝

Contributions are welcome! If you have any suggestions or find any issues, feel free to contribute. You can open an issue or create a pull request.

License 📝

This project is licensed under the MIT License.