🌍 AirSense AI – Air Quality Intelligence Platform

Your Intelligent Air Quality Analysis & Prediction System

AI-powered analysis of global air quality data with predictions, clustering & anomaly detection

Check out the application: 👉 Launch AirSense AI

🌟 About

AirSense AI is a comprehensive machine learning platform that analyzes global air quality trends using WHO datasets. It empowers researchers, policymakers, and citizens with actionable insights into air pollution patterns worldwide.

What It Offers

• Air Quality Prediction – Forecast pollution levels using ML models
• City/Country Clustering – Group regions by pollution patterns
• Risk Classification – Categorize severity levels
• Anomaly Detection – Identify unusual pollution hotspots
• Insights – Visualize and explore data dynamically

🚀 Quick Start

🔧 Running Locally

# Clone the repository
git clone https://github.com/Anamikaghosh18/AirSense.git

# Install dependencies
pip install -r requirements.txt

# Run the Streamlit app
streamlit run app.py

🌐 Using the Live Demo

Visit the deployed application: 👉 Launch AirSense AI

📊 Dataset

This project uses the WHO Air Quality Database, which includes:

• Pollutants, temperature and other metadata
• City and country metadata

🤝 Contributing

Contributions are welcome! If you'd like to improve AirSense:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

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📄 License

This project is licensed under the MIT License – see the LICENSE file for details.

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👩‍💻 Author

Anamika Ghosh

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Built with ❤️ using Data Science + Machine Learning