🌎 Airon — Real-Time Global AQI Predictor

Airon is a full-stack machine learning web app that predicts the Air Quality Index (AQI) of any country in real time. It fetches air pollutant data using OpenWeather APIs and makes predictions using a trained Random Forest model.

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• See the video demo here: https://www.youtube.com/watch?v=WSw6QEVrFaE
• See the live demo here: https://farrfoxr.github.io/Airon/

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📸 Demo

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🚀 Features

• Real-time AQI prediction from global cities
• Interactive UI with React
• Integration with OpenWeather Air Quality & Geocoding API
• Model built using scikit-learn (Random Forest)
• End-to-end full-stack: data ingestion → prediction → visualization

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🛠 Tech Stack

• Frontend: React, TypeScript, HTML/CSS
• Backend: Flask, Python, Postman
• ML Libraries: scikit-learn, pandas, matplotlib
• APIs: OpenWeather (Air Quality, Geocoding)

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🧪 Getting Started

1. Clone this repository
2. Install backend dependencies with pip install -r requirements.txt
3. Set up your OpenWeather API key in .env
4. Run backend: flask run
5. Run frontend: npm start (from React folder)

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📚 What I Learned

This project was a personal breakthrough. I transitioned from basic ML scripting to building a real-world full-stack application. I learned:

• How to connect APIs to ML workflows
• Fundamentals of REST APIs and using Flask for backend
• Frontend development with React and TypeScript
• How to structure a project from prototype to production

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📎 License

MIT – feel free to use and build upon this!