BreatheEasy – AI-Powered Air Quality Prediction | CBSE Class 12 Project

BreatheEasy is our CBSE Class 12 Informatics Practices project focused on predicting Air Quality Index (AQI) using Machine Learning.
Our system provides real-time AQI, pollutant breakdowns, and a 3-day forecast along with CPCB-aligned health advisories to help users understand and respond to air pollution effectively.

This project was developed by:
• Chirag P Patil – AI Model & Backend Developer
• Kimaya Anand – UX & Data Support
• Aarav Vaidya – Data & Research Lead
Delhi Public School, Bangalore South

🔹 What BreatheEasy Does:
• Real-time AQI display for major Indian cities
• Pollutant-specific risk analysis
• 3-day AQI forecast using LightGBM
• Health advisories aligned with CPCB guidelines
• Simple, clean dashboard interface
• Historical AQI trends and visualizations

🔹 Technologies Used:
• LightGBM (Machine Learning Model)
• Python, Pandas, NumPy
• Dash / Plotly for the frontend
• AQICN API & WeatherAPI for real-time data
• DaVinci Resolve for editing the project video

🔹 Why We Built This:

Air pollution is a major challenge in urban India, and most people struggle to interpret AQI numbers or understand the risks. BreatheEasy makes air quality simple, understandable, and actionable so users can make informed daily decisions.

Thank you for watching our project!
If you found this helpful, feel free to like and share.

Link to the Project GitHub Repository: https://github.com/cp099/BreatheEasy.git

Видео BreatheEasy – AI-Powered Air Quality Prediction | CBSE Class 12 Project канала Chirag P Patil