Saaf Hawa - AQI Delhi - Real-time Air Quality Monitoring with AI Insights
Link to open source: https://github.com/mekapilgupta/gdgnoida_albuswand
Link to Live Project: https://saaf-hawa.netlify.app/
🌬️ Saaf Hawa - AI-Powered Real-Time Air Quality Intelligence
For India, In India, By India: Tackling the NCR Air Pollution Crisis
The Challenge We Address
Delhi-NCR faces a severe public health emergency, with AQI reaching hazardous levels of 700+ this November 2025. All 1.4 billion Indians breathe air exceeding WHO safety limits, with 544 million exposed to critically dangerous pollution levels. This isn't just an environmental issue—it's a constitutional right to clean air that demands immediate, intelligent solutions.
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Our Solution
Saaf Hawa empowers citizens with real-time, AI-driven air quality intelligence through an intuitive web platform. We've built a comprehensive dashboard that monitors multiple Delhi-NCR stations, providing live AQI data, pollutant breakdowns (PM2.5, PM10, NO2, SO2), and interactive visualizations.
Why Google Gemini AI? We leverage Google's Gemini model to transform raw AQI numbers into actionable wisdom. Our AI analyzes current pollution levels, weather patterns, and health risks to generate personalized recommendations for different population groups—outdoor workers, children, elderly, and sensitive individuals. It provides context-aware warnings, suggests optimal times for outdoor activities, and explains pollution sources like stubble burning or traffic congestion.
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Future Vision
We're committed to scaling impact through:
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ISRO Satellite Integration: Analyzing OCM-3 aerosol optical depth imagery for real-time smog tracking and pollution plume visualization
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Predictive Analytics: ML models forecasting 24-48 hour AQI trends
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Multi-city Expansion: Extending coverage to all 122 Indian cities exceeding NAAQS standards
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Built with purpose, powered by AI, designed for every Indian who deserves to breathe clean air.
Tech Stack: Svelte 5, Google Gemini AI, OpenRouter API, AQICN Data, OpenLayers Maps
Demo: Loom Video
https://www.loom.com/share/c7ecde3e1f684f7f9cc094da6640d81a
GitHub: https://github.com/mekapilgupta/gdgnoida_albuswand

