Inspiration Air pollution is responsible for over 7 million premature deaths annually. Yet most people have no real-time visibility into the air quality of their city. I wanted to build a simple, accessible tool that anyone with a smartphone can use to make informed decisions about outdoor activities.
What I learned This project deepened my understanding of building complete ETL pipelines on the frontend — extracting data from REST APIs, transforming raw JSON into structured format, and loading into localStorage for persistence. I also learned real-time data visualization with Chart.js and efficient geocoding workflows.
How I built it The app fetches live air quality data from OpenWeatherMap API, geocodes city names to coordinates, processes pollutant levels (PM2.5, PM10, NO₂, O₃), and displays a color-coded AQI from 1 (Good) to 5 (Very Poor). All historical data is stored locally with automatic deduplication. The app auto-refreshes every 5 minutes with a countdown timer, and Chart.js renders trend lines of the last 30 readings.
Challenges faced Rate limiting required smart caching strategies. Duplicate entries during refreshes were solved by timestamp-based deduplication. Reverse geocoding for the "Use My Location" feature needed careful error handling for permission denials and API fallbacks.
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