Context

AirFloor (originally scoped around Kengeri, a neighborhood in Bangalore, then generalized to all of India) started as a personal flat-buying question: on a multi-storey building, which floor actually has the healthiest air. Street-level fumes and the night inversion layer sit low, but the top floors lose on wind exposure and daily friction, not oxygen. The project turned that question into a public, free tool.

Problem

There was no way to see, for a specific building in a specific place, how air quality changes floor by floor. Generic AQI apps report one number for a whole city or area, not a curve across height, and nothing served this for Indian cities in local languages.

Approach

Combine two live open data sources, real ground elevation from a Copernicus digital terrain model and live air quality from the Copernicus CAMS service through Open-Meteo, into a per-floor score built on a physics-informed weighting we defined (PM2.5/inversion, street fumes, ventilation, liveability and oxygen). The interface is a two-step hero: pick an area with a hybrid combobox, then set building height with a big highlighted floor field with no default value, so the first real action is deliberate. Results render as animated canvas charts with three views (curve, bars, table), an AQI severity scale bar in the style of aqi.in, and a plain-language household advice engine that reads the live AQI band and writes persona-specific guidance. Every string ships in English, Telugu and Kannada with natural (non-literal) translations, and location is hard-locked to India through a bounding box plus a reverse-geocode country check, because the geocoder alone leaked results from Kathmandu, Dhaka and Colombo. A print stylesheet (not a PDF library) lets people export the whole report, keeping the live charts and local-language text intact.

Outcome

The tool is live at airfloor.netlify.app, open source (MIT for code, CC BY 4.0 for content) at github.com/yashkotha/airfloor, and applied for Netlify’s Open Source hosting plan. It shipped through several rounds of visible self-correction: an early India-wide live AQI map was built, then pulled because it didn’t earn its space next to the per-building tool; the first building/air logo was replaced by a drifting-clouds animation; a first pass at the advice engine broke on an empty state and was hardened with a PM2.5 AQI fallback. Verifiable output only: no user or usage metrics exist for this project.