CleanSky — Making Air Quality Understandable: Technical Case Study
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| Format: | Recurso digital |
| Langue: | anglais |
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Zenodo
2026
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| _version_ | 1866901956085153792 |
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| author | Bobojonov, Sherzod |
| author_facet | Bobojonov, Sherzod |
| contents | <p>CleanSky is a local full-stack prototype that helps users understand air quality in a practical, map-based format. The interface is designed for quick interpretation: users click a location on an interactive map and immediately receive pollutant values (PM2.5, PM10, NO₂), a simplified risk indicator (not an official AQI), short recommendations, and a weather/forecast view.</p> <p>The backend is implemented in Python (FastAPI) and aggregates open data from Open-Meteo APIs. The frontend is implemented in JavaScript using Leaflet for map interaction and dynamic UI updates, including reverse geocoding to show human-readable place names. The system was built as an admission portfolio artifact to demonstrate end-to-end engineering: API integration, frontend–backend separation, error handling, and user-focused presentation.</p> <p>Limitations: This work is an early-stage prototype (alpha). The risk indicator is a transparent heuristic and does not claim regulatory or medical accuracy. External data availability may vary by location and time. The project is currently intended for local execution as described in the repository documentation.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18524948 |
| institution | Zenodo |
| language | eng |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | CleanSky — Making Air Quality Understandable: Technical Case Study Bobojonov, Sherzod air quality, Open-Meteo, FastAPI, Leaflet, web mapping, full-stack, JavaScript, Python, Uzbekistan, smart city, environmental informatics, public awareness <p>CleanSky is a local full-stack prototype that helps users understand air quality in a practical, map-based format. The interface is designed for quick interpretation: users click a location on an interactive map and immediately receive pollutant values (PM2.5, PM10, NO₂), a simplified risk indicator (not an official AQI), short recommendations, and a weather/forecast view.</p> <p>The backend is implemented in Python (FastAPI) and aggregates open data from Open-Meteo APIs. The frontend is implemented in JavaScript using Leaflet for map interaction and dynamic UI updates, including reverse geocoding to show human-readable place names. The system was built as an admission portfolio artifact to demonstrate end-to-end engineering: API integration, frontend–backend separation, error handling, and user-focused presentation.</p> <p>Limitations: This work is an early-stage prototype (alpha). The risk indicator is a transparent heuristic and does not claim regulatory or medical accuracy. External data availability may vary by location and time. The project is currently intended for local execution as described in the repository documentation.</p> |
| title | CleanSky — Making Air Quality Understandable: Technical Case Study |
| topic | air quality, Open-Meteo, FastAPI, Leaflet, web mapping, full-stack, JavaScript, Python, Uzbekistan, smart city, environmental informatics, public awareness |
| url | https://doi.org/10.5281/zenodo.18524948 |