Tools for air quality data analysis
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Updated
May 24, 2024 - R
Tools for air quality data analysis
An open-source Python package to easily obtain real-time, historical, or forecasted air quality data for anywhere in the world. Reliable, accurate and simple.
Python package to get and transform PurpleAir data
Achoo uses a Raspberry Pi to predict if my son will need his inhaler on any given day using weather, pollen, and air quality data. If the prediction for a given day is above a specified threshold, the Pi will email his school nurse, and myself, notifying her that he may need preemptive treatment. Community-sourced health monitoring!
A set of analysis tools for air quality data from various sources
Field observation quick analysis toolkit
Outdoor Air Quality Statistics India - Unofficial CPCB API
The sensors.AFRICA API receiving, storing, and processing data received from sensors across the continentent. Accessible at https://api.sensors.africa/
Data fusion for air quality data
A telegram bot that sends you air quality data of locations or addresses
The web interface and JSON api for the ConnectedHumber Air Quality Monitoring Project.
aqi-react is a project created to know the Air Quality Index of various parts of the world. How about a ⭐️?
R utility functions for Arpa ER air quality data
The sensors.AFRICA air quality API receiving, storing, and processing data received from sensors across the continentent. Accessible at https://api.aq.sensors.africa/
💧 Get Air Quality Data of any place in a very simplified interface
Acquire and process live and historical air quality data without efforts. Filter by station-id, sensor-id and sensor-type, apply reverse geocoding, store into time-series and RDBMS databases, publish to MQTT, output as JSON, or visualize in Grafana. Data sources: Sensor.Community (luftdaten.info), IRCELINE, and OpenAQ.
Análisis de la calidad del aire en Guadalajara
A Web widget to visually show real-time air quality data.
The sensors.AFRICA map showing data from air quality sensors deployed across the continent. Accessible at https://map.aq.sensors.africa/
This is the qualR package, it will help you bring São Paulo and Rio de Janeiro air quality data to your R session 🇧🇷.
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