AirQo
An African network of affordable sensors that measures, complements, and predicts local air pollution using machine learning.
About
AirQo originated at Makerere University in Uganda and builds sensors resistant to heat, dust, and poor connectivity. Measurements are published as open, real-time air quality data for cities, researchers, and residents. A peer-reviewed study in Uganda showed that local sensors and machine learning can provide usable estimates of particulate matter at urban scale. The data makes pollution visible, but does not by itself prove that policy has cleaned the air.
AI factor
Models calibrate cheap sensors against more accurate reference equipment and estimate values at locations and times without direct measurement. This produces a finer-grained picture of PM2.5 pollution with limited hardware.
Sources
Inspiration sourced from AI For Good. Not an Arnaldus customer case.