About AirQo

Clean air
for all

Who are we?

AirQo was founded in 2015 at Makerere University, to close the gaps in air quality data in Uganda and across Sub-Saharan Africa.

We continuously provide evidence of the magnitude and scale of air pollution by developing and deploying a network of low-cost air quality monitoring devices.

By applying artificial intelligence, we derive insights from the data collected and share in real-time through our data sharing platforms. Ultimately, we work with partners and stakeholders to inform air pollution mitigation actions and raise awareness on its effects.


In May 2019, AirQo, the only project from Africa, received a grant of $1.3m after emerging one of the 20 winners of the Google AI Impact Challenge selected from over 2600 applicants.

This has greatly enabled us to scale up our existing air quality monitoring network whilst using artificial intelligence (Al) to improve forecasting and accuracy of our air quality data.to inform air pollution mitigation actions and raise awareness on its effects.

Google CEO Sundar Pichai examining the AirQo device while Prof. Engineer Bainomugisha, Martin Baale and Paul Green explain how the device is designed to collect air quality data. This was during the AI impact challenge summit that took place in Jan, 2020 in San Francisco, California

Our Work

Building Low-cost Air Quality Monitors

These are locally and uniquely designed to work in settings characterised by extreme weather and environmental conditions such as dust, heat, unreliable power, and intermittent and limited internet connectivity, typical in a sub-Saharan African setting.

Deploying Air Quality Monitors Across Urban Areas

We have deployed our growing network of over 80 devices across Uganda and use the latest cloud-based technology to store, manage and interpret large quantities of air quality data showing both the spatial and temporal behaviour of air pollution.

We also place our devices on motor-cycle taxis locally called 'boda-bodas' to improve our spatial coverage and revolution. 'Boda- bodas' are renowned for being able to go almost anywhere, including along off-road tracks and through informal settlements.

Modelling and Forecasting

One of our key areas of activity is to model air quality using machine learning and artificial intelligence to ensure accuracy of our devices, predict pollution levels in areas where we don't have sensors, make local forecasts and troubleshoot errors.

Access air quality data in locations that matter to you

We have made access to air quality data in Uganda easy and simple through the AirQo app.

Upon download, a user is able access historical, real time and forecast air quality data in preferred locations.

A user can also personalize their experience by saving their interested locations so they can easily view their air quality information.