Airly has been nominated for the 2026 World AI Awards in the Air Quality Monitoring category, recognising the clean-tech company’s work turning pollution measurements into information that cities, businesses and public institutions can actually use.
Air pollution is an unusually local problem. A monitoring station several kilometres away can describe conditions across a wider area, but it may miss what is happening beside a congested junction, school, construction site or industrial facility.
Airly has built its technology around filling those gaps.
Its system combines compact air-quality sensors with a data platform, API and public-facing tools. Instead of simply collecting pollution readings, the company is trying to make those measurements easier to analyse, compare and act on.
The World AI Awards recognises organisations, individuals, products and technologies contributing to the development and practical application of artificial intelligence across industries.
Air pollution changes street by street
Airly’s starting point is measurement.
The company’s monitoring network covers more than 13,000 data points across over 50 countries, according to Airly. Its technology is used by local authorities, companies, schools and other organisations looking for more granular information about pollution in the places where people actually live and work.
Its Airly Pure sensor measures particulate matter including PM1, PM2.5 and PM10, while the Airly Aura adds configurable gas monitoring for pollutants including nitrogen dioxide, ozone, carbon monoxide and sulphur dioxide. Both products are designed for outdoor, hyperlocal monitoring and can feed measurements directly into Airly’s software environment.
That matters because pollution rarely behaves neatly across an entire city.
Traffic, weather, heating, construction and industrial activity can create pockets of poor air quality that broader monitoring networks struggle to capture. A denser network gives authorities another layer of evidence when deciding where a problem exists and whether an intervention is working.
Birmingham turns local measurements into decisions
There is already a practical example in Birmingham.
Birmingham City Council deployed Airly sensors to build a denser picture of pollution across the UK city. The network continuously measures pollutants including PM2.5, PM10, nitrogen dioxide and ozone, with the information fed into visualisation and analytical tools.
Airly says the project helped the council identify pollution hotspots, examine trends and support evaluation around measures including Birmingham’s Clean Air Zone. Residents could also access local information rather than relying solely on city-wide averages.
Another UK partnership shows how the hardware is spreading beyond individual municipal projects. Airly reports that environmental monitoring specialist AcSoft has deployed more than 200 Airly sensors across the UK, integrating their measurements into its SvanNET monitoring platform.
This is where Airly’s proposition becomes more interesting than another environmental sensor. The value sits in what happens after the measurement arrives.
Thousands of measurements become something people can use
The Airly Data Platform combines measurements from Airly networks with official and third-party monitoring sources.
Users can inspect real-time conditions, compare locations, study historical trends, generate reports and configure alerts when pollution thresholds are exceeded. The system is aimed at turning streams of environmental readings into something understandable enough for city officials, sustainability teams and other decision-makers to use without manually processing raw sensor feeds.
Developers can take the data elsewhere.
Airly says its API provides access to more than 13,000 data points and is used by more than 3,000 organisations, generating over seven million data calls each day. Available information includes particulate matter, gases and weather conditions, allowing air-quality information to be incorporated into city dashboards, GIS systems, applications and other digital services.
There is an important limit to the AI story
Airly describes AI-powered analytics as part of its wider technology offering, but there is an important distinction around how the company handles core air-quality measurements.
Its current quality documentation states that Airly does not use air-quality modelling or machine-learning techniques to predict air-quality levels, pointing to concerns around traceability, transparency and robustness.
Instead, Airly recommends co-locating sensors with authorised reference stations where possible so readings can be calibrated against local conditions.
It is a useful distinction.
AI can help environmental organisations process information and identify patterns, but pollution measurements still need a defensible relationship with what is physically happening in the air. For regulators, municipalities and businesses making decisions from that information, knowing where measured data ends and algorithmic inference begins matters.
Graham Cooke, President of the World AI Awards, said:
“Airly’s nomination highlights an important side of environmental technology: making complex air-quality information useful at the local level.
“By combining hyperlocal monitoring with data analytics and digital tools, Airly is showing how technology can give cities, organisations and communities a clearer picture of the pollution around them. That creates opportunities for better-informed decisions while keeping reliable measurement at the centre of the process. We congratulate Airly on its 2026 World AI Awards nomination in Air Quality Monitoring.”
Airly joins organisations, researchers, entrepreneurs and technology developers being recognised through the 2026 World AI Awards.
The programme recognises organisations, individuals and technologies contributing to the development and application of artificial intelligence across industries.
Airly’s nomination in Air Quality Monitoring brings that conversation down to street level. Sensors cannot clean the air by themselves. Neither can a dashboard. What they can do is expose differences that were previously difficult to see — where pollution concentrates, when conditions deteriorate and whether an intervention appears to be making a measurable difference.
That turns air-quality monitoring from an occasional reading into something much closer to continuous environmental intelligence.
Learn more about Airly and its air-quality monitoring technology at airly.org.
Discover the World AI Awards 2026, explore the nominees and learn more about the awards at worldawards.ai.
