article · Societal Impacts
AirQo provides an operational model for translating artificial intelligence and digital technology into large-scale societal impact through urban air pollution monitoring and modelling. The initiative developed custom-designed, low-cost air quality monitors based on Internet of Things technology, alongside a methodology for deploying high-resolution, citizen-driven monitoring networks. In addition, the project generated AI-powered digital tools to model and analyse air pollution data for urban residents and municipal leaders, supported by a structured engagement framework connecting these groups. This integrated solution has already been deployed and scaled across multiple cities in Eastern, Western, and Central Africa. Realised impacts span improvements in air quality policy and regulations, heightened public education and awareness, and expanded research into regional air pollution challenges.
Urban air pollution presents substantial health and environmental challenges across rapidly growing cities. By delivering affordable hardware, AI-based data modelling, and community engagement frameworks, this initiative provides actionable environmental intelligence. It enables municipal authorities and local communities to identify pollution trends, enact evidence-based regulatory protections, and foster broader public understanding of regional air quality risks.
The technology suite includes custom low-cost Internet of Things hardware and AI-driven data platforms designed for municipal authorities, urban planners, and civic organisations. Because the tools have already been deployed and scaled across multiple cities in Eastern, Western, and Central Africa, the system represents an applied and field-tested technology ready for wider operational rollout and adoption by environmental monitoring agencies.
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Recent advances in Artificial Intelligence (AI) research have opened up new opportunities for leveraging AI research for societal impacts. AI research offers novel ways of tackling societal problems including environmental, health, and education challenges. Despite the potential, there are limited documented use cases and methodologies for translating AI research to societal impact at a large scale. This paper presents AirQo, an AI and advanced technology-driven use case for urban environmental pollution monitoring and modelling and the resulting societal impacts that have been realised. The research outputs include a set of digital solutions for the environmental air pollution challenges including (1) custom-designed low-cost air quality monitors that are premised on IoT technology (2) a methodology for deploying a high-resolution and citizen-driven air quality monitoring (3) AI-powered digital tools for air quality information modelling and analysis for citizens and city leaders, and (4) a framework for engagement for citizens and leaders. The AirQo project has been deployed and scaled out in cities in Eastern, Western, and Central African countries. The societal impacts resulting from the implementation of the AirQo research project include policy and regulations, education and awareness, and research around air quality issues.
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DOI: 10.1016/j.socimp.2024.100044
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