Optimal data framework for large-scale application of low-cost sensor networks in African cities

Many cities in Low and Middle Income Countries (LMICs), particularly in Africa lack access to timely data from continuous networks due to the prohibitive costs of setting up conventional networks. Low-cost sensors (LCS) costing less than $2,000 have the potential to close the data gaps in data-hungry cities because of the advances in sensing technology, computational capability and affordability. Application of LCS has gained traction over the years, increasingly recognised by regulatory and international agencies including the World Meteorological Organisation, US EPA, and the recent UNEA-6/10 resolution on regional cooperation for improved air quality globally recognises the need to leverage LCS and digital platforms. However, there are contextual bottlenecks including data reliability and availability, limited internet and electricity, and local capacity for network management that hinder successful deployments of large-scale networks. These challenges are intricately linked to local environmental conditions and logistical circumstances in African settings. The current work based on AirQo’s experience across Africa seeks to unlock the barriers to the adoption of low-cost sensors for continuous monitoring through contextualization, firstly, by untangling the requirements for custom-sensor applications in an African context that transcends beyond the choice of technology. We demonstrate from ongoing case studies in major African cities including Kampala, Nairobi, Kisumu, Yaounde, and Lagos, that achieving a robust LCS network requires integration of four key pillars; (i) custom technology for autonomous portable air quality sensors, (ii) decentralised sensing network (iii) data management platform and (iv) community ownership. The current work advances the case for replicating real-life case studies across diverse settings in different data-hungry cities across Africa.