Gaussian Process Models for Low Cost Air Quality Monitoring
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Date
2021
Journal Title
Journal ISSN
Volume Title
Publisher
University of Makerere
Abstract
Air pollution contributes to over three million deaths [1] each year. Kampala
has one of the highest concentrations of fine particulate matter (PM
2.5) of any African city [2]. Unfortunately, with the exception of the US
Embassy, there is no programme for monitoring air pollution in the city
due to the high cost of the equipment required. Hence we know little
about its distribution or extent. Lower cost devices do exist, but these do
not, on their own, provide the accuracy required for decision makers. We
propose that using a coregionalised Gaussian process to combine the low
cost sensors with the embassy’s high quality results provides sufficiently
accurate estimates of pollution across the city.
Description
Keywords
Gaussian Process Models, Low Cost, Air Quality Monitoring
Citation
Smith, M. T., Ssematimba, J., Alvarez, M. A., & Bainomugisha, E. Gaussian Process Models for Low Cost Air Quality Monitoring.