Estudo da influência dos elementos climáticos em sistemas de baixo custo para monitoramento da qualidade do ar

The atmospheric pollution alerts to the need to promote thedevelopment of air quality monitoring systems. Equipment withlow implementation cost and energy consumption are highlightedfor highly scalable applications. The datasets generated by thesensors feed machine learning algorithms for the weatherconditions analysis in urban centers. However, sensor technologyused in these systems tends to be less accurate than complexequipment, resulting in a strong correlation between the collecteddata and the climatic elements variation. This paper studies theinfluence of temperature and relative humidity in low cost airquality monitoring systems. This knowledge can generate newapproaches to the monitored metrics conditioning and increasethe robustness of the low cost systems.