Abstract
Performing pollution measurements is a difficult and costly process. On the one hand, specialized laboratories are needed to calibrate sensors and adjust their readings to units that indicate the level of contaminants in the environment, and, on the other hand, measurements depend on the type of sensor. High-end sensors are very accurate but quite expensive, while low-end sensors are more affordable but have less precision and introduce considerable oscillations between readings. This paper presents a methodology to measure ozone pollution data with low-end mobile sensors, focusing on sensor calibration through historical data and the existing environmental monitoring infrastructure. The proposed methodology is developed in three phases: (i) reduction of data measurements variability, (ii) calculation of calibration equations, (iii) and analysis of the spatial-temporal behavior to reduce variations in time produced when data are captured using mobile sensors.
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Acknowledgement
This work was partially supported by the “Programa Estatal de Investigación, Desarrollo e Innovación Orientada a Retos de la Sociedad, Proyecto I+D+I TEC2014-52690-R”.
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© 2016 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Alvear, Ó., Tavares Calafate, C., Cano, JC., Manzoni, P. (2016). Calibrating Low-End Sensors for Ozone Monitoring. In: Mandler, B., et al. Internet of Things. IoT Infrastructures. IoT360 2015. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 169. Springer, Cham. https://doi.org/10.1007/978-3-319-47063-4_24
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DOI: https://doi.org/10.1007/978-3-319-47063-4_24
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