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Open AccessArticle

Distributed Multi-Scale Calibration of Low-Cost Ozone Sensors in Wireless Sensor Networks

1
Universitat Politecnica de Catalunya (UPC), UPC Campus Nord, 08034 Barcelona, Spain
2
Institute of Environmental Assessment and Water Research, Spanish National Research Council (IDAEA-CSIC), 08034 Barcelona, Spain
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(11), 2503; https://doi.org/10.3390/s19112503
Received: 12 April 2019 / Revised: 24 May 2019 / Accepted: 29 May 2019 / Published: 31 May 2019
(This article belongs to the Section Sensor Networks)
New advances in sensor technologies and communications in wireless sensor networks have favored the introduction of low-cost sensors for monitoring air quality applications. In this article, we present the results of the European project H2020 CAPTOR, where three testbeds with sensors were deployed to capture tropospheric ozone concentrations. One of the biggest challenges was the calibration of the sensors, as the manufacturer provides them without calibrating. Throughout the paper, we show how short-term calibration using multiple linear regression produces good calibrated data, but instead produces biases in the calculated long-term concentrations. To mitigate the bias, we propose a linear correction based on Kriging estimation of the mean and standard deviation of the long-term ozone concentrations, thus correcting the bias presented by the sensors. View Full-Text
Keywords: wireless sensor networks; low-cost sensors; calibration; error estimation; air pollution sensors wireless sensor networks; low-cost sensors; calibration; error estimation; air pollution sensors
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Barcelo-Ordinas, J.M.; Ferrer-Cid, P.; Garcia-Vidal, J.; Ripoll, A.; Viana, M. Distributed Multi-Scale Calibration of Low-Cost Ozone Sensors in Wireless Sensor Networks. Sensors 2019, 19, 2503.

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