TY - GEN
T1 - Calibrating low-end sensors for ozone monitoring
AU - Alvear, Óscar
AU - Calafate, Carlos Tavares
AU - Cano, Juan Carlos
AU - Manzoni, Pietro
N1 - Publisher Copyright:
© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2016.
PY - 2016
Y1 - 2016
N2 - 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 lowend 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.
AB - 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 lowend 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.
KW - Low-end sensor
KW - Ozone sensing
KW - Sensor calibration
UR - https://www.scopus.com/pages/publications/85000785987
U2 - 10.1007/978-3-319-47063-4_24
DO - 10.1007/978-3-319-47063-4_24
M3 - Contribución a la conferencia
AN - SCOPUS:85000785987
SN - 9783319470627
T3 - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
SP - 251
EP - 256
BT - Internet of Things
A2 - Campista, Miguel Elias Mitre
A2 - Somov, Andrey
A2 - Mandler, Benny
A2 - Chaouchi, Hakima
A2 - Fazio, Maria
A2 - Caganova, Dagmar
A2 - Giordano, Stefano
A2 - Marquez-Barja, Johann
A2 - Zeadally, Sherali
A2 - Badra, Mohamad
A2 - Vieriu, Radu-Laurentiu
PB - Springer Verlag
T2 - 2nd International Summit on Internet of Things, IoT 360° 2015
Y2 - 27 October 2015 through 29 October 2015
ER -