A Machine Learning-Based Approach to Calibrate Low-Cost Particulate Matter Sensors

• Published in: Brazilian Symposium on Computing System Engineering pp. 1 - 8
• Main Authors: Pastorio, Andre F., Spanhol, Fabio A., Martins, Leila D., de Camargo, Edson T.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 21.11.2022
• Subjects: Air quality; Atmospheric modeling; calibration; Humidity; low-cost sensors; Optical filters; Particle measurements; particulate matter; Sensors; Temperature sensors

Low-cost particulate matter (LC-PM) sensors have been studied around the world as a viable alternative to expensive reference stations for monitoring air quality. However, LC-PM sensors require periodic calibration, since their data are often inaccurate and subject to uncertainty. Sensors calibratio...