Agile Climate-Sensor Design and Calibration Algorithms Using Machine Learning: Experiments From Cape Point

Travis Barrett, Amit Kumar Mishra

Allbwn ymchwil: Pennod mewn Llyfr/Adroddiad/Trafodion CynhadleddTrafodion Cynhadledd (Nid-Cyfnodolyn fathau)

Crynodeb

In this paper, we describe the design of an inexpensive and agile climate sensor system which can be repurposed easily to measure various pollutants. We also propose the use of machine learning regression methods to calibrate CO2 data from this cost-effective sensing platform to a reference sensor at the South African Weather Service's Cape Point measurement facility. We show the performance of these methods and found that Random Forest Regression was the best in this scenario. This shows that these machine learning methods can be used to improve the performance of cost- effective sensor platforms and possibly extend the time between manual calibration of sensor networks.

Iaith wreiddiolSaesneg
TeitlI2MTC 2023 - 2023 IEEE International Instrumentation and Measurement Technology Conference
Is-deitlRising Above Covid-19, Proceedings
CyhoeddwrIEEE Press
Nifer y tudalennau5
ISBN (Electronig)9781665453837
Dynodwyr Gwrthrych Digidol (DOIs)
StatwsCyhoeddwyd - 13 Gorff 2023
Digwyddiad2023 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2023 - Kuala Lumpur, Malaisia
Hyd: 22 Mai 202325 Mai 2023

Cyfres gyhoeddiadau

EnwConference Record - IEEE Instrumentation and Measurement Technology Conference
Cyfrol2023-May
ISSN (Argraffiad)1091-5281

Cynhadledd

Cynhadledd2023 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2023
Gwlad/TiriogaethMalaisia
DinasKuala Lumpur
Cyfnod22 Mai 202325 Mai 2023

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