Articles | Volume 14, issue 1
https://doi.org/10.5194/amt-14-37-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-14-37-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
04 Jan 2021
Research article |
| 04 Jan 2021
| 04 Jan 2021
Robust statistical calibration and characterization of portable low-cost air quality monitoring sensors to quantify real-time O3 and NO2 concentrations in diverse environments
Ravi Sahu
Department of Civil Engineering, Indian Institute of Technology Kanpur, Kanpur, India
Ayush Nagal
Department of Computer Science and Engineering, Indian Institute of Technology Kanpur, Kanpur, India
Kuldeep Kumar Dixit
Department of Civil Engineering, Indian Institute of Technology Kanpur, Kanpur, India
Harshavardhan Unnibhavi
Department of Computational and Data Sciences, Indian Institute of Science, Bengaluru, India
Srikanth Mantravadi
Department of Electrical Communication Engineering, Indian Institute of Science, Bengaluru, India
Srijith Nair
Department of Electrical Communication Engineering, Indian Institute of Science, Bengaluru, India
Yogesh Simmhan
Department of Computational and Data Sciences, Indian Institute of Science, Bengaluru, India
Brijesh Mishra
Department of Electrical Engineering, Indian Institute of Technology, Mumbai, India
Rajesh Zele
Department of Electrical Engineering, Indian Institute of Technology, Mumbai, India
Ronak Sutaria
Centre for Urban Science and Engineering, Indian Institute of Technology, Mumbai, India
Vidyanand Motiram Motghare
Maharashtra Pollution Control Board, Mumbai, India
Purushottam Kar
Department of Computer Science and Engineering, Indian Institute of Technology Kanpur, Kanpur, India
Sachchida Nand Tripathi
CORRESPONDING AUTHOR
Department of Civil Engineering, Indian Institute of Technology Kanpur, Kanpur, India
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Short summary
A unique feature of our low-cost sensor deployment is a swap-out experiment wherein four of the six sensors were relocated to different sites in the two phases. The swap-out experiment is crucial in investigating the efficacy of calibration models when applied to weather and air quality conditions vastly different from those present during calibration. We developed a novel local calibration algorithm based on metric learning that offers stable and accurate calibration performance.
A unique feature of our low-cost sensor deployment is a swap-out experiment wherein four of the...
