Validation of low-cost air quality monitoring platforms using model-based control charts

Boulic M; Phipps R; Wang Y; Vignes M; Adegoke NA

Validation of low-cost air quality monitoring platforms using model-based control charts

dc.citation.volume	82
dc.contributor.author	Boulic M
dc.contributor.author	Phipps R
dc.contributor.author	Wang Y
dc.contributor.author	Vignes M
dc.contributor.author	Adegoke NA
dc.date.accessioned	2024-08-09T00:50:09Z
dc.date.available	2024-08-09T00:50:09Z
dc.date.issued	2024-04-01
dc.description.abstract	The SARS COVID-19 pandemic highlighted the importance of routine indoor air quality (IAQ) monitoring. Recent advances in IAQ sensors and remote logging technologies offer opportunities to use low-cost platforms to monitor indoor air. The sensor's accuracy and stability are critical for reliable monitoring and health protection. Data from our low-cost IAQ platform (SKOMOBO) was validated against a commercial platform for carbon dioxide, temperature, and relative humidity measurements to test the reliability of the low-cost instrument. The traditional statistical method to test the variability between two data sets is the coefficient of determination method. We identified that this traditional method did not detect drifts in measurements, when comparing data from two platforms, in a controlled and uncontrolled environment. In our paper, we propose two complementary methods to detect potential drifts in measurements (a modified Shewhart method and a cumulative sum control chart method). The traditional coefficient of determination method indicated strong consistency (between 0.70 and 0.99) in the measurements between SKOMOBO and the reference platforms for both tested environments. Our more sensitive methods detected 100 % data matching for the controlled environment between the SKOMOBO and the reference platform but detected some drifts for the uncontrolled environment (between 81 % and 100 % data matching). It was expected that the uncontrolled environment would create more drifts in measurements than the controlled environment. Our new statistical methods achieved two important results; namely it advanced the validation process and proved the reliability of our low-cost platform for IAQ monitoring and assurance.
dc.description.confidential	false
dc.edition.edition	108357
dc.identifier.citation	Boulic M, Phipps R, Wang Y, Vignes M, Adegoke NA. (2024). Validation of low-cost air quality monitoring platforms using model-based control charts. Journal of Building Engineering. 82.
dc.identifier.doi	10.1016/j.jobe.2023.108357
dc.identifier.eissn	2352-7102
dc.identifier.elements-type	journal-article
dc.identifier.pii	S2352710223025408
dc.identifier.uri	https://mro.massey.ac.nz/handle/10179/71247
dc.language	English
dc.publisher	Elsevier Ltd
dc.publisher.uri	https://www.sciencedirect.com/science/article/pii/S2352710223025408
dc.relation.isPartOf	Journal of Building Engineering
dc.rights	(c) 2023 The Author/s
dc.rights	CC BY 4.0
dc.rights.uri	https://creativecommons.org/licenses/by/4.0/
dc.subject	Low-cost indoor air quality monitoring
dc.subject	Reference platform
dc.subject	Reliability
dc.subject	Shewhart and cumulative sum
dc.subject	Validation
dc.title	Validation of low-cost air quality monitoring platforms using model-based control charts
dc.type	Journal article
pubs.elements-id	485474
pubs.organisational-group	Other