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

被引:3
|
作者
Boulic, Mikael [1 ]
Phipps, Robyn [1 ,3 ]
Wang, Yu [1 ,4 ]
Vignes, Matthieu [2 ,5 ]
Adegoke, Nurudeen A. [1 ]
机构
[1] Massey Univ, Sch Built Environm, Auckland 0632, New Zealand
[2] Massey Univ, Sch Math & Computat Sci, Palmerston North 4410, New Zealand
[3] Victoria Univ Wellington, Wellington Fac Architecture & Design Innovat, 139 Vivian St, Wellington 6011, New Zealand
[4] Bldg Res Assoc New Zealand BRANZ, 1222 Moonshine Rd, Porirua 5381, New Zealand
[5] Univ Sydney, Melanoma Inst Australia, Sydney, Australia
来源
JOURNAL OF BUILDING ENGINEERING | 2024年 / 82卷
关键词
Low-cost indoor air quality monitoring; Reference platform; Reliability; Shewhart and cumulative sum; Validation; TIME-SERIES; PARAMETERS; SELECTION;
D O I
10.1016/j.jobe.2023.108357
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
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.
引用
收藏
页数:13
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