Extensive evaluation and classification of low‐cost dust sensors in laboratory using a newly developed test method

Ahn, Kang‐Ho; Lee, Handol; Lee, Hae Dong; Kim, Sang Chul

doi:10.1111/ina.12615

Cited by 14 publications

(6 citation statements)

References 29 publications

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“…In addition, the Winsen ZH03A sensor and Novafitness SDS011 sensor presented coefficients of variation below 10%, which is within the precision envelope set by the EPA standards. In the work by Kim et al [68], two types of test systems ( Figure 12) were employed. One used a mixing chamber (50 L), where particles were mixed with clean air, and the overall airflow velocity was carefully adjusted to ensure that the dust sensor would function properly ( Figure 12A).…”

Section: Papapostolou Et Al Developed the Test Chamber Represented Inmentioning

confidence: 99%

“…However, accurate PM10 measurements were rarely achieved, likely because of the difficulty in transporting large particles to the detection zones. In the work by Kim et al [68], two types of test systems ( Figure 12) were employed. One used a mixing chamber (50 L), where particles were mixed with clean air, and the overall airflow velocity was carefully adjusted to ensure that the dust sensor would function properly ( Figure 12A).…”

Section: Papapostolou Et Al Developed the Test Chamber Represented Inmentioning

confidence: 99%

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A Review of Low-Cost Particulate Matter Sensors from the Developers’ Perspectives

Alfano

Barretta

Giudice

et al. 2020

Sensors

113

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The concerns related to particulate matter’s health effects alongside the increasing demands from citizens for more participatory, timely, and diffused air quality monitoring actions have resulted in increasing scientific and industrial interest in low-cost particulate matter sensors (LCPMS). In the present paper, we discuss 50 LCPMS models, a number that is particularly meaningful when compared to the much smaller number of models described in other recent reviews on the same topic. After illustrating the basic definitions related to particulate matter (PM) and its measurements according to international regulations, the device’s operating principle is presented, focusing on a discussion of the several characterization methodologies proposed by various research groups, both in the lab and in the field, along with their possible limitations. We present an extensive review of the LCPMS currently available on the market, their electronic characteristics, and their applications in published literature and from specific tests. Most of the reviewed LCPMS can accurately monitor PM changes in the environment and exhibit good performances with accuracy that, in some conditions, can reach R2 values up to 0.99. However, such results strongly depend on whether the device is calibrated or not (using a reference method) in the operative environment; if not, R2 values lower than 0.5 are observed.

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Section: Papapostolou Et Al Developed the Test Chamber Represented Inmentioning

confidence: 99%

Section: Papapostolou Et Al Developed the Test Chamber Represented Inmentioning

confidence: 99%

A Review of Low-Cost Particulate Matter Sensors from the Developers’ Perspectives

Alfano

Barretta

Giudice

et al. 2020

Sensors

113

View full text Add to dashboard Cite

show abstract

“…We first trained the MLR model with X train such that loss in equation (6), that is the mean square error (MSE) between the predicted sensors values ( Ŷftrain ) and the reference instrument values (Y train ) is minimised. Then the trained MLR model is utilized to generate error vector E atrain shown in equation (7), which is the absolute difference between Ŷftrain and Y train .…”

Section: A Practical Implementation Of Eeatcmentioning

confidence: 99%

Quantitative Analysis for Application Specific Calibration Approaches for Low-Cost Sensors for Air Quality Monitoring

Narayana

Jalihal

2022

IEEJ Trans.EIS

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Low-cost sensors (LCS) are affordable, compact, and often portable devices designed to measure various environmental parameters, including air quality. These sensors are intended to provide accessible and cost-effective solutions for monitoring pollution levels in different settings, such as indoor, outdoor and moving vehicles. However, the data produced by LCS is prone to various sources of error that can affect accuracy. Calibration is a well-known procedure to improve the reliability of the data produced by LCS, and several developments and efforts have been made to calibrate the LCS. This work proposes a novel Estimated Error Augmented Two-phase Calibration (EEATC) approach to calibrate the LCS in stationary and mobile deployments. In contrast to the existing approaches, the EEATC calibrates the LCS in two phases, where the error estimated in the first phase calibration is augmented with the input to the second phase, which helps the second phase to learn the distributional features better to produce more accurate results. We show that the EEATC outperforms well-known single-phase calibration models such as linear regression models (single variable linear regression (SLR) and multiple variable linear regression (MLR)) and Random forest (RF) in stationary and mobile deployments. To test the EEATC in stationary deployments, we have used the Community Air Sensor Network (CAIRSENSE) data set approved by the United States Environmental Protection Agency (USEPA), and the mobile deployments are tested with the real-time data obtained from SensurAir, an LCS device developed and deployed on moving vehicle in Chennai, India.

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“…Signal drifts may also occur, especially in long-term measurements; therefore, calibration of the sensors is recommended [ 42 , 50 ]. It is also noted that PM 10 is more challenging to measure with LCSs than PM 2.5 [ 51 ].…”

Section: Introductionmentioning

confidence: 99%

Indication Variability of the Particulate Matter Sensors Dependent on Their Location

Wiora,

Kasprzyk

2024

Sensors

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Particulate matter (PM) suspended in the air significantly impacts human health. Those of anthropogenic origin are particularly hazardous. Poland is one of the countries where the air quality during the heating season is the worst in Europe. Air quality in small towns and villages far from state monitoring stations is often much worse than in larger cities where they are located. Their residents inhale the air containing smoke produced mainly by coal-fired stoves. In the frame of this project, an air quality monitoring network was built. It comprises low-cost PMS7003 PM sensors and ESP8266 microcontrollers with integrated Wi-Fi communication modules. This article presents research results on the influence of the PM sensor location on their indications. It has been shown that the indications from sensors several dozen meters away from each other can differ by up to tenfold, depending on weather conditions and the source of smoke. Therefore, measurements performed by a network of sensors, even of worse quality, are much more representative than those conducted in one spot. The results also indicated the method of detecting a sudden increase in air pollutants. In the case of smokiness, the difference between the mean and median indications of the PM sensor increases even up to 400 µg/m3 over a 5 min time window. Information from this comparison suggests a sudden deterioration in air quality and can allow for quick intervention to protect people’s health. This method can be used in protection systems where fast detection of anomalies is necessary.

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Extensive evaluation and classification of low‐cost dust sensors in laboratory using a newly developed test method

Cited by 14 publications

References 29 publications

A Review of Low-Cost Particulate Matter Sensors from the Developers’ Perspectives

A Review of Low-Cost Particulate Matter Sensors from the Developers’ Perspectives

Quantitative Analysis for Application Specific Calibration Approaches for Low-Cost Sensors for Air Quality Monitoring

Indication Variability of the Particulate Matter Sensors Dependent on Their Location

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