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Reliability Validation of a Low-Cost Particulate Matter IoT Sensor in Indoor and Outdoor Environments Using a Reference Sampler

Author

Listed:
  • Sergio Trilles

    (Institute of New Imaging Technologies (INIT), Universitat Jaume I, Av. Vicente Sos Baynat s/n, 12071 Castelló de la Plana, Spain
    These authors contributed equally to this work.)

  • Ana Belen Vicente

    (Department of Agricultural and Environmental Sciences, Universitat Jaume I, Av. Vicente Sos Baynat s/n, 12071 Castelló de la Plana, Spain
    These authors contributed equally to this work.)

  • Pablo Juan

    (Department of Mathematics, Statistics Area, Universitat Jaume I, Av. Vicente Sos Baynat s/n, 12071 Castelló de la Plana, Spain
    Institut Universitari de Matemàtiques (IMAC), Universitat Jaume I, Av. Vicente Sos Baynat s/n, 12071 Castelló de la Plana, Spain
    These authors contributed equally to this work.)

  • Francisco Ramos

    (Institute of New Imaging Technologies (INIT), Universitat Jaume I, Av. Vicente Sos Baynat s/n, 12071 Castelló de la Plana, Spain)

  • Sergi Meseguer

    (Department of Agricultural and Environmental Sciences, Universitat Jaume I, Av. Vicente Sos Baynat s/n, 12071 Castelló de la Plana, Spain)

  • Laura Serra

    (CIBER of Epidemiology and Public Health (CIBERESP), 28029 Madrid, Spain
    Research Group on Statistics, Econometrics and Health (GRECS), University of Girona, 17004 Girona, Spain
    These authors contributed equally to this work.)

Abstract

A suitable and quick determination of air quality allows the population to be alerted with respect to high concentrations of pollutants. Recent advances in computer science have led to the development of a high number of low-cost sensors, improving the spatial and temporal resolution of air quality data while increasing the effectiveness of risk assessment. The main objective of this work is to perform a validation of a particulate matter (PM) sensor ( HM-3301 ) in indoor and outdoor environments to study PM 2.5 and PM 10 concentrations. To date, this sensor has not been evaluated in real-world situations, and its data quality has not been documented. Here, the HM-3301 sensor is integrated into an Internet of things (IoT) platform to establish a permanent Internet connection. The validation is carried out using a reference sampler ( LVS3 of Derenda) according to EN12341:2014. It is focused on statistical insight, and environmental conditions are not considered in this study. The ordinary Linear Model, the Generalized Linear Model, Locally Estimated Scatterplot Smoothing, and the Generalized Additive Model have been proposed to compare and contrast the outcomes. The low-cost sensor is highly correlated with the reference measure ( R 2 greater than 0.70), especially for PM 2.5 , with a very high accuracy value. In addition, there is a positive relationship between the two measurements, which can be appropriately fitted through the Locally Estimated Scatterplot Smoothing model.

Suggested Citation

  • Sergio Trilles & Ana Belen Vicente & Pablo Juan & Francisco Ramos & Sergi Meseguer & Laura Serra, 2019. "Reliability Validation of a Low-Cost Particulate Matter IoT Sensor in Indoor and Outdoor Environments Using a Reference Sampler," Sustainability, MDPI, vol. 11(24), pages 1-14, December.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:24:p:7220-:d:298620
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    References listed on IDEAS

    as
    1. Sergio Trilles Oliver & Alberto González-Pérez & Joaquín Huerta Guijarro, 2019. "Adapting Models to Warn Fungal Diseases in Vineyards Using In-Field Internet of Things (IoT) Nodes," Sustainability, MDPI, vol. 11(2), pages 1-18, January.
    2. Ana Belen Vicente & Pablo Juan & Sergi Meseguer & Laura Serra & Sergio Trilles, 2019. "Air Quality Trend of PM10. Statistical Models for Assessing the Air Quality Impact of Environmental Policies," Sustainability, MDPI, vol. 11(20), pages 1-18, October.
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    Cited by:

    1. Jewan Ryu & Heekyung Park, 2022. "Band-Sensitive Calibration of Low-Cost PM2.5 Sensors by LSTM Model with Dynamically Weighted Loss Function," Sustainability, MDPI, vol. 14(10), pages 1-17, May.
    2. Nikola Zaric & Velibor Spalevic & Nikola Bulatovic & Nikola Pavlicevic & Branislav Dudic, 2021. "Measurement of Air Pollution Parameters in Montenegro Using the Ecomar System," IJERPH, MDPI, vol. 18(12), pages 1-21, June.

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