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

Sergio Trilles, Ana Belen Vicente, Pablo Juan, Francisco Ramos, Sergi Meseguer and Laura Serra
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Sergio Trilles: Institute of New Imaging Technologies (INIT), Universitat Jaume I, Av. Vicente Sos Baynat s/n, 12071 Castelló de la Plana, Spain
Ana Belen Vicente: Department of Agricultural and Environmental Sciences, Universitat Jaume I, Av. Vicente Sos Baynat s/n, 12071 Castelló de la Plana, Spain
Pablo Juan: Department of Mathematics, Statistics Area, Universitat Jaume I, Av. Vicente Sos Baynat s/n, 12071 Castelló de la Plana, Spain
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

Sustainability, 2019, vol. 11, issue 24, 1-14

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.

Keywords: low-cost sensors; reference samplers; air quality; particulate matter (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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