Reliability Validation of a Low-Cost Particulate Matter IoT Sensor in Indoor and Outdoor Environments Using a Reference Sampler
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Other documents of the author: Trilles, Sergio; Vicente, Ana Belen; Juan, Pablo; Ramos, Jose Francisco; Meseguer Costa, Sergio; Serra, Laura
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comunitat-uji-handle2:10234/7038
comunitat-uji-handle3:10234/8634
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INVESTIGACIONMetadata
Title
Reliability Validation of a Low-Cost Particulate Matter IoT Sensor in Indoor and Outdoor Environments Using a Reference SamplerAuthor (s)
Date
2019Publisher
MDPIISSN
2071-1050Bibliographic citation
TRILLES, Sergio, et al. Reliability Validation of a Low-Cost Particulate Matter IoT Sensor in Indoor and Outdoor Environments Using a Reference Sampler. Sustainability, 2019, vol. 11, núm. 24, p. 7220Type
info:eu-repo/semantics/articlePublisher version
https://www.mdpi.com/2071-1050/11/24/7220Version
info:eu-repo/semantics/publishedVersionSubject
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 ... [+]
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 PM2.5 and PM10 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 ( R2 greater than 0.70), especially for PM2.5, 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. [-]
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Sustainability, 2019, vol. 11, núm. 24, p. 7220Investigation project
This work has been funded by the Generalitat Valenciana through the Subvenciones para la Realización de Proyectos de I+D+i Desarrollados por Grupos de Investigación Emergentes program (GV/2019/016). Sergio Trilles has been funded by the postdoctoral programme PINV2018, Universitat Jaume I (POSDOC-B/2018/12).Rights
info:eu-repo/semantics/openAccess
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