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Annual International Symposium on Information Management and Big Data

SIMBig 2018: Information Management and Big Data pp 137–150Cite as

Monitoring of Air Quality with Low-Cost Electrochemical Sensors and the Use of Artificial Neural Networks for the Atmospheric Pollutants Concentration Levels Prediction

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 898))

Abstract

This paper shows the preliminary results of the monitoring and estimation of air pollutants at a strategic point within the district of San Isidro, Lima - Peru. Low-cost, portable, wireless and geo-locatable electrochemical sensors were used to capture reliable contamination levels in real-time which could be used not only to quantify atmospheric pollution exposure but also for prevention and control, and even for legislative purposes. For the prediction of \(CO{_2}\) and \(SO{_2}\) levels, computational intelligence algorithms were applied and validated with experimental data. We proved that the use of Artificial Neural Networks (ANNs) has a high potential as a tool to use it as a forecast methodology in the area of air pollution.

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Acknowledgment

The authors would like to thank the Universidad del Pacífico and in particular the Department of Engineering for the purchase of the air and sound pollution sensors; and of the SIM cards used for data transmission. The authors would also like to express their gratitude to Mrs. Jimena Sánchez Velarde, Director of datosabiertosperu.com and Pamela Olenka Peña, Manager of Sustainability of the Municipality of San Isidro, who authorized the use of the facilities within the Municipality, allowing the realization of this research.

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Authors and Affiliations

  1. Universidad del Pacífico, Av. Salaverry, 2020, Lima, Peru

    Ana Luna, Alvaro Talavera, Hector Navarro & Luis Cano

Authors
  1. Ana Luna
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  2. Alvaro Talavera
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  3. Hector Navarro
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  4. Luis Cano
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Corresponding author

Correspondence to Ana Luna .

Editor information

Editors and Affiliations

  1. Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, USA

    Juan Antonio Lossio-Ventura

  2. Fondazione Bruno Kessler, Trento, Italy

    Denisse Muñante

  3. Facultad de Ingeniería, University of the Pacific, Jesús María, Lima, Peru

    Hugo Alatrista-Salas

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Luna, A., Talavera, A., Navarro, H., Cano, L. (2019). Monitoring of Air Quality with Low-Cost Electrochemical Sensors and the Use of Artificial Neural Networks for the Atmospheric Pollutants Concentration Levels Prediction. In: Lossio-Ventura, J., Muñante, D., Alatrista-Salas, H. (eds) Information Management and Big Data. SIMBig 2018. Communications in Computer and Information Science, vol 898. Springer, Cham. https://doi.org/10.1007/978-3-030-11680-4_15

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  • DOI: https://doi.org/10.1007/978-3-030-11680-4_15

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-11679-8

  • Online ISBN: 978-3-030-11680-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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