Monitoring of air quality with low-cost electrochemical sensors and the use of artificial neural networks for the atmospheric pollutants concentration levels prediction

Ana Luna; Alvaro Talavera; Hector Navarro; Luis Cano

doi:10.1007/978-3-030-11680-4_15

Monitoring of air quality with low-cost electrochemical sensors and the use of artificial neural networks for the atmospheric pollutants concentration levels prediction

Ana Luna, Alvaro Talavera, Hector Navarro, Luis Cano

Resultado de la investigación: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

2 Citas (Scopus)

Resumen

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 CO2 and SO2 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.

Idioma original	Inglés
Título de la publicación alojada	Information Management and Big Data - 5th International Conference, SIMBig 2018, Proceedings
Editores	Denisse Muñante, Juan Antonio Lossio-Ventura, Hugo Alatrista-Salas
Páginas	137-150
Número de páginas	14
ISBN (versión digital)	9783030116798
DOI	https://doi.org/10.1007/978-3-030-11680-4_15
Estado	Publicada - 1 ene. 2019
Evento	Communications in Computer and Information Science - Duración: 1 ene. 2019 → …

Serie de la publicación

Nombre	Communications in Computer and Information Science
Volumen	898
ISSN (versión impresa)	1865-0929

Conferencia

Conferencia	Communications in Computer and Information Science
Período	1/01/19 → …

Nota bibliográfica

Publisher Copyright:
© 2019, Springer Nature Switzerland AG.

Palabras clave

Air pollution
Artificial neural networks
Electrochemical sensors

Acceder al documento

10.1007/978-3-030-11680-4_15

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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. En D. Muñante, J. A. Lossio-Ventura, & H. Alatrista-Salas (Eds.), Information Management and Big Data - 5th International Conference, SIMBig 2018, Proceedings (pp. 137-150). (Communications in Computer and Information Science; Vol. 898). https://doi.org/10.1007/978-3-030-11680-4_15

Luna, Ana ; Talavera, Alvaro ; Navarro, Hector et al. / Monitoring of air quality with low-cost electrochemical sensors and the use of artificial neural networks for the atmospheric pollutants concentration levels prediction. Information Management and Big Data - 5th International Conference, SIMBig 2018, Proceedings. editor / Denisse Muñante ; Juan Antonio Lossio-Ventura ; Hugo Alatrista-Salas. 2019. pp. 137-150 (Communications in Computer and Information Science).

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title = "Monitoring of air quality with low-cost electrochemical sensors and the use of artificial neural networks for the atmospheric pollutants concentration levels prediction",

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 CO2 and SO2 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.",

keywords = "Air pollution, Artificial neural networks, Electrochemical sensors, Air pollution, Artificial neural networks, Electrochemical sensors",

author = "Ana Luna and Alvaro Talavera and Hector Navarro and Luis Cano",

note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG.; Communications in Computer and Information Science ; Conference date: 01-01-2019",

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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. En D Muñante, JA Lossio-Ventura & H Alatrista-Salas (eds.), Information Management and Big Data - 5th International Conference, SIMBig 2018, Proceedings. Communications in Computer and Information Science, vol. 898, pp. 137-150, Communications in Computer and Information Science, 1/01/19. https://doi.org/10.1007/978-3-030-11680-4_15

Monitoring of air quality with low-cost electrochemical sensors and the use of artificial neural networks for the atmospheric pollutants concentration levels prediction. / Luna, Ana ; Talavera, Alvaro; Navarro, Hector et al.

Information Management and Big Data - 5th International Conference, SIMBig 2018, Proceedings. ed. / Denisse Muñante; Juan Antonio Lossio-Ventura; Hugo Alatrista-Salas. 2019. p. 137-150 (Communications in Computer and Information Science; Vol. 898).

Resultado de la investigación: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

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Luna A , Talavera A, Navarro H, Cano L. Monitoring of air quality with low-cost electrochemical sensors and the use of artificial neural networks for the atmospheric pollutants concentration levels prediction. En Muñante D, Lossio-Ventura JA, Alatrista-Salas H, editores, Information Management and Big Data - 5th International Conference, SIMBig 2018, Proceedings. 2019. p. 137-150. (Communications in Computer and Information Science). doi: 10.1007/978-3-030-11680-4_15

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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