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 congresoCapítulo de libro

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 originalInglés
Título de la publicación alojadaCommunications in Computer and Information Science
Páginas137-150
Número de páginas14
ISBN (versión digital)9783030116798
DOI
EstadoPublicada - 1 ene. 2019
EventoCommunications in Computer and Information Science -
Duración: 1 ene. 2019 → …

Serie de la publicación

NombreCommunications in Computer and Information Science
Volumen898
ISSN (versión impresa)1865-0929

Conferencia

ConferenciaCommunications in Computer and Information Science
Período1/01/19 → …

Palabras clave

  • Air pollution
  • Artificial neural networks
  • Electrochemical sensors

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