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

Research output: Chapter in Book/Report/Conference proceedingChapter

2 Scopus citations

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.
Original languageEnglish
Title of host publicationCommunications in Computer and Information Science
Pages137-150
Number of pages14
ISBN (Electronic)9783030116798
DOIs
StatePublished - 1 Jan 2019
EventCommunications in Computer and Information Science -
Duration: 1 Jan 2019 → …

Publication series

NameCommunications in Computer and Information Science
Volume898
ISSN (Print)1865-0929

Conference

ConferenceCommunications in Computer and Information Science
Period1/01/19 → …

Keywords

  • Air pollution
  • Artificial neural networks
  • Electrochemical sensors

Fingerprint

Dive into the research topics of 'Monitoring of air quality with low-cost electrochemical sensors and the use of artificial neural networks for the atmospheric pollutants concentration levels prediction'. Together they form a unique fingerprint.

Cite this