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 language | English |
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Title of host publication | Information Management and Big Data - 5th International Conference, SIMBig 2018, Proceedings |
Editors | Denisse Muñante, Juan Antonio Lossio-Ventura, Hugo Alatrista-Salas |
Pages | 137-150 |
Number of pages | 14 |
ISBN (Electronic) | 9783030116798 |
DOIs | |
State | Published - 1 Jan 2019 |
Event | Communications in Computer and Information Science - Duration: 1 Jan 2019 → … |
Publication series
Name | Communications in Computer and Information Science |
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Volume | 898 |
ISSN (Print) | 1865-0929 |
Conference
Conference | Communications in Computer and Information Science |
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Period | 1/01/19 → … |
Bibliographical note
Publisher Copyright:© 2019, Springer Nature Switzerland AG.
Keywords
- Air pollution
- Artificial neural networks
- Electrochemical sensors