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- Title
Air Pollution Monitoring Using WSN Nodes with Machine Learning Techniques: A Case Study.
- Authors
Rosero-Montalvo, Paul D; López-Batista, Vivian F; Arciniega-Rocha, Ricardo; Peluffo-Ordóñez, Diego H
- Abstract
Air pollution is a current concern of people and government entities. Therefore, in urban scenarios, its monitoring and subsequent analysis is a remarkable and challenging issue due mainly to the variability of polluting-related factors. For this reason, the present work shows the development of a wireless sensor network that, through machine learning techniques, can be classified into three different types of environments: high pollution levels, medium pollution and no noticeable contamination into the Ibarra City. To achieve this goal, signal smoothing stages, prototype selection, feature analysis and a comparison of classification algorithms are performed. As relevant results, there is a classification performance of 95% with a significant noisy data reduction.
- Subjects
AIR pollution monitoring; WIRELESS sensor networks; AIR pollution; CLASSIFICATION algorithms; DATA reduction; MACHINE learning
- Publication
Logic Journal of the IGPL, 2022, Vol 30, Issue 4, p599
- ISSN
1367-0751
- Publication type
Article
- DOI
10.1093/jigpal/jzab005