Abstract
This work presents a new approach to the Internet of Things (IoT) between sensor nodes and data analysis with visualization platform with the purpose to acquire urban pollution data. The main objective is to determine the degree of contamination in Ibarra city in real time. To do this, for one hand, thirteen IoT devices have been implemented. For another hand, a Prototype Selection and Data Balance algorithms comparison in relation to the classifier k-Nearest Neighbourhood is made. With this, the system has an adequate training set to achieve the highest classification performance. As a final result, the system presents a visualization platform that estimates the pollution condition with more than 90% accuracy.
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This work is supported by the Smart Data Analysis Systems - SDAS group. http://sdas-group.com/.
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Rosero-Montalvo, P.D., López-Batista, V.F., Peluffo-Ordóñez, D.H., Lorente-Leyva, L.L., Blanco-Valencia, X.P. (2019). Urban Pollution Environmental Monitoring System Using IoT Devices and Data Visualization: A Case Study. In: Pérez García, H., Sánchez González, L., Castejón Limas, M., Quintián Pardo, H., Corchado Rodríguez, E. (eds) Hybrid Artificial Intelligent Systems. HAIS 2019. Lecture Notes in Computer Science(), vol 11734. Springer, Cham. https://doi.org/10.1007/978-3-030-29859-3_58
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