Paul David Rosero Montalvo, Vivian Félix López Batista, Diego Hernán Peluffo Ordoñez, Leandro L. Lorente Leyva, Xiomara Patricia Blanco Valencia
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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