Smart City Visualization Tool for the Open Data Georeferenced Analysis Utilizing Machine Learning

  • Elsa Estrada CUCEA, Universidad de Guadalajara
  • Rocío Maciel CUCEA, Universidad de Guadalajara
  • Carlos Alberto Ochoa Ortíz Zezzatti Universidad Autónoma de Ciudad Juarez
  • Beatriz Bernabe-Loranca Benemérita Universidad Autónoma de Puebla
  • Diego Oliva CUCEI, Universidad de Guadalajara
  • Víctor Larios CUCEA, Universidad de Guadalajara
Keywords: Smart City tools

Abstract

In Smart cities it is essential the development of information systems that collaborate in the measurement of the urban surroundings towards the cities’ sustainability. In this research, for the key performance indicators it is proposed a pattern’s visualization of efficiency metrics tool, utilizing the auto learning techniques “machine learning”. The objective is to give support to the decision making throughout the georeferenced analysis exploiting the Open Data. The research was applied to the primary public schools data study case, including four stages: the study of metrics, the search of the data model, the test of territorial dependency, and the development of the tool that applies the grouping techniques or clustering to compare the development and school resources by zone. In the tool, the kmeans algorithm is implemented with label as validation method to select the more relevant centroids to display on a map.

Published
2018-02-23
How to Cite
Estrada, E., Maciel, R., Ortíz Zezzatti, C. A. O., Bernabe-Loranca, B., Oliva, D., & Larios, V. (2018). Smart City Visualization Tool for the Open Data Georeferenced Analysis Utilizing Machine Learning. International Journal of Combinatorial Optimization Problems and Informatics, 9(2), 25-40. Retrieved from https://ijcopi.org/index.php/ojs/article/view/93
Section
Articles