ANÁLISE DE CIDADES INTELIGENTES EM MINAS GERAIS
UMA ABORDAGEM BASEADA EM CLUSTERIZAÇÃO K-MEANS
DOI:
https://doi.org/10.54399/rbgdr.v22i1.8170Keywords:
Multicriteria Analysis, Smart Cities, K-Means clustering, Urban Development, City RankingAbstract
This study analyzes global urbanization and its challenges, such as environmental pollution, lack of electricity, and scarcity of basic public services. The research highlights the role of smart cities, which combine social, human, and information capital, aided by information and communication technologies, to improve the quality of life of individuals. The study aimed to analyze the relationships of the clusters generated from the six dimensions understood in a classification ranking aimed at underdeveloped countries by Mokarrari and Torabi (2021), applied in cities of Minas Gerais. The analysis involved the use of the K-Means clustering algorithm, the elbow analysis to determine the ideal number of centroids, and the silhouette index to assess the effectiveness of cluster division. The results highlighted the cities of Belo Horizonte, Betim, Uberaba, and Juiz de Fora, which are among the 100 smart Brazilian cities according to the Connected Smart Cities Ranking. The research concludes by emphasizing the relevance of the generated clusters for the development of Smart Cities in Minas Gerais, providing valuable insights into the strengths and weaknesses of each city, which can guide public administration and future studies.
Downloads
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Revista Brasileira de Gestão e Desenvolvimento Regional

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Authors who have their papers accepted and published in the Brazilian Journal of Regional Management and Development must agree to the copyright policy CC BY https://creativecommons.org/licenses/by/4.0/.
If the article is accepted for publication, the copyright is automatically assigned to the Brazilian Journal of Regional Management and Development.






