DCluster: Geospatial Analytics with PoI Identification


  • Cláudio Gustavo S. Capanema Universidade Federal de Minas Gerais
  • Fabrício A. Silva Universidade Federal de Viçosa
  • Thais R. M. Braga Silva Universidade Federal de Viçosa
  • Antonio A. F. Loureiro Universidade Federal de Minas Gerais




Points of Interest, Clustering, Geospatial Data, Data Analysis


The generation of geospatial data is an inherent aspect for several applications that aim to track people, automobiles, or other mobile objects. Mining information from this type of data is a crucial factor for the development of Smart Cities. In many cases, it can help improve human mobility and the quality of citizens. In this sense, there is a growing demand for systems capable of extracting information from several data types, including the geospatial one. In this work, we present DCluster, a web system that aims to assist data analysts in exploring and visualizing the main types of data, including the geospatial one. Additionally, DCluster has the capability of discovering points of interest based on data of mobile users and classifying them as Home, Work, and Other locations. Data analysts can take advantage of DCluster to explore their data and extract knowledge from it.


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How to Cite

S. Capanema, C. G., A. Silva, F., M. Braga Silva, T. R., & F. Loureiro, A. A. (2021). DCluster: Geospatial Analytics with PoI Identification. Journal of Information and Data Management, 12(2). https://doi.org/10.5753/jidm.2021.1952



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