@InProceedings{OliveiraRodrMartSoar:2022:NeBiDa,
               author = "Oliveira, S{\'a}vio S. Teles de and Rodrigues, Vagner J. do 
                         Sacramento and Martins, Wellington S. and Soares, Anderson da 
                         Silva",
          affiliation = "{Universidade Federal de Goi{\'a}s (UFG)} and {Universidade 
                         Federal de Goi{\'a}s (UFG)} and {Universidade Federal de 
                         Goi{\'a}s (UFG)} and {Universidade Federal de Goi{\'a}s (UFG)}",
                title = "A New Big Data Architecture for Efficient Processing of 
                         Spatiotemporal Data using Machine Learning",
            booktitle = "Anais...",
                 year = "2022",
               editor = "Rosim, Sergio (INPE) and Santos, Leonardo Bacelar Lima (CEMADEN) 
                         and Pereira, Marconi de Arruda (UFSJ)",
         organization = "Simp{\'o}sio Brasileiro de Geoinform{\'a}tica, 23. (GEOINFO)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "The volume of spatiotemporal data is increasing in the era of Big 
                         Data and has brought several challenges in managing and processing 
                         these data. Many big data platforms have been created to address 
                         these challenges, but none can outperform the others in all 
                         scenarios on spatiotemporal queries. This paper presents a 
                         scalable architecture for efficient spatiotemporal data 
                         processing. This architecture allows a couple of several big data 
                         platforms and automatically choose on the fly, using machine 
                         learning, the best big data platform to process each 
                         spatiotemporal query.",
  conference-location = "On-line",
      conference-year = "28 a 30 nov. 2022",
                 issn = "2179-4847",
             language = "en",
                  ibi = "8JMKD3MGPDW34P/487M24S",
                  url = "http://urlib.net/ibi/8JMKD3MGPDW34P/487M24S",
           targetfile = "39-50_Oliveira_New.pdf",
        urlaccessdate = "13 maio 2024"
}