@InProceedings{ReisCâmaAssuMont:2007:DaClGe,
               author = "Reis, Ilka Afonso and C{\^a}mara, Gilberto and 
                         Assun{\c{c}}{\~a}o, Renato and Monteiro, Ant{\^o}nio Miguel 
                         Vieira",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE). Universidade 
                         Federal de Minas Gerais (UFMG). Departamento de 
                         Estat{\'{\i}}stica.} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Universidade Federal de Minas Gerais 
                         (UFMG). Departamento de Estat{\'{\i}}stica.} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)}",
                title = "Data-aware clustering for geosensor networks data collection",
            booktitle = "Anais...",
                 year = "2007",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares and Fonseca, Leila Maria Garcia",
                pages = "6059--6066",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 13. (SBSR).",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "remote sensing, environment monitoring, spatio-temporal data, data 
                         aggregation.",
             abstract = "Geosensor networks comprise small electro-mechanical devices that 
                         communicate over a wireless network. These devices collect 
                         environmental measures and send them to a base station. Energy 
                         consumption and data routing are critical factors for efficient 
                         geosensor networks. The usual cluster-based data routing protocols 
                         for sensor networks group the nodes based on their geographical 
                         closeness and aggregate their data to save energy. However, this 
                         clustering procedure does not produce the best data summaries. We 
                         propose to group the nodes into spatially homogeneous clusters, 
                         which consider both the geographical distance and the similarity 
                         of measurements between the nodes. Through simulated experiments, 
                         we have concluded that spatially homogeneous clusters produce 
                         better spatial zones identification and data summaries with a 
                         higher statistical quality if compared with the usual clustering 
                         methods. Besides, spatially homogeneous clustering can be seen as 
                         a tool for spatial sensor data mining, since their clusters 
                         represent the partition of the sensor field that has maximum 
                         internal homogeneity regarding the values of monitored variable. 
                         To make possible the use of our data-aware clustering proposal to 
                         collect the sensors data, we present a design guideline for a 
                         cluster-based data routing protocol, the HR-DASH.",
  conference-location = "Florian{\'o}polis",
      conference-year = "21-26 abr. 2007",
           copyholder = "SID/SCD",
                 isbn = "978-85-17-00031-7",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "dpi.inpe.br/sbsr@80/2006/11.15.23.33",
                  url = "http://urlib.net/ibi/dpi.inpe.br/sbsr@80/2006/11.15.23.33",
           targetfile = "6059-6066.pdf",
                 type = "Processamento de Dados e de Imagens",
        urlaccessdate = "23 maio 2024"
}