@MastersThesis{Barbosa:2017:AqDaCa,
               author = "Barbosa, Ivan M{\'a}rcio",
                title = "Aquisi{\c{c}}{\~a}o de dados de carga {\'u}til de plataformas 
                         orbitais com o aux{\'{\i}}lio de t{\'e}cnicas de 
                         intelig{\^e}ncia artificial",
               school = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                 year = "2017",
              address = "S{\~a}o Jos{\'e} dos Campos",
                month = "2016-11-30",
             keywords = "intelig{\^e}ncia artificial, sistemas especialistas, 
                         sat{\'e}lites, CLIPS, design science research, artificial 
                         intelligence, expert systems, satellite.",
             abstract = "Este trabalho utiliza o m{\'e}todo cient{\'{\i}}fico Design 
                         Science Research para condu{\c{c}}{\~a}o de pesquisas 
                         cient{\'{\i}}ficas e prop{\~o}e a cria{\c{c}}{\~a}o de um 
                         prot{\'o}tipo de sistema especialista denominado Payload Data 
                         Acquisition and Dissemination Expert System (PDAD-ES). O sistema 
                         especialista PDAD-ES contempla o estudo de caso para 
                         configura{\c{c}}{\~a}o das esta{\c{c}}{\~o}es terrenas de 
                         recep{\c{c}}{\~a}o de dados dos sat{\'e}lites COSMIC-2, 
                         LANDSAT-8 e GOES-R e o estudo de caso para 
                         identifica{\c{c}}{\~a}o de anomalias e falhas na 
                         esta{\c{c}}{\~a}o terrena de recep{\c{c}}{\~a}o COSMIC-2 e na 
                         dissemina{\c{c}}{\~a}o dos dados brutos desses sat{\'e}lites 
                         para UCAR e para o EMBRACE do INPE. A defini{\c{c}}{\~a}o dos 
                         requisitos do sistema especialista, o levantamento e o mapeamento 
                         das regras de produ{\c{c}}{\~a}o e o conhecimento gerado nesse 
                         trabalho de pesquisa contribuem para o aperfei{\c{c}}oamento das 
                         atividades relacionadas ao segmento solo no INPE. A 
                         constru{\c{c}}{\~a}o do prot{\'o}tipo PDAD-ES compreende a 
                         codifica{\c{c}}{\~a}o na linguagem de programa{\c{c}}{\~a}o 
                         CLIPS e integra{\c{c}}{\~a}o ao servidor web apache atrav{\'e}s 
                         da extens{\~a}o PHLIPS. Este trabalho tamb{\'e}m descreve as 
                         caracter{\'{\i}}sticas t{\'e}cnicas atuais das 
                         esta{\c{c}}{\~o}es terrenas de recep{\c{c}}{\~a}o de dados de 
                         sat{\'e}lites do INPE, o estudo sobre intelig{\^e}ncia 
                         artificial, sistema especialista e sistemas de solo. ABSTRACT: 
                         This work uses the scientific method Design Science Research to 
                         conduct scientific research and proposes the creation of a 
                         prototype of an expert system named Payload Data Acquisition and 
                         Dissemination Expert System (PDAD-ES). The PDAD-ES expert system 
                         includes a case study to set up the COSMIC-2, LANDSAT-8 e GOES-R 
                         ground receiving stations and the case study to identify anomalies 
                         and failures in COSMIC-2 ground receiving station and raw data 
                         dissemination from these satellites to UCAR and the INPE EMBRACE. 
                         The definition of the requirements of the expert system, the 
                         survey and mapping of the production rules and the knowledge 
                         generated in this research work contribute to the improvement of 
                         the activities related to the ground segment at INPE. The 
                         developing of the PDAD-ES prototype comprises coding in the CLIPS 
                         programming language and integration to the apache web server 
                         through the PHLIPS extension. This work also includes details 
                         about the current technical characteristics of INPE's ground 
                         receiving stations to acquire the payload data, the study of 
                         artificial intelligence, expert systems and ground systems.",
            committee = "Mattiello-Francisco, Maria de F{\'a}tima (presidente) and 
                         Ferreira, Maur{\'{\i}}cio Gon{\c{c}}alves Vieira (orientador) 
                         and Chagas Junior, Milton de Freitas and Silva, Rodrigo Rocha",
           copyholder = "SID/SCD",
         englishtitle = "Orbital platform payload data acquisition with the aid of 
                         artificial intelligence techniques",
             language = "pt",
                pages = "243",
                  ibi = "8JMKD3MGP3W34P/3MRECQH",
                  url = "http://urlib.net/ibi/8JMKD3MGP3W34P/3MRECQH",
           targetfile = "publicacao.pdf",
        urlaccessdate = "27 abr. 2024"
}