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dc.contributor.advisorBarbosa, Jorge Luis Victória
dc.contributor.authorHelfer, Gilson Augusto
dc.date.accessioned2022-05-10T12:46:19Z
dc.date.accessioned2022-09-22T19:49:54Z
dc.date.available2022-05-10T12:46:19Z
dc.date.available2022-09-22T19:49:54Z
dc.date.issued2022-03-25
dc.identifier.urihttps://hdl.handle.net/20.500.12032/65497
dc.description.abstractThe applications of ubiquitous computing have in creasedin recente years, mainly due to the development of Technologies such as mobile computing and its integration with the real world. One of the challenges in this area is the use of contexto aware ness. In agriculture, the contexto related to the environment can be considered, such as the chemical and physical aspects that characterize the diferente types of soil.This scenario changes periodically dueto factors such as climate, type of cultivar and soil management technique used, amongo ther aspects. This thesis presentes a computational model called Tellus applied in precision agriculture that uses historical contexts to predict soil physicochemical properties. A prototype was created to evaluate the model based on a telemetry station and installed in the field, as well as a mobile application for in formation management. The Prediction Agent training had 43 soil samples from diferente collection points in Vale do Rio Pardo, whose concentrations of organic matter varied between 0.6% and 5.9% and clay between 8% and 60%, respectively. For prediction of organic matter and clay in the soil, coefficients of determination (R2) of 0.9738 and 0.9536 were obtained and mean square erros of calibration (RMSEC) of 0.26% and 2.95%, respectively. For the irrigation recommendation, 192 images were used for training and an accuracy of 82.55% was achieved. In addition, na Agro XML based ontology called Tellus-Onto was proposed that extends the state of the artin the classification of Brazilians oil saccording to organicand textural composition. A series of axioms and semantic rules were used to provide queries and inferences about its instantiated base. In addition, from thes oil analysis information, the ontology infers recommendation for fertilization and liming. To test the ontology, 98 soils ample results were instantiated and their classifications were in ferredina precise and automatic way.The computational modeland its prediction agentes together with the ontology are the contributions of Tellus in ubiquitous agriculture applied to soil analysis.en
dc.description.sponsorshipCAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superiorpt_BR
dc.languagept_BRpt_BR
dc.publisherUniversidade do Vale do Rio dos Sinospt_BR
dc.rightsopenAccesspt_BR
dc.subjectAgricultura de precisãopt_BR
dc.subjectPrecision agricultureen
dc.titleTellus: um modelo computacional para análise de solo na agricultura ubíqua baseado em históricos de contextospt_BR
dc.typeTesept_BR


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