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    Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10259/8356

    Título
    A Smart Decision System for Digital Farming
    Autor
    Cambra Baseca, CarlosAutoridad UBU Orcid
    Sendra, Sandra
    Lloret, Jaime
    Tomás, Jesús
    Publicado en
    Agronomy. 2019, V. 9, n. 5, 216
    Editorial
    MDPI
    Fecha de publicación
    2019
    ISSN
    2073-4395
    DOI
    10.3390/agronomy9050216
    Resumo
    New technologies have the potential to transform agriculture and to reduce environmental impact through a green revolution. Internet of Things (IoT)-based application development platforms have the potential to run farm management tools capable of monitoring real-time events when integrated into interactive innovation models for fertirrigation. Their capabilities must extend to flexible reconfiguration of programmed actions. IoT platforms require complex smart decision-making systems based on data-analysis and data mining of big data sets. In this paper, the advantages are demonstrated of a powerful tool that applies real-time decisions from data such as variable rate irrigation, and selected parameters from field and weather conditions. The field parameters, the index vegetation (estimated using aerial images), and the irrigation events, such as flow level, pressure level, and wind speed, are periodically sampled. Data is processed in a decision-making system based on learning prediction rules in conjunction with the Drools rule engine. The multimedia platform can be remotely controlled, and offers a smart farming open data network with shared restriction levels for information exchange oriented to farmers, the fertilizer provider, and agricultural technicians that should provide the farmer with added value in the form of better decision making or more efficient exploitation operations and management.
    Palabras clave
    Smart farming
    IoT farming
    Agriculture smart system
    WSN agriculture
    Digital farming
    Materia
    Ingeniería civil
    Civil engineering
    Informática
    Computer science
    URI
    http://hdl.handle.net/10259/8356
    Versión del editor
    https://doi.org/10.3390/agronomy9050216
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    Cambra-agronomy_2019.pdf
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