doctoralThesis
Integração de dados de sensoriamento remoto em sistema de irrigação por taxa variável utilizando sistemas fuzzy de suporte à decisão
Fecha
2020-02-07Registro en:
MENDES, Willians Ribeiro. Integração de dados de sensoriamento remoto em sistema de irrigação por taxa variável utilizando sistemas fuzzy de suporte à decisão. 2020. 191f. Tese (Doutorado em Engenharia Elétrica e de Computação) - Centro de Tecnologia, Universidade Federal do Rio Grande do Norte, Natal, 2020.
Autor
Mendes, Willians Ribeiro
Resumen
Freshwater is a scarce resource, and nowadays it is under unprecedented focus due
to concerns about the sustainability of natural ecosystems and because of the agricultural
demand, which needs to feed a growing global population. These concerns make
freshwater a necessary natural resource for everyone. All these issues lead us to want to
manage this asset efficiently, thus generating an increase in the demand for more
intelligent, automated and accurate systems. These needs are the driving force behind the
development and implementation of new technologies for more rational use, allowing
farmers to improve when and where irrigation is applied, seeking to increase food
production. In this manner, this work presents a new proposal for an intelligent variable
rate irrigation system application in order to achieve that goal. It is a site-specific
irrigation management tool; in other words, a system that should assist in decisions about
applying water quantity to delimited zones. We expect a higher yield from crop
productivity and greater efficiency in water use. To be successful, the system has an
artificial intelligence approach to automatically create optimal control maps for a center
pivot irrigation system. At the heart of this system there are the fuzzy logic, which is be
able to set the reference values for the rotating speed controllers and individual opening
of each central pivot sprinkler valve. The system is based on the decision making (whether
applying more or less water) and will use remote sensing data, so we expect the smart
irrigation system to describe the spatial variability of the crop efficiently. The results point
out that the edaphoclimatic variables, when well combined with fuzzy logic, can solve
uncertainties and non-linearities of an irrigation system and define a control model for
high precision irrigation. However, it will not always be possible to reduce water
consumption, but this technology has many uses to increase farm productivity
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