Prescription maps elaboration for variable rate irrigation system using fuzzy logic and deepening
Variable Rate Irrigation, Deep Learning, Fuzzy Systems.
The maintenance of water availability has been treated as a challenge, because with the increase in population, and consequently in the demand for water, it is also neces- sary to produce food, since its production requires drinking water for irrigation. Precision agriculture gains more space due to the rational and efficient use of water in strategic locations in the plantation, also requiring intelligent systems to support the intake. This research presents a technique using deep neural networks and fuzzy logic to deal with un- certainties and prediction models to develop an irrigation management map, considering the spatial variability of planting water needs. The object of this research is to perform autonomously, using fuzzy logic linguistic variables, the control of the rotation speed of a central irrigation pivot, together with the opening of the water spray valve, thus develo- ping a high precision irrigation model.