Uso de sistema de controle fuzzy e internet das coisas para irrigação na agricultura de precisão

Abstract

World agriculture will face the challenge of guaranteeing the food security of 9 billion people in the 2050s. Given this, it is essential to develop new farming techniques aimed at increasing food production and also the sustainable maintenance of natural resources and the environment. To produce food in the right quantity, at the right time, and affordable prices, farmers must adopt precision farming models to increase the food production amount. Precision agriculture uses agricultural management techniques based on the measurement and control of crop parameters such as soil moisture, air temperature, and the irrigation control. In this context, agricultural irrigation accounts for the greater consumption of freshwater available for use on the planet. Adopting techniques that allow increasing agricultural production, reducing irrigated water amount and waste, becomes crucial and the most appropriate responses are the implementation of solutions using Artificial Intelligence. This work uses a Precision Irrigation model, with the rain forecast as a complement to the irrigation process, to keep the soil moisture at an appropriate level for the sweet pepper culture. A fuzzy inference system was used in the the irrigation prescription amount, with the climatic data acquisition made through IoT devices installed in the crop field, maximizing soil wetting through rainfall and reducing irrigated water amount. The average reduction of 16% in irrigation, obtained in simulations and real experiments, indicates a good response of the model to the proposed objective

Importância da agricultura de precisão para a eficiência da produção agrícola: uma revisão

“…Na irrigação as principais causas de desperdícios são os vazamentos e o excesso de irrigação (Souza, 2021).…”