A system based on interval fuzzy approach to predict the appearance of pests in agriculture

Precision Agriculture is becoming an unavoidable approach for farmers aiming to improve their businesses. Technologies that were once used only by urban companies are being used in agriculture in order to maximize their production, reducing the costs. In this sense, this work proposes to apply environmental sensing technologies to assist farmers to detect the probability of occurrence (or proliferation) of pests in their culture. For that, the Arduino platform, in combination with adequate sensors to capture climatic conditions in a given region, is used. We apply an approach based on Interval Fuzzy Logic for the assessment of the sensing data to report if the weather conditions are favorable for the emergence of pests, especially fungi, which depend on factors such as temperature, humidity and leaf wetness. A discussion about an experiment performed to test the developed system is presented. The experiment is based on a common disease encountered, mainly, in the southern region of the state of Rio Grande do Sul, in Brazil. The disease, called Brown Rot, is caused by a fungus known as Monilinia fructicola.