An Interval Fuzzy Logic-Based System to Predict Pests in Agriculture - Rodrigues, L. M.; Dimuro, G. P.; Franco, D. T.; Fachinello, J. C. (Anais do Workshop de Computação Aplicada à Gestão do Meio Ambiente e Recursos Naturais (WCAMA); 2013: Anais do IV Workshop de Computação Aplicada à Gestão do Meio Ambiente e Recursos Naturais, 2013)
Precision Agriculture is a relatively new area of study in Brazil, with its expansion in the mid 90s. In this period, there were government incentives in credit lines for rural producers, making possible the use of new technologies in rural areas for maximizing production and reducing costs. In this sense, this work proposes to apply environmental sensing technologies to assist farmers to detect the possibility of pests occurrence (or proliferation) in their culture. For that, the Arduino platform is being used in combination with adequate sensors to capture meteorological conditions in a given region. 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. Besides, 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.