Sistema de Internet das Coisas para captação de dados do microclima vegetal na agricultura 2023

• Ano de defesa: 2023
• Autor(a) principal: Mendes, Davila Fernandes
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Palavras-chave em Português: Microclimatologia; Internet das Coisas; agricultura de precisão; agricultura inteligente; Microclimate; Internet of Things; precision agriculture; smart agriculture; CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA
• Link de acesso: http://repositorio.ufc.br/handle/riufc/75147

Global trends indicate that the main challenges facing humanity in the coming years will be energy, water, food, the environment, and poverty. The scarcity of resources demands new models for precision agriculture in order to optimize resource usage. One need is higher accuracy in capturing climatic elements that directly impact plant development and food production. In this context, the Internet of Things is a concept that improves automated and accurate decision- making regarding the efficient use of resources. This aspect is because the Internet of Things connects objects, human beings, and environmental aspects. The Internet of Things allows to monitor, process, and store data collected by using sensors. Monitoring climatic conditions, mainly temperature and humidity, is relevant for several agricultural applications, such as precision irrigation, pest and disease control, and soil analysis. Therefore, these variables are often monitored in the productive environment and are generally collected by meteorological stations appropriately positioned in the agricultural field. Meteorological stations gather data referring to the climatic elements of the outer zone of the field. However, measuring these climatic elements in the plant microclimate (leaves and back of the studied plant) is essential for multiple applications to support more accurate decision-making. In this context, we propose an Internet of Things (IoT) system for capturing meteorological data whose differentials are sensors placed explicitly in the microclimate of the plant. In this way, studying the dynamics of the meteorological elements involved in plant development is possible. The temperature difference between the sensors was over 20%, showcasing the impact of sensor positioning on measurements.