The agribusiness sector has been showing strong interest in the implementation of 4.0 technologies with the aim of projecting more favorable scenarios for the crop environment. Traditional conceptions of a homogeneous crop field do not meet current productivity demands, given the importance of understanding how each plot behaves. Thus, a crop field with greater productive gains has already become a reality for small, medium, and large producers. Resources such as the Internet of Things (IoT), combined with Artificial Intelligence (AI), enable the collection and processing of environmental and soil variables, as well as the prediction of scenarios through machine learning algorithms. This paper focuses on proposing a sensor station for monitoring critical variables in hop cultivation (Humulus lupulus), aiming to increase productive capacity and product quality. The proposal is based on structured data collection as a foundation for the development and application of predictive models, enabling more accurate and higher-accuracy yield projections. Furthermore, the developed model is not limited exclusively to hop management, being designed as an adaptable solution for application in different agricultural crops.

Keywords

Agribusiness, 4.0 Technologies, Internet of Things, Artificial Intelligence, Hop Farming.