ABSTRACT
The usage of digital data is one of the main characteristics of the Agriculture 4.0 era. Different devices and sensors may be used to capture a variety of types of data that enable the development of applications of computer vision, acoustic events, and data processing. These applications are useful for monitoring, understanding, and predicting many attributes of agricultural chain production with the objective of assisting farmers in the decision-making process. In a scenario of increasing obligation for sustainable usage of natural resources and an increase in production rates to assure a food security situation in the world, there is a high demand for improvements at any stage of agricultural processes. This paper aims to contribute to further research on artificial intelligence in the agricultural context, listing sample practical AI scenarios, including those that the Eldorado Research Institute has contributed. Throughout this paper, different applications of AI are discussed, highlighting some characteristics, advantages, disadvantages, and results to provide an overview of the different technologies that can be applied in agriculture. Furthermore, we presented the main challenges of popularizing the use of AI-based systems, some possible approaches to reduce the difficulties, and a view of the next most promising technologies in conjunction with AI.
Key words:
Algorithm; Neural network; Computer vision; Acoustic event detection; Data processing