Research on the Design and Application of Digital Twin-Based Smart Agricultural Systems

The smartization of agriculture is happening at a rapid pace. A large number of sensors are being used in agricultural systems to collect data, analyze it, and provide appropriate environmental conditions to lead to more efficient agricultural production. This paper is a study on building a smart agricultural system using digital twins. To this end, the proposed agricultural system collects crop and environmental data from sensors in real time and generates digital twins based on them. The generated digital twins are modeled using machine learning algorithms, and agricultural experts can then determine We show that it is possible to build a smart agricultural system using digital twins that can increase crop productivity and reduce costs.