Design of a precision irrigation nursery system based on binocular vision system

In response to the increasing demand for precision irrigation technology in smart agriculture, this study designed and studied a precision irrigation seedling system based on a binocular depth camera. In order to solve the problem of seedling data collection and precise control of the robotic arm, the 3D mapping and neural network recognition technology of binocular depth camera were used to comprehensively analyse the growth environment and species of the seedlings to obtain the key parameters of water demand analysis. In addition, the system analyses the distance between the water-deficient part of the seedling and the robotic arm through depth ranging, calculates the coordinate system and precisely controls the robotic arm for irrigation. The simulation experimental results show that the system effectively improves the irrigation accuracy and efficiency, provides a feasible solution for smart agriculture, and provides a new reference for water-saving irrigation and crop growth monitoring.