Image processing and recognition for controlling a greenhouse tower mechanism focused on ergonomics and acceleration in substrate placement for sugarcane germination

Abstract

Objective: To make the process of placing substrate in greenhouse towers for sugarcane germination faster and easier, through an automated prototype that uses image processing to reduce work time and physical effort.
Design/methodology/approach: A small-scale prototype was built to test how it works and to see if it could be used in real conditions. The system used a camera to recognize and locate points inside the work area, allowing smoother and more accurate movement of the mechanism.
Results: The tests showed that the system detected positions correctly and responded well to control commands, even with small changes in the environment. It also helped reduce working time and the operator’s physical effort, improving both efficiency and comfort.
Limitations/implications: During testing, changes in lighting and small vibrations affected the accuracy of the system at times. These issues were mostly caused by the materials used in the prototype and the light conditions around it. Still, the results show that the system can be improved to work with greater precision and stability.
Findings/conclusions: The prototype proved to be a good option to make substrate placement in greenhouse towers faster and more efficient, while reducing physical strain for the operator.