Automatic Classification of Medical Waste

The medical industry is essential, but its waste poses significant risks. We propose a system for automating medical waste sorting using a lifter, image recognition, mechanical arm, and real-time monitoring. The lifter design is unique and maximises space without requring conveyor belts. Additionally, a self-printed mechanical arm is used to handle waste, reducing the risk of infection and promoting environmental, social, and governance principles and public health. The proposed recognition result achieved an overall accuracy of 96.67% precision with YOLOv8-seg.