Published Paper Details:

The development and implementation of a Raspberry Pi-based automated fruit sorting machine utilizing advanced computer vision techniques. The primary objective of this project is to enhance the efficiency and accuracy of fruit sorting processes in agricultural industries. The system leverages a Raspberry Pi microcontroller integrated with a high-resolution camera to capture images of fruits as they pass along a conveyor belt. Using machine learning algorithms, specifically convolutional neural networks (CNNs), the system analyzes the images to classify and sort fruits based on predefined criteria such as size, color, and surface defects. The sorted fruits are then directed into appropriate bins by an actuator mechanism controlled by the Raspberry Pi. Extensive testing of the system demonstrated high accuracy rates in fruit classification and sorting, proving the efficacy and potential for large-scale application in the agricultural sector. This innovative approach significantly reduces manual labor, enhances productivity, and ensures consistent quality in fruit sorting operations.