Fruit Grading Using CNN

This project presents an automated fruit grading system using Convolutional Neural Networks (CNN) implemented on a Raspberry Pi platform. The system is designed to classify fruits based on their ripeness into two categories: ripened and unripen. A USB web camera captures real-time images of the fruit, which are then processed by a CNN model trained to detect and classify the ripeness stage. An IR sensor is used to detect the presence of a fruit on the conveyor or platform. Once detected, the CNN analyses the image and triggers a servo motor mechanism to sort the fruit accordingly. Ripened fruits are directed into one box, while unripen ones are guided into another. The entire setup is compact and cost-effective, featuring an LCD for system status display and integrated components suitable for smart agriculture and food processing applications.