Abstract
Abstract: The Automatic Fruit Plucking Machine project aims to develop an innovative automated system to revolutionize fruit harvesting. By integrating computer vision, robotic arm manipulation, and YOLO deep learning algorithms, the machine can accurately identify and pluck ripe fruits. It reduces labor costs, enhances harvest quality, and improves productivity. The machine's core is a trained machine learning algorithm that combines image processing and deep learning models for real-time fruit detection. Through iterative testing and refinement, the machine's performance continually improves. This project offers a sustainable and efficient solution for fruit producers to meet market demands and reduce manual labor reliance
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