Abstract: This project focuses on the development of a fruit sorting system utilizing Raspberry Pi and machine learning techniques. The primary objective is to implement an automated system capable of detecting and sorting tomatoes based on their ripeness. The system utilizes a Raspberry Pi for object detection using the Haar Cascade algorithm and analyzes the color of the detected tomatoes to determine their ripeness. The determined data is then transmitted to an Arduino, which controls a servo motor to sort the tomatoes accordingly. This abstract provides an overview of the project's methodology, key components, and anticipated outcomes.

Keywords: Raspberry pi, Haar cascade algorithm, Arduino uno

| DOI: 10.17148/IARJSET.2024.11590