The objective is to create a Raspberry Pi–based system that uses OpenCV to track eye movements for hands-free cursor control, enhancing accessibility for differently-abled individuals
This project presents a Raspberry Pi-based eye movement-controlled cursor system using OpenCV and a USB web camera. The camera continuously captures eye movements, and OpenCV image processing techniques are used to detect and track the user's gaze in real time. Based on the detected eye movement direction, the system controls the computer cursor without requiring a mouse or touchpad. The proposed system provides a low-cost, efficient, and hands-free human–computer interaction solution, particularly useful for individuals with physical disabilities and assistive technology applications.
Keywords: Raspberry Pi, OpenCV, Eye Tracking, Cursor Control, Computer Vision.
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Hardware components:
Software requirements: