An emerging technology is human computer interaction (HCI). One of the most important HCI strategies is the eye gazing method, which enables the user to operate the display without using their hands. Direct eye movement detection, template, appearance, feature, hybrid, regression, clustering 3D methods are all ways to categorize eye gaze detection techniques. Deep learning, a technology that mimics human behavior and features like speech recognition, image recognition, and language translation can make this possible. A web camera was employed in this study to capture a frame of an eye frame for mouse cursor movement. In connection with the point previously mentioned, we must first concentrate on the function of our eye. We are employing a web camera for pupil identification, which can manage the computer’s cursor. For this paper, an Aspect Ratio Eye (EAR) is determined that corresponds to the blinks of eye’s (right or left) applying the library of Mediapipe which is open source and acts as a computer vision library. You can provide smart people with crippled limbs who are having trouble using computers a chance to express their opinions. Here, the method’s objective is improving the experience of using computer for physically disabled people by assisting them in overcoming challenges using a mouse.