This paper presents “Smart Mobility with iWheel,” an innovative approach to improve the abilities of individuals with disabilities through eye-tracking and voice control technology The iWheel system connects wheelchairs to Arduino-based controls and provides them users can navigate through the environment with simple head movements and eye gaze. Python is used for visual processing, OpenCV is used for visualization and the Dlib library is used for detection of facial feature. The eye angle (EAR) is calculated to monitor blinking, which triggers a specific command. Furthermore, head motion is interpreted for guidance signals based on yaw angle. The wheelchair is controlled by an Arduino, which processes commands from Python scripts through a series of connections. The Arduino IDE code includes functions that control the wheelchair mechanism for forward, backward, left, and right tilting, as well as an ultrasonic sensor for detection of obstacle. Extensive testing shows that the system hears user commands is not touched reliably and translates into precise movement of the wheelchair. The iWheel project aims to provide affordable and accessible mobility solutions that maximize the quality and independence of life of individuals with mobility disabilities. The results show that the integration of eye tracking and voice control is a promising strategy for assistive technology, reducing the need for physical devices floor is reduced future development focuses on reducing the accuracy of tracking methods and expanding the functionality of the system to meet a wide range of user needs Focuses on the ability to engage behavioral devices.