In a fast-paced world, caring for the elderly and disabled can be challenging, while they strongly desire independence. Various initiatives like joystick, voice, and vision-based controls have enhanced mobility, with vision-based systems offering greater autonomy for users with severe motor disabilities. However, existing systems often neglect users’ mental and emotional well-being. Our system addresses this gap by integrating eye movement and facial expression tracking via a webcam, processed using deep learning to drive the wheelchair. Ultrasonic sensors ensure obstacle detection and safer navigation, replacing traditional Global Positioning System (GPS) systems. Additionally, continuous facial expression monitoring aids in mental health analysis, promoting both intuitive mobility and emotional care, significantly improving quality of life, and reducing caregiver dependence.