The Vocal Vision system introduces an innovative approach to enhancing electric wheelchair maintenance and control. It utilizes a network of sensors embedded within the wheelchair's wheels to gather real-time data on tire pressure, temperature, tread wear, and alignment. This data is wirelessly transmitted to a central control unit. Advanced algorithms, incorporating machine learning and predictive analytics, analyze the data to detect irregularities and predict maintenance needs. Users can control direction, speed, and perform complex maneuvers with precision using voice commands and eye gestures. The wheelchair integrates OpenCV for eye gesture recognition and Google Speech Recognition API for voice commands, enabling intuitive control methods. This proposed method introduces a new assistive technology for individuals with disabilities, leveraging cutting-edge technologies.