Solar-Powered Autonomous Robotic Wheelchair with AI, IVRS, Facial Recognition, and Multi-Tasking Capabilities

Mobility limitations pose significant challenges for elderly and physically disabled people, particularly movement in various environments such as hospitals, airports, and large shopping malls. The initial stages of implementation and navigation are confined to Hospital environments. Therefore, this paper presents a solar-powered, autonomous robotic wheelchair integrated with Artificial Intelligence (AI), Interactive Voice Response System (IVRS), facial recognition, and multi-tasking capabilities to enhance user independence and reduce dependency on hospital staff. The wheelchair autonomously helps patients across main hospital areas, from reception to doctor consultations and pharmacy visits. The main features include AI-driven voice interaction, Internet of Medical Things (IoMT) based vital sign monitoring (temperature, heartbeat, ECG, SpO2), predefined path navigation, and real-time data management. To implement this, the paper proposes an implementation methodology with seven significant stages, covering system readiness, AI interaction, database management, vital monitoring, guided consultations, and pharmacy assistance. The wheelchair is powered by solar energy and built with various components like Raspberry Pi, BTS7960 motor drivers, ultrasonic sensors, IoMT sensors and a camera. The system emphasizes sustainability, accessibility, and efficiency in healthcare and public environments.