A Multi-Functional AI-Enabled Robotic Doctor for Intelligent Patient Monitoring and Autonomous Healthcare Support with Adaptive Human-Centered Interaction

Abstract

The increasing demand for contactless and uninterrupted healthcare has accelerated the need for intelligent robotic systems capable of supporting clinical tasks with minimal human exposure. This research presents a complete design and architectural framework for an AI-Enabled Robotic Doctor developed using Tinkercad, integrating vital-sign monitoring, autonomous navigation, room detection, voice interaction, AI-driven priority assessment, medication assistance, and remote doctor communication into a unified operational model. The methodology outlines structured healthcare requirement analysis, functional decomposition, workflow modeling, and conceptual system validation, demonstrating how the robot can interpret vital data, navigate safely using AI-based visual recognition and obstacle avoidance, communicate naturally with patients, and support medication management. The system architecture defines six coordinated layers responsible for monitoring, decision-making, interaction, assistance execution, and documentation. Conceptual evaluation shows that the proposed model can enhance patient monitoring efficiency, reduce clinical workload, and improve safety in high-risk medical environments. The 3D structural design validated ergonomic feasibility and modular organization. Future work includes software simulation of navigation and interaction behaviours. Followed by hardware realization with biomedical sensors and embedded controllers to transition this design into a fully operational autonomous healthcare robot. The study establishes a comprehensive foundation for advancing robotic healthcare support systems in modern clinical settings.