An AI-Assisted Smart Healthcare System Using 5G Communication

This study has articulated and evaluated an AI- Assisted Smart Healthcare System that leverages the synergy of IoT sensing technology, artificial intelligence, and a multi-tier Edge-Fog-Cloud computational architecture to redefine the boundaries of modern remote patient monitoring. By disaggregating the data processing pipeline across geographically distributed computational tiers, the system achieves a favorable balance between real-time responsiveness and analytical depth, enabling both rapid anomaly alerting and nuanced longitudinal health trend analysis. The implementation results substantiate the architecture's capability to deliver persistent physiological monitoring, proactive disease identification, and intelligent clinical guidance while upholding stringent data security standards through lightweight cryptographic mechanisms. The AI-driven inference layer proves particularly impactful, transforming streams of raw sensor readings into actionable medical intelligence that can supplement and augment physician expertise. In summary, the proposed system represents a meaningful step toward the realization of intelligent, secure, and patient-centered healthcare delivery, with demonstrable advantages over both traditional and existing IoT-based monitoring paradigms in terms of responsiveness, predictive capability, and data protection.

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