IoT Enabled Healthcare Framework Using Edge AI and Advanced Wearable Sensors for Real Time Health Monitoring

Abstract

The Internet of Things (IoT) is redefining healthcare by enabling real-time monitoring, analytics, and diagnostics, significantly enhancing patient outcomes and reducing response times in critical scenarios. This paper presents a state-of-the-art IoT-enabled healthcare system that integrates wearable sensors for continuous heart rate and blood pressure monitoring. The framework collects physiological data from patients, transmits it to an IoT cloud for secure storage, and performs advanced analytics to generate real-time health alerts and reports for clinicians. The system architecture emphasizes reliability, scalability, and security, addressing key challenges in IoT healthcare implementations. A robust cloud-based analytics engine processes sensor data using optimized algorithms, ensuring high accuracy and reduced latency in generating actionable insights. Performance evaluations demonstrate the system's efficacy, achieving data transmission latencies below 50 milliseconds, accuracy levels exceeding 95% in comparison with standard clinical devices, and optimal resource utilization in diverse network conditions. Comparative analysis with existing IoT healthcare solutions highlights significant improvements in throughput, reliability, and scalability. This work provides a foundational framework for future advancements in AI-powered predictive diagnostics, expanded sensor integrations, and enhanced security protocols for patient data.