IoT-Enabled Smart Healthcare Monitoring using Wearable Sensors

Abstract

The integration of the Internet of Things (IoT) with wearable sensors has transformed healthcare monitoring, enabling real-time, continuous, and personalized patient care. This study explores the state-of-the-art in IoT-enabled smart healthcare systems, emphasizing wearable physiological sensors for mobile monitoring of vital signs and activity patterns. We review developments in energy-autonomous wearable sensors capable of supporting continuous biosignal tracking with minimized reliance on external power sources, essential for pervasive, lowmaintenance healthcare devices arXiv. We also examine fog-assisted energy optimization frameworks, which mitigate computation and energy constraints of wearable sensors by offloading processing tasks to nearby edge nodes arXiv. Additionally, we assess privacy-preserving federated learning frameworks like FedHealth, which enable collaborative, yet privacy-conscious, deep learning across diverse wearable data sources arXiv. Complementing these technical advances, we review safety, security, and regulatory considerations shaping IoT wearable adoption, where data privacy, reliability, and compliance (e.g., GDPR and usability standards) dominate design imperatives JMIR Publications. Through synthesis of these themes, we propose a conceptual architecture integrating energy autonomy, edge-assisted processing, federated analytics, and privacy-by-design principles. This architecture promises low-latency, efficient, and secure health monitoring suited for real-world deployment. We conclude with research gaps: enhancements in sensor energy efficiency, seamless interoperability, user-centered design, and clinical validation—key directions for bringing IoT wearables from lab prototypes to impactful healthcare solutions.