AI And IoT Convergence For Real-Time Healthcare Analytics And Personalized Patient Care Solutions

Abstract

The traditional healthcare model is being disrupted by the convergence of Artificial Intelligence (AI) and the Internet of Things (IoT), giving rise to the Artificial Intelligence of Things (AIoT). This review article investigates the architectural and clinical foundations of AIoT-enabled healthcare, evaluating its capacity for real-time analytics and personalized patient care. We analyze a multi-layered framework encompassing medical-grade sensing, high-speed 5G/6G communication, and the intelligence core where Cloud and Edge AI synchronize. Central to our study is the role of predictive modeling and digital twins in facilitating precision medicine and smart medication management. The article explores specific clinical applications in chronic disease management and post-operative remote care, while addressing critical challenges in data security, privacy-preserving federated learning, and algorithmic bias. By synthesizing implementation strategies with future trends—such as ambient intelligence and quantum-accelerated drug discovery—this study provides a comprehensive roadmap for the digital transformation of medicine. Ultimately, we demonstrate that the AIoT paradigm is the essential mechanism for transitioning to a proactive, value-based healthcare system that delivers tailored, real-time solutions to patients globally.

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