Smart Health Systems for Personal Health Management of Elderly People Using IoT and AI

Abstract

The rapid growth of the elderly population has introduced significant challenges to modern healthcare systems, necessitating the development of innovative and scalable solutions for continuous health monitoring and management. The integration of the Internet of Things (IoT), Internet of Medical Things (IoMT), Artificial Intelligence (AI), and wearable technologies has emerged as a transformative approach in smart healthcare systems. These systems enable real-time monitoring of vital health parameters such as heart rate, body temperature, blood pressure, and oxygen saturation, ensuring early detection of abnormalities and timely medical intervention. Smart health systems provide elderly individuals with enhanced safety, independence, and quality of life by allowing remote healthcare services within the comfort of their homes. Additionally, AI-driven analytics assist in predictive diagnosis, chronic disease management, and personalized healthcare recommendations. This paper explores recent advancements in IoT-based smart healthcare systems, focusing on their architecture, functionalities, and applications in elderly care. It also highlights key challenges such as data security, privacy concerns, interoperability, and system reliability. Finally, future research directions are discussed to improve the efficiency, scalability, and security of smart health monitoring systems for elderly populations.