Abstract

The growing aging population presents significant challenges to healthcare systems, particularly in
monitoring and managing elderly health. Internet of Things (IoT) technology has emerged as a promising
solution for continuous, real-time health monitoring of elderly individuals, offering potential improvements
in patient outcomes and reducing healthcare burdens. This paper presents a comprehensive IoT framework
designed for elderly health monitoring, which identifies key physiological and environmental parameters
critical for assessing the well-being of the elderly. These parameters include heart rate, blood pressure, body
temperature, motion, and ambient environmental factors. The framework leverages advanced IoT sensors,
data collection, and transmission technologies to monitor these parameters continuously. Additionally, it
integrates Fog Computing to enhance the real-time processing, analysis, and decision-making capabilities of
the system. By processing data closer to the edge, Fog Computing minimizes latency, optimizes bandwidth
usage, and ensures faster response times, which are critical for elderly care. This study explores the
synergistic combination of IoT and Fog Computing to offer improved health outcomes for the elderly,
ensuring timely interventions, early detection of health anomalies, and personalized care management. The
proposed framework is evaluated in terms of its scalability, flexibility, and effectiveness in delivering
actionable insights. Overall, this paper provides a holistic approach to elderly health monitoring, emphasizing
the need for an integrated, real-time, and efficient system to address the unique healthcare challenges posed
by the aging population.