<p>➀ This article explores the implementation of an IoT-based health monitoring system using the statistical programming language R. The system aims to process and analyze real-time health data from various IoT devices, with a focus on predicting heart attack risks.</p><p>➁ The proposed system integrates wearable sensors, mobile applications, and cloud-based infrastructure to connect individuals with healthcare providers. R's analytical capabilities, including statistical functions, visualization tools, and machine learning models like GLMs, random forests, and decision trees, are utilized to generate insights and predictive models.</p><p>➂ The system emphasizes data security and privacy, incorporating encryption and authentication mechanisms. It also includes a user-friendly mobile app for real-time health monitoring and personalized feedback.</p>