Using R To Analyse An loT Connected HEALTH MONITORING SYSTEM

We delve into the deployment of IoT for health monitoring using the statistical programming language R. The primary aim of the system developed here is to harness R’s analytical prowess to process and analyse real-time health data acquired from diverse IoT devices.

- DR MAHESWARI R.

The health monitoring system proposed here incorporates wearable sensors, mobile applications, and cloud-based infrastructure to establish a seamless connection between individuals and healthcare providers. Wearable devices, equipped with sensors, continuously capture vital health metrics such as heart rate, blood pressure, temperature, and activity levels. These metrics are transmitted to a central server via the internet, where R-based algorithms are utilised for real-time analysis.

R plays a pivotal role in the processing of raw health data, execution of statistical analyses, and generation of meaningful insights. Leveraging the language’s extensive library of statistical functions, visualisation tools, and machine learning capabilities facilitates the development of predictive models aimed at identifying potential health issues. Additionally, R enables the creation of personalised health profiles and trend analyses for individuals, fostering proactive healthcare management. The architecture also encompasses a user-friendly mobile application, providing individuals with real-time access to their health information.