IoT-Based Smart Home Healthcare Monitoring System Using Machine Learning Algorithms

The purpose of this study is to demonstrate an Internet of Things (IoT)-based smart home healthcare monitoring system that is run by machine literacy algorithms. An opportunity to update healthcare monitoring has arisen as a result of the spread of Internet of Things (IoT) devices. This is especially true when it comes to monitoring patients within the comfort of their own homes. To gather real-time data on vital signs and the conditioning of diurnal life from cases, our proposed system makes use of Internet of Things detectors. In addition, machine learning algorithms are utilized to analyze this data, which enables the implementation of proven and forward-thinking healthcare monitoring. The system can adapt to the activities of individual cases by continuously learning, which allows it to identify anomalies and provide predictions about implicit health problems. The incorporation of machine literacy not only improves the precision of health monitoring but also makes it easier to provide early intervention and preventative care, which ultimately leads to the resolution of patient difficulties and a reduction in the expenses of healthcare. This investigation makes a crucial contribution to the rapidly developing field of Internet of Things (IoT)-)-enabled healthcare systems, illustrating the potential for technology to transform conventional approaches to the delivery of healthcare.