Improving Healthcare with Remote Patient Monitoring and Real-Time Data Analytics Using IoT

Abstract: The Internet of Things (IoT) is powering Remote Patient Monitoring (RPM), which is changing healthcare by letting data be collected, analysed, and decisions made in real time. This essay looks at how IoT-based RPM systems improve care for patients, lower the number of times they have to go back to the hospital, and make the best use of healthcare resources. RPM systems constantly check important health indicators like heart rate, blood pressure, glucose levels, and oxygen saturation by using personal sensors, smart devices, and cloud computing. They send real-time data to healthcare providers. A lot of data about patients is processed by advanced analytics and machine learning algorithms. These algorithms find insights that can be used to take action and predict possible health risks before they become problems. The study focusses on how edge and fog computing can help ensure low-latency data handling, which makes the system more reliable and efficient. Blockchain technology and standardised standards help solve problems like data security, portability, and scaling. This makes patient data more private and helps systems work together better. Case studies show that RPM works well for controlling chronic diseases, recovering from surgery, and caring for the old, showing big changes in patient results and cost saves. In addition, using AI allows for predictive analytics, which makes treatment plans more personalised and gives doctors the power to make decisions based on data.