Remote Patient Health Monitoring Using Iot And Artificial Intelligence

Abstract

There is a chance for extremely intelligent and clever IoT-based use cases in the modern period thanks to developments in ICTs like Cyber-Physical Systems (CPS), 5G cellular technology, and the Internet of Things (IoT). As IoT enables Ambient Assisted Living (AAL), Mobile Health (mHealth), and Electronic Health (eHealth), one such use case with a significant social impact is healthcare. People devote a large portion of their income to their health. In addition to resulting in patient deaths, traditional healthcare services are prone to delays, waste of time, and financial loss. When used in conjunction with the IoT's intelligence and prediction capabilities, regular Remote Patient Monitoring (RPM) at home, work, or at a hospital can help individuals who specifically require it overcome obstacles presented by traditional healthcare facilities. Wearable technology, sensor networks, and other digital infrastructure are used in IoT-based RPM can serve as a precursory warning system for approaching situations that, if ignored or care is postponed, could result in serious health problems or even patient death. Doctors can receive real-time patient vital signs through wearable devices (biosensors) with IoT integration. That way, medical professionals can start treating patients right away. The term "RPM" refers to this occurrence, which has the potential to reduce wait times, save healthcare expenses, and enhance patient comfort and service quality. In order to implement a Remote Patient Monitoring System (RPMS) with data analytics capabilities, this paper aims to develop an Internet of Things (IoT) and Artificial Intelligence (AI) enabled framework. We implemented RPM for data collection and proposed an algorithm for disease diagnosis. Our experimental results revealed that our method outperforms existing methods.