An IoT-Based Remote Patient Monitoring Architecture Integrating Edge AI and Blockchain for Chronic Disease Management

Abstract

The maintenance of chronic disease requires a continuous health checkup to prevent complications and minimize the number of times one goes to the hospital. The Internet of Things (IoT) is utilised to develop Remote Patient Monitoring (RPM) systems that assist doctors in gathering and reviewing health information in real-time. Although these systems have the potential to enhance care delivery, they are still affected by challenges such as delay of communication, poor security, system incompatibility and ineffective usage of the systems in the zones with weaker internet connections. The current paper introduces an IoT-based RPM system with six layers. It has Edge Artificial Intelligence (AI) to search promptly through anomalous health information, an impregnable blockchain to secure and conserve health records securely, and a digital twin design to assist in making forecasts about the future. This system was tested using a Python simulation mechanism in which sample health data were used. The performance indicated rapid identification of issues within 10.46 milliseconds and great data security based on blockchain. Figures and charts demonstrated that the system could sort out the normal and abnormal health data accurately and assist the physicians in making superior judgments. This design fixes most of the issues with the existing RPM system design and provides a secure, intelligent, and adaptable mode of chronic disease management.