DESIGN AND IMPLEMENTATION OF A TELEHEALTH MONITORING SYSTEM INTEGRATING IoMT AND ARTIFICIAL INTELLIGENCE TO ENABLE EARLY DETECTION AND TREATMENT OF DIABETES

Abstract

This paper outlines the development and implementation of a cutting-edge TeleHealth monitoring system that leverages the synergy of the Internet of Medical Things
(IoMT) and advanced Artificial Intelligence (AI) technology. The system seamlessly connects terminal medical devices to cloud platforms, enabling real-time access for
healthcare professionals, anytime and anywhere. This innovation particularly benefits patients in remote areas, disabled elderly individuals, people with limited mobility, and
medical units situated in isolated regions, islands, and border areas etc. The terminal devices employed in this system exhibit precision and reliability in measuring patients'
health parameters. These measurements are conveniently transmitted to a base station through SMS messages, subsequently linking to the Internet and routing through the
cloud to a centralized server. From there, doctors gain access to the data on their computers, facilitating remote monitoring, diagnosis, and treatment. Furthermore, the paper
details the establishment of a comprehensive dataset for public health and the creation of a big data platform focused on diabetes. Artificial intelligence is employed to enable
early detection and treatment of diabetes, showcasing the potential for advanced analytics in improving healthcare outcomes.