Leveraging IoT for Personalized Diabetes Management: Predictive Analytics and Remote Monitoring

— Diabetes is a chronic disease that requires continuous monitoring and timely interventions to prevent complications. However, traditional diabetes management methods often rely on intermittent measurements and patient self-reporting, which can lead to delayed responses and suboptimal care. The integration of the Internet of Things (IoT) presents a transformative opportunity, enabling real-time monitoring and predictive analytics for personalized management of diabetes. This paper examines the intersection of the Internet of Things (IoT) and diabetes management, with a focus on predictive analytics and remote monitoring. Diabetes, a global health challenge, demands continuous monitoring and timely interventions to maintain glucose levels within a healthy range. IoT-enabled devices, such as Continuous Glucose Monitoring (CGM) systems, offer real-time data transmission and analysis, revolutionizing diabetes care. This study introduces an intelligent system that leverages the Internet of Things (IoT) and advanced algorithms to enhance diabetes monitoring. The system collects data from IoT devices, processes it using machine learning techniques, and provides actionable insights for patients and healthcare providers. By harnessing the power of the Internet of Things (IoT), this system aims to redefine diabetes management and enhance patient outcomes. Experimental results demonstrate that the predictive model achieves 86% accuracy in identifying diabetes risks, showcasing its potential as a decision-support tool.