Real-Time Medical IoT for Continuous Glucose Monitoring

This research is about Continuous Glucose Monitoring (CGM) technology and its pivotal role in revolutionizing diabetes care. Leveraging data obtained from a comprehensive study focused on evaluating CGM’s efficacy in diabetes management, this study investigates the impact and potential benefits of CGM usage on patients’ health after collecting the real secondary data through online forms. It encompasses a diverse array of patient-centric variables, including medical history, medication intake, physiological parameters, and CGM-derived glucose monitoring.By integrating machine learning techniques and statistical analysis, this study aims to derive valuable insights into the interplay between CGM data patterns and real-time activities, patients’ physiological profiles, and diabetes management outcomes. The extracted features and processed data serve as a foundation for subsequent predictive modeling, classification, and regression analysis. This research aims to contribute to the expansion of knowledge regarding the effectiveness of CGM technology in diabetes treatment. By exploring correlations between CGM data, patient attributes, and clinical outcomes, this study endeavors to pave the way for personalized and optimized diabetes management strategies.