Artificial intelligence powered glucose monitoring and controlling system: Pumping module

Figure 1 The block diagram encompasses a comprehensive diabetes management system: A glucose sensing component utilizes a glucose sensor, feeding data to an artificial intelligence driven decision system, which then triggers an insulin dispensing mechanism, forming an integrated framework for precise and automated diabetes control. AI: Artificial intelligence.

Figure 2 The flow chart illustrates a closed-loop diabetes management system that optimizes patient care.

Figure 3 Wi-Fi controller for the pumping system.

Figure 4 Graph depicts the dynamic relationship between glucose concentration and time, revealing fluctuations that highlight the critical need for precise glucose management in diabetes care.

Figure 5 Graph showcases the correlation between glucose concentration and basal insulin dosage, providing insights into the effectiveness of the basal insulin regimen in maintaining stable glucose levels.

Figure 6 Graph highlights the impact of high glucose concentrations, revealing the critical importance of effective interventions to prevent hyperglycemia-related complications in diabetes management, but after a certain period of time glucose levels increases abnormally.

Figure 7 Graph illustrates the dynamic interaction between meal intake and basal insulin dose, showcasing the intricate balance required for optimal glucose control in diabetes management.

Figure 8 Graph demonstrates the performance of the proportional-integral-derivative controller, showcasing its ability to efficiently regulate a system's output by continuously adjusting the control parameters.

Figure 9 Graph illustrating the combined effect of proportional-integral-derivative controller with basal dose which is measured to evaluate the ability to effectively regulate glucose levels.