IoT-Based Insulin Pump Design Analysis Using Flowrate Monitoring

The management of diabetes, particularly for individuals requiring insulin therapy, presents significant challenges
in ensuring accurate and timely insulin delivery. Traditional insulin pumps often lack the precision and adaptability needed for
effective glucose control, leading to potential complications. This study addresses these issues by developing an IoT-based
insulin pump that utilizes flowrate monitoring to enhance the accuracy of insulin administration. The research employed the
ESP8266 microcontroller for data processing and control, coupled with the SLF3S-0600F liquid flow sensor to monitor insulin
flow rates. The Blynk application was utilized for remote monitoring and dose adjustments, allowing users to manage their
insulin delivery conveniently via an Android device. The experimental methodology involved conducting five repeated
measurements to assess flow rate accuracy, volume delivery, and motor speed. Results indicated that the insulin pump achieved
a flow rate measurement error of only 0.0051% at a setting of 1.5 ml/min, while the largest error recorded was 0.0391% at 3
ml/min. Additionally, the volume measurement error was minimal, with the smallest error at a 2 ml setting of 0.016% and the
largest at 1 ml with an error of 0.152%. The average motor speed was recorded at 21.22 rpm for auto settings and 49.88 rpm for
bolus settings. In conclusion, the developed IoT-based insulin pump demonstrates significant potential for improving diabetes
management through precise insulin delivery and real-time monitoring capabilities. The integration of IoT technology not only
enhances the accuracy of insulin administration but also provides users with greater flexibility and control over their treatment. This research contributes to the ongoing efforts to innovate diabetes care solutions, ultimately aiming to reduce the risk of long-
term complications associated with the disease.