Infusion is a critical procedure in medical care that requires meticulous monitoring and control. Manual monitoring and control of infusion fluids are often ineffective and demand intensive attention from healthcare professionals. This study aims to design and develop a multi-sensor infusion monitoring and control system based on the Internet of Things (IoT). The research employs a research and development (R&D) methodology to ensure the continuity of the study. The system integrates three real-time infusion monitoring sensors: load cell sensor, optocoupler sensor, and speed IR LM393 sensor. Control is executed through the Blynk application, which adjusts the stepper motor to regulate the drip rate at three preset points: 26 dpm, 29 dpm, and 32 dpm. Test results indicate that the load cell sensor has an average error rate of 0.85%, the optocoupler sensor 1.13%, and the drip rate setting error is 2.32%, while the speed IR LM393 sensor shows 0% error. The overall system testing across 10 trials yields an average error rate of 1.30% and an average accuracy of 98.70%. When the volume falls below 50 ml, the sensor provides a notification to the Blynk application. When the volume is below 10 ml, the sensor sends a notification and the stepper motor will close. Data on volume, drip rate, and air bubble conditions are displayed on an LCD and the Blynk application, allowing healthcare professionals to monitor and control infusion fluids wirelessly.
Keyword: Infus, Load Cell, Optocoupler, Speed IR LM393, Blynk.