<![CDATA[The demand for an effective and precise monitoring and control system for intravenous infusion therapy has increased due to concerns regarding medication errors and inefficiencies associated with current manual monitoring methods employed by nurses, particularly when caring for multiple patients across different rooms. This research aims to enhance intravenous infusion therapy by developing a real-time monitoring and control system. The system utilizes IoT technology and advanced sensors, including the load cell sensor for infusion volume detection, the FC-33 optocoupler sensor for precise infusion drop monitoring, and also a servo motor as an actuator to bend the infusion hose. Integrated with the NodeMCU ESP32 microcontroller, the system empowers healthcare professionals with the user-friendly DripControl+ app to remotely monitor and cont rol the infusion process. The results indicate a seamless collaboration among the system components. The FC-33 Optocoupler sensor exhibits an outstanding accuracy rate of 99.39%. The load cell sensor achieves an impressive 99.61% accuracy. The servo motor precisely follows predetermined positions. These outcomes effectively highlight the system's ability to accurately control the infusion drip rate with exceptional precision. The FC-33 optocoupler sensor and servo motor play crucial roles in achieving this accuracy. With an impressive average accuracy of 97.99%, the system has proven to be highly efficient. However, it should be noted that sudden changes in infusion speed could impact the accuracy of the readings. The future research could focus on refining the system's ability to respond to abrupt changes in infusion speed through advanced algorithms, such as machine learning.]]>
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