Optimization of Internet of Things-Based Infusion Monitoring and Control System (OSPKI - IoT)

Nurses have an important role in patient care in hospitals, but excessive workload can cause errors in monitoring IV fluids. This research aims to develop an Internet of Things (IoT) based infusion monitoring and control system to increase efficiency and accuracy in managing infusion fluids. The system developed is capable of monitoring the volume of infusion fluid, counting drops per minute, and controlling the infusion speed automatically, as well as connecting to a database for online monitoring. The research method uses an experimental method with Waterfall model-based system development, which includes the stages of requirements analysis, system design, implementation, testing, and maintenance.. Test results show that the system can work accurately in monitoring various types of infusion fluids with a low error rate. It is hoped that the development of this system can reduce the risk of infusion monitoring errors and improve patient safety in hospitals. The novelty of this study lies in the integration of IoT-based infusion drip speed control automation in real time via a website with sensor accuracy below 1%, which has not been widely implemented in similar studies in Indonesian clinical settings.