Infusion bottle monitoring system based on IoT

In the field of healthcare, the intravenous fluid infusion process has become a crucial method in patient recovery. However, monitoring and replacing infusions pose challenges for hospitals due to limited medical staff and time constraints. Currently, infusion control is still manual, leading to risks such as delayed handling when the infusion is depleted and the potential for blood clot formation. Therefore, the use of technology is essential to address these issues. This research aims to design and create a monitoring and alert device for real-time patient infusion bottle conditions based on the Internet of Things (IoT) related to weight, utilizing a website. The ON/OFF method serves as the primary framework for designing and implementing the IoT-based patient infusion bottle monitoring system. The research results include an infusion pole equipped with Load cell sensors and a website application capable of monitoring the patient's infusion bottle conditions in the nurse's room. The conclusion drawn from the study is a comparison of sensors with digital scales, showing a percentage error of 0.11% for Load cell A and 0.14% for Load cell B. The average measurement tolerance at different infusion flow rates exhibits variation. At slow infusion rates, the average tolerance for infusion A is -0.66%, while for infusion B, it is -0.06%. At moderate infusion rates, the average tolerance for infusion A is -0.97%, and for infusion B, it is -0.66%. At fast infusion rates, the average tolerance for infusion A is -0.13%, and for infusion B, it is -0.04%.