Implementation of a Real-Time Dashboard for Monitoring Backflow Detection in IoT-Based IV Lines

Abstract

Continuous monitoring of patients receiving intravenous therapy is crucial to prevent blood from flowing back into the IV line (reflux), which can endanger patient safety. This study aims to design and develop an Internet of Things (IoT)-based monitoring device capable of detecting blood backflow in the IV line and presenting data in real-time via a web-based dashboard. The system utilizes a TCS3200 color sensor to detect specific color changes in the infusion fluid when blood enters the line. Data obtained from the sensor is processed by an ESP8266 microcontroller and transmitted to a Flask-based server via the HTTP protocol, then visualized on a Dash-based web dashboard. Experimental testing was conducted through 50 trials under various ambient light conditions. The test results show that the system achieved a 100% accuracy rate in differentiating clear infusion fluid from blood backflow. Furthermore, the system demonstrated a rapid data transmission response with an average latency of 1.5 to 2.2 seconds to trigger notifications on the medical staff's dashboard. This device successfully minimizes the risk of blood coagulation and is expected to improve healthcare efficiency and patient safety in medical facilities.