Accuracy assessment and error decomposition of internet of things sensor: Low-flow conditions in Dorimcheon stream

Abstract

In recent years, a significant shift towards automation has arisen in the field of flow measurement. This study presents an Internet of Things (IoT) sensor-based flow measurement system designed to accurately measure and collect real-time flow rate data while reducing the need for manual labor and increasing safety. The system was tested in a stream located in Dorimcheon, where two different sensors were compared: the YF-S201 and Sontek FlowTracker2. The results indicate that the IoT sensor (YF-S201) is a viable option for measuring flow rate under low-flow conditions. However, it should be noted that the accuracy of the YF-S201 sensor is limited, with a standard uncertainty of 9.5% under low-flow conditions., while the FlowTracker2 had an uncertainty of 7.7%. An error decomposition analysis revealed that changes in the instrument accuracy were the largest contributors to the uncertainty in the YF-S201 sensor. The study also employed an ultrasonic sensor for measuring water levels, and the uncertainty analysis indicated that the sensor was suitable for this purpose with an acceptable level of accuracy.