Accurate measurement of streamflow is fundamental for water resources management, ecological conservation, flash flood early warning, and climate change impact studies. Traditional gauging stations, while effective, are costly and difficult to deploy in mountainous streams. Although Parshall flumes can be equipped with ultrasonic water level sensors and telemetry systems for real-time monitoring, their installation requires fixed hydraulic geometry, calibration, and maintenance, which may be impractical in small, remote, or temporary stream contexts. This study presents a proof of concept on the usage of IoT for automatic streamflow measurements using commercial off-the-shelf (COTS) hardware. The system is designed, implemented, and field-tested as a low-cost, solar-powered IoT device tailored to small-order streams and headwater tributaries. At its core is the hall-effect YF-S201 flow sensor. Although primarily designed for closed-conduit applications, the sensor was tested in a controlled setup where stream water was diverted into a short pipe section, enabling continuous monitoring and calibration against known discharge. The sensor can be easily incorporated with a variety of boards (Arduino, Raspberry, OrangePi, etc.) with or without wireless capabilities, based on the usage scenario and user requirements (demand for cloud storage, virtual dashboards, etc). This paper provides analytical details on the design and validation of a low-cost, solar-powered streamflow measurement system based on a water flow sensor, using wireless communications, and cloud storage based on an ESP32 board, PostgreSQL, and a web interface. The device was tested in a simulated environment. Results indicate the proposed device reliably tracks flow variability, while offering portability, energy autonomy, and cost efficiency, and may serve as a feasible alternative for low-infrastructure, temporary deployments.
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Low-Cost IoT sensor for real-time streamflow measurements
Published:
06 November 2025
by MDPI
in The 9th International Electronic Conference on Water Sciences
session Remote Sensing, Artificial Intelligence and New Technologies in Water Sciences
Abstract:
Keywords: hydrological IoT; COTS sensor platforms; solar-powered telemetry; wireless monitoring; embedded edge computing
