A Low-Cost Radar-Based IoT Sensor for Noncontact Measurements of Water Surface Velocity and Depth

Abstract

We designed an out-of-water radar water velocity and depth sensor, which is unique due to its low cost and low power consumption. The sensor is a first at a cost of less than USD 50, which is well suited to previously cost-prohibited high-resolution monitoring schemes. This use case is further supported by its out-of-water operation, which provides low-effort installations and longer maintenance-free intervals when compared with in-water sensors. The inclusion of both velocity and depth measurement capabilities allows the sensor to also be used as an all-in-one solution for flowrate measurement. We discuss the design of the sensor, which has been made freely available under open-hardware and open-source licenses. The design uses commonly available electronic components, and a 3D-printed casing makes the design easy to replicate and modify. Not before seen on a hydrology sensor, we include a 3D-printed radar lens in the casing, which boosts radar sensitivity by 21 dB. The velocity and depth-sensing performance were characterised in laboratory and in-field tests. The depth is accurate to within ±6% and ±7 mm and the uncertainty in the velocity measurements ranges from less than 30% to 36% in both laboratory and field conditions. Our sensor is demonstrated to be a feasible low-cost design which nears the uncertainty of current, yet more expensive, velocity sensors, especially when field performance is considered.

A Compact, Low-Cost, and Low-Power Turbidity Sensor for Continuous In Situ Stormwater Monitoring

“…The turbidity sensor is able to operate under a 3.3 V power supply and communicate via a universal asynchronous receiver-transmitter (UART). The sensor circuit, as depicted in Figure 1 a, utilises an ATmega328P chip as the MCU due to its ease of use and familiarity in sensing applications [ 47 , 48 ]. The circuit includes one LED, one phototransistor, and a voltage regulator to match the nominal voltage of the infrared LED (1.65 V [ 49 ]).…”

Low-cost monitoring systems for urban water management: Lessons from the field

“…While the open science movement has improved access to low-cost monitoring system components and resources, implementing such technology still implies significant resources. A broad range of skills are needed for deploying monitoring systems, including coding, electrical and electronic engineering skills ( Catsamas et al, 2023 ), experience with DIY (e.g., building an enclosure and fixing hardware in the field), metrology (how to measure a quantity and how to assess sensor performance through calibration, uncertainty assessment, repeatability and reproducibility experiments), and data analysis (e.g., data verification, Fig. 1 ) ( Chan et al, 2020 ; Horsburgh et al, 2019 ).…”

“…First, a controlled laboratory experiment comparing the low-cost sensor's measurements to reference values will help qualify it and evaluate its performance, including range, accuracy, precision, reproducibility, and reliability ( Cherqui et al, 2020 ; Shi et al, 2021 ). Second, before and during field implementation, testing, calibration and periodic verifications of the system in real field environmental conditions will help characterize actual performance ( Catsamas et al, 2022 ; 2023; Shi et al, 2021 ). Field performance may differ from laboratory conditions due to environmental factors outside the range of those tested in the lab (e.g., temperature or humidity conditions, sunlight), a possibly different electrical setup (e.g., fluctuating power supply, rewiring to accommodate field conditions), and, importantly, a possible drift over time that might not have been detected in short-term laboratory testing.…”

A Compact, Low-Cost and Low-Power Turbidity Sensor for Continuous In-Situ Stormwater Monitoring

“…The turbidity sensor is able to operate under a 3.3 V power supply and communicate via a universal asynchronous receiver-transmitter (UART). The sensor circuit, as depicted in Figure 1a, utilises an ATmega328P chip as the MCU due to its ease of use and familiarity in sensing applications [47,48]. The circuit includes one LED, one phototransistor, and a voltage regulator to match the nominal voltage of the infrared LED (1.65 V [49]).…”