A Low-Cost LoRa Optical Fluorometer–Nephelometer for Wireless Monitoring of Water Quality Parameters in Real Time
Phytoplankton are crucial for aquatic ecosystems; however, their overgrowth, or blooms, is rising due to climate change and pollution, threatening ecosystems and public health. Current commercial water quality sensors are often expensive, lack wireless capabilities, and depend on proprietary software, making them inaccessible to resource-limited research communities.
Several low-cost, Internet of Thing (IoT)-based water quality monitoring solutions have been developed, incorporating turbidity, chlorophyll-a, or phycocyanin sensors. However, many of them lack direct, continuous measurement capabilities. Also, in-situ sensors with real-time wireless data transmission capabilities are rarely explored.
The researchers present a low-cost, portable, IoT-enabled water quality monitoring device based on the open-source designs. It measures key water quality parameters like temperature, turbidity, phycocyanin, and chlorophyll-a using a device called a fluorometer-nephelometer. The device features a 3D-printed housing designed to hold its optical components. It includes three distinct light-emitting diodes (LEDs) that excite specific wavelengths and silicon photodiodes for detection: amber (590nm) for phycocyanin, blue (465nm) for chlorophyll-a, and near-infrared (870nm) for turbidity. The photodetectors are positioned orthogonally to minimize interference and improve accuracy.
A peristaltic pump is utilized to circulate the water sample through a polymethylmethacrylate cuvette, enabling consistent sample flow and accurate sensor readings. The electronic components, such as the circuit board, motor drivers, data storage unit, and pump, are housed inside a Pelican waterproof case. The system utilizes LoRaWAN, a low-power, long-range wireless communication protocol, to facilitate the transmission of water quality data collected by field-deployed fluorometer-nephelometers to a cloud-based server via a LoRa gateway, enabling data transmission over distances exceeding 2.4 km.
The system underwent a 12-day trial monitoring temperature, turbidity, phycocyanin, and chlorophyll-a. The temperature sensor showed higher accuracy (0.75°C deviation) than a commercial sensor. The turbidity sensor provided a linear response, detecting up to 200 FTU with a 3 mm aperture and 100 FTU with a more sensitive 4 mm aperture. The phycocyanin sensor measured 0.025–2.5 mg-PC/L (R² up to 0.9987) with minor, correctable interference. The chlorophyll-a sensor detected 1–50 µg-Chl-a/L (R² ≥ 0.9946) with minimal interference.
The customizable, open-source design of the sensor enables modification of hardware and software to adapt to diverse applications. It can be deployed for single-point measurements and distributed sensing networks, providing real-time data that can be transmitted to remote servers for analysis or stored locally. For instance, sensitivity can be lowered in nutrient-rich waters with algal blooms, while turbidity measurements in riverine settings can be improved through adjustments or added components. This flexibility makes the system suitable for both short-term studies and long-term environmental monitoring, aiding in the understanding and management of aquatic ecosystems.
The system's limitations, such as LoRaWAN range, sensor sensitivity to sediments and biofouling, and battery life, can be addressed by adjusting the spreading factor, optimizing transmission power, replacing the cuvette regularly, using solar power, and implementing low-power pumps. Future work should emphasize continuous field deployment and smart IoT network integration. However, this innovative solution offers a promising approach to improving water quality management and protecting aquatic ecosystems.