Real-time water quality monitoring of an artificial lake using a portable, affordable, simple, Arduino-based open source sensor

Abstract

Water quality assessment is vital to identify existing problems and any changes that emerge in water sources over a period of time. Conventional water quality monitoring systems remain to be limited to on-site sample collection and further analysis in environmental laboratories. The progress in Arduino-based low-cost and open-source hardware has paved the way for the development of low-cost, portable, and on-site measuring platforms. In this work, we have assembled an Arduino-based open-source water testing platform out of commercially available sensors and controllers. The water testing system was powered by a 9 V battery and had the capability of measuring water turbidity, acidity, and temperature on-site in real-time. The calibration and validation studies were carried out to assess the measurement capabilities of turbidity and pH sensors in the lab using calibration samples and UV-Vis-NIR absorption spectroscopy. The water quality platform was tested in an artificial lake that is located at Sabanci University Campus (Istanbul, Turkey), which serves as a reservoir for treated wastewaters and rainwater. Untreated wastewater samples were collected from the wastewater treatment station of the university for comparison. The measurements performed on several locations along the coast of the artificial lake were also validated in the laboratory. The water testing platform showed significant potential for miniaturization and portability of such analytical platforms for on-site environmental monitoring.

Real-Time Water Quality Assessment via IoT: Monitoring pH, TDS, Temperature, and Turbidity

“…Toxic substances, heavy metals, and both organic and inorganic particles are commonly found, accompanied by physical, chemical, and biological contaminants like bacteria and viruses [3]. Disturbingly, such pollutants are believed to account for nearly 1.5 million annual deaths in children below five, primarily from ailments such as diarrhea [4]. This revelation is further exacerbated when considering that a mere 3% of Earth's water resources are freshwater, and these resources are being contaminated at an accelerating pace [5].…”

An Artificial Intelligence Approach for Italian EVOO Origin Traceability through an Open Source IoT Spectrometer

“…NIRS, paired with chemometric techniques, were satisfactorily used for olive oil authentication and screening [28][29][30][31][32][33]. Generally, using both software and hardware, open source infostructure solutions potentially result in significant cost reduction, making the scientific tools available for a wider audience [34]. Following this path, results such as the prediction of qualitative parameters, the evaluation of indices of different fruit and vegetable products [35], the authentication of olive oil according to the variety and geographical origin [36], and the detection of adulteration through acidic composition [37] were achieved using visible/near-infrared (VIS-NIR) spectroscopy.…”