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Low-cost IoT based system for lake water quality monitoring

PLoS ONE 2024 13 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 60 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Kartikay Lal, Sanoj Menon, Sanoj Menon, Frazer Noble, Khalid Mahmood Arif

Summary

This study built a low-cost sensor system using Internet of Things technology to monitor basic water quality parameters like turbidity, pH, and dissolved oxygen in lakes. While not focused on microplastics specifically, affordable real-time water monitoring tools like this could eventually be adapted to track microplastic contamination. Better water quality monitoring is an important step toward understanding and reducing the pollutants, including microplastics, that end up in drinking water sources.

Water quality monitoring is a critical process in maintaining the well-being of aquatic ecosystems and ensuring growth of the surrounding environment. Clean water supports and maintains the health, livelihoods, and ecological balance of the ecosystem as a whole. Regular assessment of water quality is essential to ensure clean and reliable water is available to everyone. This requires regular measurement of pollutants or contaminants in water that can be monitored in real-time. Hence, this research showcases a system that consists of low-cost sensors used to measure five basic parameters of water quality that are: turbidity, total dissolved solids, temperature, pH, and dissolved oxygen. The system incorporates electronics and IoT technology that are powered by a solar charged lead acid battery. The data gathered from the sensors was stored locally on a micro-SD card with live updates that could be viewed on a mobile device when in proximity to the system. Data was gathered from three different bodies of water over a span of three weeks, precisely during the seasonal transition from autumn to winter. We adopted a water sampling technique since our low-cost sensors were not designed for continuous submersion. The results show that the temperature drops gradually during this period and an inversely proportional relationship between pH and temperature could be observed. The concentration of total dissolved solids decreased during rainy periods with a variation in turbidity. The deployed system was robust and autonomous that effectively monitored the quality of water in real-time with scope of adding more sensors and employing Industry 4.0 paradigm to predict variations in water quality.

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