An Internet of Things-enabled system for monitoring multiple water quality parameters

Water quality plays a vital role in sustainable aquaculture. Fish life cycles are solely dependent on the water they live. Regular monitoring of water quality parameters helps maintaining and taking necessary measures to ensure healthy and sustainable fisheries efficiently. Therefore, developing a low-cost, low-power, highly sensitive sensor and sensing system for water quality monitoring is needed for innovative aquaculture. Fish lives are dependent on various parameters, and among those most crucial parameters are temperature, pH, nitrate, phosphate, calcium, and magnesium. This research proposes a novel multifunctional interdigital sensor for monitoring all these essential factors. The sensor is fabricated using mold-based casting method. The substrate is formed using polydimethylsiloxane (PDMS), and interdigital electrodes are developed using multi-walled carbon nanotubes (MWCNTs). The sensor is characterized for multiple parameters determination using electrochemical impedance spectroscopy (EIS) method. The proposed sensor can detect and differentiate a wide range of temperature (0-50°C), pH (1.3-12.4), nitrate (0.1-25ppm), phosphate (0.1-25ppm), calcium (1-200ppm), and magnesium (1-200ppm). An IoT-enabled autonomous system is also developed for monitoring water quality from any remote location. An intelligent data processing algorithm is also developed using the K-nearest neighbor method to predict each water quality parameters’ value in actual water samples. The proposed sensor’s results are repeatable and stable and highly potential for innovative aquaculture for continuous water quality monitoring.