Rapid, Portable and Low-Cost Water Quality Sensor Using Artificial Intelligence
The project addresses the limitations of traditional water treatment methods by employing artificial intelligence, rapid-prototyping, and biodetection techniques to detect Enterococcus faecalis and Escherichia coli in water samples. Traditional methods are costly, time-consuming, and reliant on trained personnel and equipment, with results taking days and water quality conditions potentially changing during analysis.
