Physics Informed Machine Learning for Electrical Sensing and Prediction of Heavy Metal Contamination in Water
Access to safe drinking water remains a global challenge, with approximately 2.1 billion people lacking safely managed water services. Continuous, low-cost monitoring of heavy metal contamination is limited because conventional techniques such as atomic absorption spectroscopy (AAS) and inductively coupled plasma mass...