Analyzing Groundwater Quality in Healthcare: A Digital Twin Framework Approach

Assessing groundwater resources is crucial for managing water contamination and preventing illnesses. Effective water quality evaluation requires continuous real-time parametric data collection. Previous systems have failed to incorporate unpredictability and flexibility, relying on static models that lead to errors. This study introduces a novel Virtual Twin-inspired Water Quality System (VTWQS) for real-time water quality assessment, addressing these limitations and providing quantitative insights into health risks. The validity of the method is confirmed using experimental data from the Maheru surveillance post in Punjab, India. Results indicate strong performance in water quality evaluation, with an overall prediction accuracy of 94.14%, recall of 91.47%, precision of 93.74%, and f-measure of 92.37%. The system also demonstrates lower computing latency, higher reliability, and increased dependability, making it an effective choice for accurate water quality forecasts.