IoT-inspired Healthcare-oriented Water Quality Analysis

Analyzing groundwater is crucial for minimizing contamination and preventing health risks. Real-time water quality assessment requires evaluating multiple parameters, yet many existing methods rely on time-invariant models, which can lead to inaccuracies and inconsistencies in impurity detection. To address this, the current research proposes a hybrid system based on a Two-Actor Game-Theoretic decision model for time-sensitive water quality evaluation. A novel metric, Water Quality Measure (WQM), is introduced to quantify risk and vulnerability to human health. The framework was validated using real-time data acquired from a remote location. Experimental results demonstrate improved efficiency with Sensitivity of 94.75%, Specificity of 95.45%, and Precision of 95.56%, indicating strong predictive reliability. Additionally, it recorded low computational latency (15.62s), and high Reliability (90.18%) and Stability (75%), supporting its effectiveness for accurate and real-time water quality forecasting.