IoT-Assisted Smart Water Quality Prediction and Assessment in River Basins Using Machine Learning Models

The current water quality measurement methods involve extensive work force while capturing data only at set intervals. A concept of continuous water quality assessment and prediction using ML model assistance from IoT technology is introduced in this work. Multiple ML models underwent evaluation for determining four critical water quality measurements including pH alongside dissolved oxygen (DO), turbidity alongside biological oxygen demand (BOD). The research study demonstrates how IoT together with ML creates opportunities for effective environmental monitoring with improved decision-making processes.