IoT-based real-time monitoring of river water quality: a case study of the Selangor River

Abstract

Monitoring river water quality is crucial for preserving freshwater ecosystems, ensuring public health, and supporting resource management. Traditional methods, while accurate, lack the scalability and real-time capabilities needed for proactive intervention. This study introduces an IoT based water quality monitoring system for the Selangor River, integrating sensors for pH, temperature, turbidity, and total dissolved solids (TDS) with a NodeMCU ESP32 microcontroller. To complement the IoT system, a handheld test pen was used to measure salinity and electrical conductivity (EC), offering additional insights into water quality. Field tests at four stations along the river revealed significant spatial variations. Station 1, near the river mouth, showed high salinity, EC, and TDS, indicating saltwater intrusion, with relatively low turbidity. Stations 2 and 3 recorded the highest turbidity levels, suggesting sedimentation and upstream activities, with moderate salinity and EC. Station 4, upstream, demonstrated stable freshwater characteristics, with low salinity, EC, and turbidity levels. The IoT system reliably monitored real-time parameters, and its measurements were validated against those from the handheld test pen. Minor discrepancies in TDS and temperature readings highlighted the importance of calibration.