IoT-Enabled Monitoring and Notification System for Real-Time Water Quality Management

Abstract

River water pollution is a critical issue in Malaysia, posing health and environmental risks. This study presents a real-time monitoring and alert system integrating pH, turbidity, and temperature sensors with IoT technology. Using ESP32 hardware, sensor data were transmitted to ThingSpeak for visualization and logging, while SMS alerts were delivered via Twilio with confirmation logic to minimize false alarms. Tests under normal, high turbidity, and low pH conditions showed accurate performance, with alerts triggered when pH fell outside 6–9 or turbidity exceeded 50 NTU. The system proved stable, low-cost, and scalable, offering practical applications for residential and community use. It supports early pollution detection, as emphasized by incidents like the Kim Kim River case. Future work will expand monitored parameters, add mobile app integration, and introduce automated sensor cleaning for improved usability.