Virtual Booth

River water pollution remains a critical environmental and public health challenge, particularly in Malaysia, where delayed detection has previously resulted in severe consequences, including the Kim Kim River pollution incident. Conventional laboratory-based monitoring methods are periodic and reactive, limiting rapid intervention and increasing the risk of prolonged exposure to contaminated water. This project introduces the HydroSense, an Internet of Things-based innovation designed to provide continuous, real-time monitoring and early warning for effective water quality management. The system integrates pH, turbidity, and temperature sensors with an ESP32 microcontroller for accurate data acquisition. Sensor readings are transmitted via Wi-Fi to the ThingSpeak cloud platform for real-time visualisation, storage, and trend analysis. A threshold evaluation mechanism aligned with national water quality standards is embedded to assess compliance. When abnormal readings exceed permissible limits, a three-minute confirmation protocol is activated to prevent false alerts. Persistent violations trigger automated SMS notifications through the Twilio API, enabling immediate response from users or authorities. Experimental validation under controlled and polluted scenarios demonstrated reliable performance, accurate detection of single and multiple parameter breaches, and controlled alert intervals to prevent notification flooding. The proposed system offers a low-cost, scalable, and user-friendly solution suitable for residential communities, semi-urban areas, and environmental agencies. By transforming monitoring from a reactive process into a proactive defence mechanism, this innovation strengthens pollution prevention strategies and supports sustainable water resource management.