IoT-Based intelligent system for headwater phenomenon detection and alerts using ESP32

Headwater phenomena, characterised by rapid increases in river levels and flow velocity, pose significant risks to downstream communities. This study presents an Internet of Things (IoT)-based intelligent monitoring and alert system for detecting headwater phenomena in real time. The proposed system integrates multiple ESP32 microcontrollers with water level and rainfall sensors to monitor environmental parameters continuously. Data are transmitted to Firebase for cloud storage and further processed using Google Sheets for visualisation and analysis. A decision-making algorithm correlates rainfall intensity with water level changes to classify potential hazards and trigger appropriate alerts. Notifications are issued through an LCD display, buzzer, and Telegram alerts, ensuring timely responses. The system enhances early warning capabilities, minimises damage risks, and improves public safety in flood-prone regions. The integration of cloud computing and IoT technology ensures real-time monitoring, remote access, and automated data-driven decision-making. Experimental results demonstrate the system’s effectiveness in accurately detecting and responding to headwater-related hazards, making it a viable solution for disaster preparedness and mitigation.