IOT-Based Headwater Detector System

The tragic headwater surge incident at Jeram Air Putih, Kemaman, which resulted in the loss of ten lives, has underscored the urgent necessity for real-time, technology-enhanced monitoring systems in high-risk recreational water areas. This research introduces a comprehensive Internet of Things (IoT)-based Headwater Monitoring System (HMS) designed to rectify the shortcomings of the manual observation techniques currently utilized in 39 identified high-risk regions throughout Malaysia. The system's architecture features a distributed network of environmental sensors, including ultrasonic level sensors, pressure transducers, and flow rate meters, strategically positioned at critical upstream sites. These sensors connect to edge computing units for initial data filtering and compression before wirelessly transmitting the information to a centralized cloud-based analytics platform using LoRaWAN and cellular IoT protocols (NB-IoT/LTE-M). Real-time hydrological data is analyzed through anomaly detection algorithms and threshold-based decision models, facilitating the prompt identification of sudden water level increases or flash flood indicators. When critical events are detected, the system activates automated alerts through a multi-channel communication framework, which includes SMS, mobile applications, and integration with local siren systems, aimed at informing authorities, emergency responders, and nearby residents. Field tests conducted under various rainfall conditions validate the system's responsiveness, energy efficiency, and scalability. This IoT-driven HMS represents a significant improvement in disaster risk reduction strategies, bolstering early warning capabilities and operational preparedness in flood-prone recreational areas.