Development of a Flood Early Warning System Using IoT Sensors for Communities in Bayelsa State

Bayelsa State in the South South geopolitical zone of Nigeria is among the most flood-prone regions in West Africa, experiencing annual inundation that displaces thousands of residents and destroys livelihoods. This study presents the development of a flood early warning system using Internet of Things sensors deployed along key waterways in communities within Yenagoa Local Government Area. The research was motivated by the recurring failure of existing manual flood observation methods to provide sufficient advance warning for community evacuation. The proposed system employs ultrasonic water level sensors, rain gauge modules, and NodeMCU microcontrollers transmitting real-time data to a cloud server via Wi-Fi. A Telegram-based alert notification system was integrated to disseminate warnings to community leaders and residents within seconds of threshold exceedance. System testing during a controlled simulation produced alert delivery within 8 seconds of sensor threshold breach, with all test notifications received accurately across 20 registered user devices. The study acknowledges the need for waterproof sensor enclosures and tamper-resistant installations given field conditions. Recommendations include collaboration between the Bayelsa State Emergency Management Agency and telecommunications infrastructure providers to ensure network reliability in riverine communities. Keywords: flood early warning, IoT sensors, Bayelsa State, disaster management, community alerts.