Flood Early Warning System Based on Firebase Platform and Internet of Things

Abstract

Floods are natural disasters that frequently occur and cause significant damage to human life, infrastructure, and the environment. This study designed and implemented a prototype of an early flood warning system based on the Internet of Things (IoT) integrated with Firebase Realtime Database. The system aimed to address the limitations of previous warning systems by providing more accurate information, faster response times, and easier accessibility. The prototype enabled real-time data access through a web-based application accessible via smartphones and was equipped with a DF Player module to deliver audio warnings. A scaled-down prototype (1:10) was tested using an ultrasonic sensor for water level measurement and a tipping bucket sensor for rainfall measurement. The results demonstrated 99% accuracy for water level measurements up to 200 mm, with a data response time of 1 second and text updates every 5 seconds. This system significantly improved the accuracy, update speed, information accessibility, and effectiveness of audio warnings.