Integrating IoT Sensors and Machine Learning Algorithms for Early Flash Flood Detection System

The rising frequency of flash floods due to climate change demands efficient detection systems to reduce their impact. This study presents the "Early Flash Flood Detection System Using Machine Learning Algorithms," which integrates IoT sensors and machine learning for accurate, real-time flood prediction. Developed with Agile methodology, the project utilized key technologies like Flutter and TensorFlow to enhance functionality and user engagement. Testing showed 72% prediction accuracy, demonstrating the system's potential as a scalable solution for disaster management, advancing public safety, and fostering resilient communities.