FloodBot - RealTime Innovative Flood Resilience Through Machine Learning

Flooding, one of the most devastating natural disasters, threatens lives, property and infrastructure globally. This paper presents ‘FloodBot’, a real-time flood prediction and resilience system that integrates machine learning and environmental data. Leveraging Convolutional Neural Networks (CNNS), FloodBot analyzes diverse datasets—weather, topography, and hydrology to predict and monitor floods with high accuracy. Achieving a 97% accuracy rate, the model surpasses traditional methods, and its real-time monitoring and alert system enable timely interventions, making it a robust tool for disaster management and preparedness. Hence, FloodBot demonstrates the efficacy of machine learning in disaster resilience and provides a foundation for future enhancements in predictive analytics for floods.