Res-Q: A Smart Disaster Safety Management System with Real-Time Prediction and Alert Using Machine Learning and Flutter

Natural disasters such as earthquakes, floods, and fires pose severe threats to human life and property.In recent years, the integration of technology in disaster management has shown promise in reducing damage and improving emergency response.This paper presents Res-Q, a mobile-based Disaster Safety Management System developed using Flutter.The system not only provides structured safety tips and emergency contact features but also integrates machine learning algorithms to predict the possibility of earthquakes and floods based on real-time weather conditions.The app leverages open-source maps, weather APIs, and Firebase for authentication, delivering a user-friendly and proactive solution.The prediction models are trained using Random Forest and Support Vector Machine (SVM), and the system displays alerts and safety measures accordingly.This paper outlines the architecture, methodology, implementation, and performance of the system, highlighting its potential impact in disaster preparedness and response.