Natural disasters create rapidly changing information environments in which citizens, volunteers, and administrators require a common operational picture. This paper presents a full-stack prototype for real-time disaster tracking and evacuation support. The platform integrates a React-based geospatial interface, a Python Flask and Flask-SocketIO backend, JSON persistence, role-aware authentication, browser-based live location, OpenWeather current-weather data, road-network routing, multilingual emergency guidance, SOS signaling, and PDF situation-report generation. Administrators can publish incident and response-resource information, while citizens can view hazards, locate resources, request evacuation routes, and transmit distress information. A transparent climate-risk heuristic combines rainfall, wind speed, and humidity into a bounded preliminary screening score. Functional evaluation was performed across authentication, incident and shelter workflows, climate analysis, live-location display, weather-data integration, administrator-to-user synchronization, routing, SOS, and reporting. The observed tests demonstrate integrated operation of these components; however, no numerical accuracy claim is made for geolocation, route estimation, or the heuristic because dedicated ground-truth and historical validation datasets were not part of the supplied evaluation. The principal contribution is an integrated, explainable emergencycoordination workflow rather than a new prediction algorithm.

Maseeha Banu, Gagan D S, Likitha C D, Lokesh M M, Bhoomika R Kandgal, "A Real-Time Disaster Intelligence and Evacuation Support Platform Using Geospatial Visualization, Live Event Synchronization, and Climate Risk Inference" International Journal of Computer Science and Engineering Development, V1(4): Page(152-156) September - October 2026. ISSN: 3139-0862. www.ijcsed.com. Published by Scientific and Academic Research Publishing.