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About SafeRouteX exists to address the problem that during disasters, the shortest route is often unsafe. It computes evacuation paths that account for real-time risk factors such as heavy rainfall and nearby seismic activity, rather than distance alone. By modeling regions as a graph with dynamically penalized risks, it helps planners, researchers

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SafeRouteX Disaster-Aware Evacuation Routing System

SafeRouteX computes risk-aware evacuation routes using live weather and seismic data, built for backend engineers, researchers, and emergency-planning system designers.

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About

SafeRouteX exists to address the problem that during disasters, the shortest route is often unsafe. It computes evacuation paths that account for real-time risk factors such as heavy rainfall and nearby seismic activity, rather than distance alone. By modeling regions as a graph with dynamically penalized risks, it helps planners, researchers, and backend-focused engineers explore safer evacuation strategies and disaster-aware routing systems.


Features

  • Risk-aware evacuation routing: Computes evacuation paths that minimize risk rather than distance using dynamic penalties.
  • Live disaster data integration: Incorporates real-time rainfall (Open-Meteo) and earthquake data (USGS).
  • Graph-based modeling: Represents regions as a weighted graph to enable flexible and extensible routing logic.
  • Safehouse discovery: Identifies nearby shelters and critical facilities for evacuation endpoints.
  • Minimal interactive UI: Provides a lightweight Gradio interface with map visualization for demonstration.

Tech Stack

  • Language: Python
  • Frameworks / Libraries: FastAPI, NetworkX, Gradio, Folium, Requests
  • Geospatial / Data APIs: OpenStreetMap (Nominatim), Open-Meteo, USGS Earthquake API
  • Containerization: Docker
  • Deployment: Single-container service (Render / Railway / VPS compatible)

About

About SafeRouteX exists to address the problem that during disasters, the shortest route is often unsafe. It computes evacuation paths that account for real-time risk factors such as heavy rainfall and nearby seismic activity, rather than distance alone. By modeling regions as a graph with dynamically penalized risks, it helps planners, researchers

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