SafeRoute

SafeRoute uses AI to find the safest route, not just the fastest—analyzing crime risk, lighting, and infrastructure to guide users with real-time safety insights and emergency support.

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Inspiration

Imagine walking alone at night, following a navigation app — but having no idea how safe that route actually is.

We realized that existing navigation systems optimize for speed, not safety. This gap inspired us to build SafeRoute — a solution that prioritizes personal safety during travel using real-world data and AI.

What it does

SafeRoute is an AI-powered safety navigation system that finds the safest route between two locations.

Instead of only considering distance or time, it analyzes multiple real-world safety factors such as:

  • Street lighting
  • Police proximity
  • Medical access
  • Commercial activity
  • Crime hotspots

It then ranks routes based on safety and provides:

  • Color-coded safety visualization on maps
  • AI-generated safety insights
  • Real-time awareness of risky areas
  • Emergency tools for user protection

How we built it

We built SafeRoute as a full-stack application:

Frontend:** React (Vite) with Leaflet for interactive maps Backend:** Python Flask API for routing and safety calculations Routing:** OSRM for generating route alternatives Data Sources:** Google Places API + OpenStreetMap (Overpass) AI Integration:** Google Gemini for safety briefings and hotspot generation

The system samples multiple points along a route, evaluates safety factors, and computes a safety score to rank routes intelligently.

Challenges we ran into

  • Designing a meaningful safety scoring system using real-world proxies
  • Handling incomplete or inconsistent location data
  • Ensuring AI outputs were relevant and useful, not generic
  • Balancing performance while querying multiple APIs in real time
  • Creating a smooth and intuitive user experience despite complex backend logic

Accomplishments that we're proud of

  • Successfully combining multiple data sources into a unified safety score
  • Integrating AI to provide human-readable safety insights
  • Building a real-time, interactive safety visualization system
  • Creating a practical solution with real-world impact
  • Delivering a full-stack working prototype within limited time

What we learned

  • How to design systems that solve real-world problems, not just technical challenges
  • The importance of user experience in safety-focused applications
  • Practical integration of AI into meaningful workflows
  • Handling real-world data limitations and edge cases

What's next for SafeRoute

SafeRoute can be scaled beyond a single city by integrating location-specific datasets.

In the future, we aim to:

  • Expand to multiple cities and regions globally
  • Incorporate real-time user-reported incidents
  • Integrate live data from authorities and public safety systems
  • Enhance predictive capabilities using advanced AI models

Our vision is to make safety-aware navigation accessible to everyone, everywhere.

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