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Inspiration

Urban safety shouldn't be a gamble. While standard GPS prioritizes speed, RadiantSafety prioritizes security. We built this to bridge the gap between navigation and situational awareness, giving Victorians and tourists the tools to navigate unfamiliar areas with confidence.

What it does

RadiantSafety is an active security ecosystem. It generates a live heatmap by merging historical CSA Victoria data with real-time police news scrapes. Our custom navigation engine routes users around high-intensity hotspots, favoring safety over distance. Key features include a "Safe Walk" dead-man’s switch for hazardous zones and a geofenced SOS network that pings verified community responders within a 1km radius during emergencies.

How we built it

Our stack focuses on speed and spatial accuracy. We used Next.js (React 19) and TypeScript for the frontend, with Mapbox for rendering. The backend is powered by Supabase for data and auth. Our routing engine is a Python-based microservice deployed via Docker on Railway, while Elasticsearch handles real-time querying of Victoria Police data.

Challenges we ran into

The biggest hurdle was the pathfinding logic. Balancing "risk weights" against geographical distance required extensive tuning to ensure routes remained practical without clipping danger zones. Managing real-time data ingestion from disparate sources into a unified spatial grid also required significant backend iteration.

Accomplishments & Lessons

We successfully deployed a functional MVP that merges static government stats with live emergency pings. We learned the complexities of geospatial architecture and the power of containerized microservices for handling heavy algorithmic logic.

What's next

We plan to further refine our pathing algorithm for better precision, while incorporating street-level data like lighting and foot traffic patterns to optimize our mobile-first SOS features.