Rebel Radar

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  Main Page

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  Event Description

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  Event on Map

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  Map

Inspiration

We kept missing things on campus. A club meeting we didn't know about, an event in a building we'd never been to, a food deal that came and went. Everything was scattered across different platforms and there was no single place to just check what was going on at UNLV. On top of that, there was no way to know about something happening in real time. We figured if we were dealing with this, every other person probably was too.

What it does

Rebel Radar pulls all publicly posted UNLV events, like clubs, associations, food, and puts them in one place. You get a clean feed of event cards on the homepage with all the details: what it is, when it is, and where it is. You can tap into any event to learn more or pull it up directly on the map. We also built a Hotspot feature where users can drop a live named pin on the map to notify others about something happening in the area.

How we built it

React Native Expo holds everything together on the frontend. For the events, we wrote a Python scraper to pull UNLV event data and then ran it through DeepSeek AI to parse and clean it into a structured JSON file, which the app reads directly to populate the event cards. The map is powered by Google Maps API and handles both event locations and hotspots. Supabase runs the backend storing hotspot pins and syncing them in real time across all users so everyone sees the same map.

Challenges we ran into

Some challenges we ran into were working on a tight schedule and having to sacrifice our sleep to complete the project. But besides that the only main problem we had was the setup. The setup was the hardest part as we had to find our frameworks we were going to be using, what backend and what idea we were going to go through with.

Accomplishments that we're proud of

Something that we are very proud of is finishing the project in around 8 hours of work. For the quality of our project to the time worked on it, it's surprisingly really good (in our terms).

What we learned

We learned a lot about working with different technologies into one cohesive product. Using an LLM as a data pipeline tool was a new way of thinking about AI for us. We also got a lot more comfortable with Supabase's real-time features and with building map interactions.

What's next for Rebel Radar

Next thing for Rebel Radar is hopefully getting published because this came out better than we expected. With active users on our app, monetization could help with us scraping more sites to eventually get every posting of an event online at UNLV.

Built With

• deepseek
• google-maps
• python
• react-native-expo
• supabase
• typescript