CrowdFlare

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  leaderboards

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  landing apge

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  maps

Inspiration

When we want to find a chill place on the UNSW campus, everywhere we look is always full or busy. This inspired us to build a solution that helps students find quieter spots in real-time.

What it does

It allows users to report busy areas, similar to how the Waze app works, and shows these "flares" visually on a map. Contributions also lead to fun stats, making it both practical and engaging.

How we built it

We built the project using a modern tech stack, including HTMX, Go Templates, AlpineJS, MongoDB, TailwindCSS, and Leaflet. We also integrated the DevSocAPI for room data to provide accurate location-based information.

Challenges we ran into

We faced several challenges, including data representation and working with a map (which was our first time). Additionally, adapting to a new tech stack brought its own learning curve.

Accomplishments that we're proud of

We're proud of the nice-looking UI, the interactive map that provides real-time data, and successfully implementing authentication for user contributions.

What we learned

Throughout the development process, we learned how to integrate new technologies and overcome challenges like working with Leaflet for map visualizations. We also deepened our understanding of database management using MongoDB and how to implement dynamic, interactive features with minimal JavaScript.

What's next for CrowdFlare

The next steps for the project involve incorporating machine learning predictive models to improve flare accuracy and help users find the best spots based on real-time trends and predictions.

Built With

• alpinejs
• golang
• htmx
• mongodb
• tailwind