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UI
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Data
Inspiration
Driving in Philadelphia, I quickly realized that finding parking is often a nightmare. Circling blocks for 20+ minutes, wasting gas, and stressing over spots became a frustrating daily routine. Existing apps were outdated, incomplete, or focused only on pricey garages. I wanted a solution that made parking fast, easy, and stress-free for everyone.
What it does
The app helps you find parking quickly and stress-free by: 1- Showing all garages, meters, and permits in the city. 2- Highlighting free parking spots in real-time. 3- Offering filters for price, distance, EV charging, and accessibility. 4- Using predictive logic to estimate which spots are likely available. 5- Letting users report parking availability, improving accuracy over time.
How we built it
Challenges we ran into
Outdated or inconsistent datasets – Most data I found was from 2015, which meant I had to add locations and update prices manually. Performance – Keeping the app fast and responsive while handling live updates was tricky. Feature vs. simplicity – I wanted the app to be powerful but still easy to use in real-world situations. Real-time availability – I hoped to show whether a spot is actually free, but that required more data and paid APIs I didn’t have access to.
Accomplishments that we're proud of
Built a working, interactive app showing over 2,500 parking locations across Philadelphia. Integrated multiple data sources—city datasets, garage info, and live user reports—into a single map. Implemented predictive logic to estimate parking availability using historical and real-time data. Solo project completed end-to-end – From data cleaning to interface design and mapping.
What we learned
Data integration, interactive mapping, and predictive modeling
What's next for PhilaSpot
I really want to have a real-time availability – Integrate additional live data or paid APIs to show whether a spot is actually free. Expanded coverage – Add more locations and parking types, including private lots and event-specific spots. Improved predictions – Use more advanced AI models for better accuracy in estimating availability. Mobile-friendly version – Make the app accessible on phones for on-the-go use. Community growth – Encourage more users to report spots, making predictions smarter and more reliable. Additional features – Include notifications, route suggestions, or integrations with navigation apps.
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