Inspiration
On our way to Hack Harvard, we lost way too much time hunting for parking near the library. Being from NYC, we thought we could outsmart the system, but nope. After realizing there’s no app for finding free street parking, we decided to create one ourselves—because no one should have to endure that pain again.
What it does
We provide a heatmap that represents public parking availability in dense urban areas. Our focus is on free, street-level parking, including metered spots, but not on private garages or paid parking services. The app gives users insights into the probability of finding an open parking spot or the average time it takes to secure one.
While driving, users receive assistance in finding parking through the display of likely open spots via a heatmap. This prediction is based on historical data about parking trends, factoring in variables like the time of day and the day of the week.
Once users open the app, their driving routes are recorded, and any spots along the way where parking is unavailable are marked. When a user successfully parks, they simply tap a button to confirm, and we ask a few follow-up questions, such as whether they noticed parking availability elsewhere or if accessibility was an issue.
To encourage user participation, we’ve introduced a contribution-based system. Users must share parking data to continue accessing the heatmaps. Initially, new users are granted a limited number of free requests, after which they must contribute more data to unlock additional insights. Users can earn points through various actions, such as marking when they leave a parking spot. Points are awarded based on the difficulty of finding parking in that area, and users can see their live-time rank as they contribute more.
How we built it
We used React for the front end, MongoDB for the database, and Heroku for hosting.
Challenges we ran into
We encountered several challenges with integrating the Google Maps API, particularly with implementing the heatmap, pinpointing user locations accurately, and ensuring the UI was smooth. Additionally, designing the algorithm to predict parking availability (hot and cold spots) proved more complicated than expected.
Accomplishments that we're proud of
We’re really proud of the heatmap we were able to create, along with the shared database that connects all users. Initially, our app was limited to local testing, but we transitioned to a shared online database that aggregates parking data in real-time. In fact, to gather realistic data for our map, we went out and drove around late at night! The algorithm we built to calculate parking probability is something we’re especially proud of.
What we learned
We deepened our knowledge of the Google Maps API, especially the Roads API, which turned out to be trickier to work with than we anticipated.
What's next for Parkara
We want to enhance the gamification aspect to further incentivize users. Additionally, we plan to incorporate data on no-parking zones and parking restrictions (like fire hydrants or tow-away zones) to avoid marking these as false positives.
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