We got inspired by simple every day problems. Parking is a big aspect of transport and a big cause of traffic due to the ineffectiveness in which it is used. What we got inspired by was making the process of finding a parking spot as painless and seamless as it is possible.

What it does

Our app marks parking spots in the city on the map, and allows the user to filter the results based on his preferences (based on parking duration, budget, spots for electric cars etc.). It also shows the user a more detailed view of the parking lot, shows empty parking spots based on sensory data and lets you navigate to the desired spot. You can then park and access your information off the Cloud (info like how long you've been standing there, how much you're going to have to pay and more) and when you return, our app allows you to pay through it. We also use machine learning and datamining to process user data and offer better suggestions to the user.

How we built it

We built this app by splitting up into the different parts of the app, and then having each part be developed with the larger use case scenario in mind.

Challenges we ran into

Scoping was a problem, as well as coordination between the different parts of the app. Presenting this much data in a useful manner is also difficult.

Accomplishments that we're proud of

We're proud of our datamining and machine learning algorithm, as well as our general idea and our use case scenario.

What we learned

We have learned that a clear plan and good planning are as important as the work on the project itself. Also coordination and setup of the cooperative environment (github for example) should be done in advance and all teammates should stick to the common design guidelines

What's next for park it

Next we would like to finalize on which sensor technology we use, and implement and improve our UX/UI design. We'd also tighten the integration of our core features with each other.

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