Inspiration
We were inspired to build this project by our own experiences of the difficulty of finding parking in big cities.
What it does
Our project returns parking locations that have the highest probability of vacancy in proximity to a user given location.
How we built it
We built this project by utilizing the flask python framework to develop the back end and a mix of html, css, and javascript to develop the front end.
Challenges we ran into
We came into this hackathon with little to no experience with API's so there was definitely a steep learning curve we had to traverse at the beginning of the hackathon. We also ran into a little resistance extracting specific information from the JSON files that the API's returned. Near the end of the hackathon, we ran into an issue converting information from certain data types to others. As a result, we had to simplify the scope of our project, namely the aspect that sorts the parking spots with respect to probability of vacancy, in order to get a functioning program. In its current form, the project outputs all parking spots within proximity of the user location and its corresponding probability of vacancy for the users to decide for themselves.
Accomplishments that we're proud of
We're proud that we were able to persevere beyond our first couple hours in which we were making little to no progress and create a working project.
What we learned
We learned how to work with and incorporate professional API's into our own code. We also learned valuable collaborative skills in the process of working in a team to create this project.
What's next for EZPark
In the future, we will try to reimplement code that will give a definitive suggestion for a parking location to the user weighing probability of vacancy, distance, and price. We can also search for different data we can use to make the probabilities more accurate.
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