We were excited to use the Syracuse Open Data source after meeting with the representatives, and wanted to challenge ourselves to combine that information with a Google Cloud API. Our team wanted to expose ourselves to some new coding techniques, using multiple new technologies that we were not familiar with. After one team member revealed she damaged her car on a pothole in years past, we decided to stick with the road quality data from DataCuse and build our project off the need to avoid potholes, and treacherous roads in general.

What it does

Our project takes an input of a start and end address in Syracuse, obtaining the route via the Google API. Once it has the roads that will be traveled, it will calculate the average road quality across the trip. We also created a map that had the roads mapped out with their quality rating.

How we built it

We utilized Python, along with the csv, requests, and json, in order to read the json file from the Google API and the csv file acquired from Syracuse Open Data. First, we used R in order to narrow the Syracuse Open Data set down to the necessary data. The csv was transferred into a dictionary in our python code to make the quality ratings easily accessible. We then parsed the json file for the desired roads. Once the roads were located, they were used to find the quality rating so that we could output the average quality rating for the trip. We imported the data from Syracuse Open data, in the form of a shapefile, into ArcGIS. We then added a base map to improve the visualization of the data.

Challenges we ran into

The main problem that we ran into is that we were unable to connect our Python code with our ArcGIS map. We also struggled to work with the Google API, as we had no previous experience working with an API before (admittedly, all group members had search Google for what an API was before the project truly got underway). We also had never worked with JSON files inside of python before so it was difficult parsing the data to find the street names.

Accomplishments that we're proud of

We are proud of using a combination of technologies that we were not familiar with before. API, JSON, and ArcGIS were all technologies that we were not familiar with and we were able to create a project that utilized all three of these to various extents.

What we learned

First of all, we did indeed learn what an API is! On a more serious note, we learned how to incorporate multiple technologies inside of one program, with the API and the dataset. We learned how to maneuver a JSON file in python in order to obtain the information that we needed. We also learned how to develop a map in ArcGIS.

What's next for Car Care for 'Cuse

In the future, we would like to connect our ArcGIS map with the python code in order to visualize the path the user will be taking. We would also like to incorporate a feature that provides the user with multiple choices of routes with varying levels of quality ratings. We would also like to fix some issues that we had with streets not matching up across data sets, such as "e colvin st" and "colvin st e".

Built With

Share this project: