HECO Stations

Inspiration

Our team realized that the format of the page(s) needed to be concise and clear from the moment it was loaded in. As such, the design was meant to be non-scrollable and rich with information.

What it does

Future Goal: The main page will maintain an aggregate data of all charging stations that denote the aspects of a charging stations status such as: kilowatt per hour (kW/h) used per charge session, power consumed per session, distribution of port types and payment types. We plan to make predictions off of these data sets, for example if we see that the gap between two charging sessions begins to lessen at a certain peak then we can warn users that at this time this specific station will be congested.

Current: Using the data sheet provided by HECO were able to create four graphs using Python that highlighted aspects of the charging stations. We believed that the distribution of both the charging type and payment method were signifiers what types of people frequented certain stations.

How I built it

We built the web app using Flask to help interact with the front-end and the back-end. The back-end for us just means the necessary logic to create the graphs from parsing through a csv file.

Challenges I ran into

Since the team was very new into the field of web development, we felt that googling things was and still is the hardest challenge. Certain concepts like interaction between Python/R and front-end languages, how to create graphs with Python or R and many more meant that first half of the competition we were stuck in an information dump.

Accomplishments that I'm proud of

We were able to use Flask to display our charging station data, create a map component on the page and overcome the initial challenge of working with GitHub for such a project.