The way Data is generated by the shipping industry is neither transparent nor efficient. It creates endless amounts of paper, and is largely not automated. Managers report that the current software for interacting with that data is cumbersome and requires too many clicks to arrive at relevant information

What it does

Ship Dash puts a small amount of relevant information up front in an easily viewable dashboard. The contents of that dashboard can be configured by the user to display only the information they find most important, to establish a high-level view of the state of their fleet.

How we built it

We wrote Python scripts to scrape data from the noon reports, which are emailed from vessels at see, that insert that data into a database. We then created a RESTful API using django and Pandas, which serves this data to our application in a well organized, concise manner. Our front-end application was built in React.

Challenges I ran into

The data we had access to over the course of the weekend was largely incomplete and limited in scope, containing many null values, and few complete entries. With a more complete dataset, we could implement machine learning for the purposes of predicting delays or other anomalies, with the end goal of saving the shipping company money.

Accomplishments that I'm proud of

A working prototype after only a day of work! We are very excited to build out further features with more time, and more access to relevant data.

What I learned

This weekend was an excellent introduction to the use of data in the shipping industry, and we are excited to explore the possibilities when data flow is less constricted.

What's next for ship dash

More features! More configuration. For instance, ship managers will be able to set preferences for KPIs on their fleet and be notified automatically when any ship's report fall outside of those parameters. Also, predictive learning. The more data our application is able to collect, the smarter it will become, and the more efficient it will be for finding opportunities for eliminating waste maximizing revenue.

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