entertrain logo
The 127 ComputerBande team
The entertrain app design
The entertrain api documentation
The entertrain backend
The entertrain backend
The entertrain backend
The entertrain backend
Screenshot of the shiny entertrain node js crawler (niklas is no fan of readable debug outputs)
Proof of an important team discussion about what to eat
127 ComputerBande logo

Brought you by 127 ComputerBande (Team #12)

Inspiration

You know the problem: You sit in the train or bus on the way to your work and you have no idea what really to do with your time. So you open up facebook and instagram but after a few minutes you consumed all the new content and stories so you start to switch the apps over and over again. This ist frustrating, we wanted to change this and give your the possibility, to consume content on the go that is directly preselected for you.

What it does

We parse the data from 7Sports, 7TV and YouTube to load them in our backend. The backend system then provides another api for our app that allows to get videos matching a given duration. Paired with the nfc tags from nxp we can calculation your estimated travel time to show you a video that actually matches the whole trip.

How we built it

We built the app for ios and android using react native. The backend and the api are driven by symfony4 and php. Our crawlers that process the third party apis to move the data in our system is written in javascript and running on node.js.

Challenges we ran into

The major challenge was to get the third party data in our system. Beside of this, we actually ran in some design issues in our app - it took a night longer than expected to get some nice looking slider controls up and running.

Accomplishments that we're proud of

The whole system has a huge potential. There is a lot of data out there we could use for our algorithms to provide the user a rich story of content while he is travelling totally stress free. We are proud that we are able to manage that amount of different systems (backend, app, design, crawlers) up and running together.

What we learned

We learned that its always a good idea to treat "nice looking but complex" controls as cream topping since we lost too much time in fixing weird bugs for controls that were replaceable with a default slider within seconds.

What's next for Entertrain

We are able to add apis of local transportation companies like Münchner Verkehrs- und Tarifverbund so our app would be able to run totally automatic and autonomous with realtime video and realtime traffic plan data.