Skip to content
This repository has been archived by the owner. It is now read-only.
master
Go to file
Code

Latest commit

 

Git stats

Files

Permalink
Failed to load latest commit information.
Type
Name
Latest commit message
Commit time
 
 
app
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

README.md

Aquila - Sightseeing in the Train

This Project was built at 8th DB Hackathon in Berlin at the 15th and 16th December 2017 by the team "SightTraining".

Team

  • Mauricio Abrigada
  • Paul Bauriegel
  • Kilian Kluge
  • Florian Proske
  • Jan-Philipp Schröder
  • Joshua Töpfer (@joshuatoepfer)
  • Luca Vazzano (@lvgermany)

Use Case

Train trips aren't always that fun, because of that we want to give you the opportunity to explore your surroundings and learn about them.

Technologies

This Project was made with a Python backend, which is an REST API made with Flask and a frontend which was made with Angular2+ and Bluma.

Data

For our Project we used different kind of data. Because we hadn't had access to live positioning data of trains we used historical data collected by the "Wifi on ICE" system which is build into every ICE. For the point of interests we used different approaches. First we tried the wikipedia geosearch. But this wasn't a good choice because it also marked call-houses near the train tracks. So we tried the wikunia-sights API next. There we found a lot of streets and also villages as point of interests. That isn't such a good solution too. So our last attempt was to use the wikidata API which did a pretty good job, but marked some memorial tablets on a cemetery. So we had to improve out filtering. For that we hadn't enough time. So the point of interests in our presentation are from the wikunia-sights API. Since the hackathon, the idea of using Wikidata and filtering is in development as ionicsolutions/pomi, which one day might or might not serve as a more advanced backend to this project.

Prospect

In the future you could implement our solution into the ICE portal of Deutsche Bahn, where it could use the positioning system of the Train. You could also build a augmented reality version of our solution or also a augmented window solution like shown in this article.

Run the project

cd aquila
wget http://download-data.deutschebahn.com/static/datasets/wifi/20171212_wifionice.zip
unzip 20171212_wifionice.zip && rm 20171212_wifionice.zip
mv surveyor_hackathon_data_20171212.csv app/default/surveyor_hackathon_data_20171212.csv

cd app/static
npm install
npm run build

cd ../..
python3 -m pip install -r requirements.txt
python3 run.py

About

DB Hackathon #8 Team Aquila

Resources

License

Releases

No releases published

Packages

No packages published
You can’t perform that action at this time.