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