Hacktrain EU

What an experience! As soon as I heard about this amazing hackathon, I knew I had to participate! Hacking on a train for 48 hours from London to Paris, from Paris to Lyon and back sounded incredible. And it was! It was SO much fun!

Of course, the theme was hacking the rails and this was the hack’s third edition! Organised by Hack Partners, this event is more than just a fun weekend. At the end of the hack, 10 interesting projects get selected and go into an accelerator program, becoming real start-ups in less than a year.

Two amazing examples from last year, include Busybot and Vivacity. The first one is integrated in the trainline app and allows customers to find where empty seats are on a train so that they can wait next to that coach. A very convenient feature for peak hour commuters. Vivacity, on the other hand, is developed by a group of Cambridge graduates and offers state of the art video analytics. With the use of machine learning it can also predict numbers of people at a station, boarding or alighting the train, queues at the ticket office and so on.

This year, each sponsor provided challenges and data sets for the participants. Out of 600 applicants, 80 hackers were selected to take part and we were split between 2 trains : HackTrainUK and HackTrainEU. I was lucky to go on the EU one, having the opportunity to see my beloved Paris once more (if only for a few of hours). The four main sponsors were Arriva, Eurostar, TfL and SNCF, joined by EY, BAE systems, the Department of Transport and many more.

Our journey started at St Pancras, taking as in.. wait a minute.. Business Class!!! to Paris. It was amazing! As the teams were already formed, this 2 hour trip offered us the chance to brainstorm ideas and organise our projects. I was really surprised that as soon as we entered France, the train’s speed reached 185 miles/hour. It was crazy!

I was part of a team of 3 hackers and we chose to focus on allowing train companies to improve their communication with clients during disruptions. Helping them to also store and make predictions for future events regarding the number of passengers impacted by such events.

For this, we used TfL’s data set from the Tramlink service, where they use door sensors to count how many people board and alight the trams at each station. This was great for us and we managed to mine the data and observe patterns of commuters and periods when trams are disrupted and how many people are on those trams, as well as how many people are waiting to board at next stations. These are some screenshots of our prototype, which will allow the train controllers to view the passenger data regarding each train passing a station.

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The winner of this year’s edition was FlexiRail and they developed an app that allows users to opt for flexible train times so they’ll be offered a ticket on the most convenient route to avoid overcrowding. Runner ups, AutoMapr, tackled the most technically challenging data set, the LiDAR data, offering machine learning integration for visualising train wires. What they managed to do in 48 hours was amazing! The topic is usually one for research groups at Princeton University.

The weekend was packed with amazing ideas, people and stories! I would strongly encourage other people to join the Hacktrain next year as it truly is a unique hacking experience!

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