HackTrain 3.0 – The HackTrainEU Teams
Below is a description of all the HackTrainEU teams. These are the pitches they gave me while developing their ideas and solutions in the co-working space in Lyon. They’ve assured me they’ll probably change their minds completely before the final pitch in front of the judges on Sunday! I’m definitely looking forward to the finished pitches as well as the ones I haven’t heard from the #HackTrainUK train! Click here to read part 1 of my blog post about our weekend in France where this fun group came up with all their great ideas!
1) UnRAIListic
Thomas, Ashton, Steven, Sebastian
Challenge: BAI Communications: “we have all this data, we don’t really use it, go and see what you can come up with.”
Idea: to track customers, specifically commuters who make up half of all passengers on urban networks, by their station wifi usage. Typically you will have a wifi provider at a station and ideally across a whole network of stations. UnRAIListic wants to use data such as disruption feeds and weather data etc. to give customers information when they log into the station wifi, e.g. “it is raining at your destination” or “your next train is cancelled, here are your alternatives”. The benefit is that this doesn’t require an app, this would just come up on customers’ screens when they log into the wifi. Wifi providers could choose the level of features they wanted to apply. It would be possible to suggest to customers who always get out at station X that they could pre-order a coffee from a coffee shop at that station that they could easily pick up on arrival. It would help businesses in stations take advantage of travellers when they arrive at their destination, whereas typically today they leave the station immediately upon arrival. It would be up to the wifi provider to choose how to monetise that but if they pushed such deals, their advertising space would be more valuable. It’s simple to start off small and can be customized for every different wifi provider.
2) e-motion: feelings as data
Sam, Tom, Daniel, Greg, Struan
Challenge: personalising customer experience
Idea: sentiment mapping in a three-step process: Connect, Respond, Know. Using technology to capture people’s faces and process their emotions to be able to respond to passenger needs in real time, making someone’s day and therefore connecting more closely with customers, increasing their enjoyment of the journey. The Connect element is about detecting people’s faces and emotions, the Respond element would be the suggested solution, e.g. offering a free coffee, and the Know element looks at long-term trends, e.g. times of day when people feel more negatively. Once implemented, the system could learn what solutions are most effective at achieving their goal, as this too would be measurable through evaluating the customers’ faces after the fact.
3) Oru
Kyle, Daniel, Ravi, Christian
Challenge: personalising customer experience
Idea: to create a chat bot specifically for the time when passengers are on the Eurostar to help them make the most of their experience.
For example, this bot could inform passengers about the on-board entertainment system and about segments of the journey where wifi is particularly good or poor. It could also help passengers with their onward travel, e.g. the bot could help with booking a hotel or finding an onward connection. This is particularly convenient as passengers typically have time on the train and it would be much more relaxing than trying to find these solutions at the destination station. Typically operators wish to engage with their passengers before, during and after their journey. This experience would start in the middle, during the journey, connect with them after the journey and then bring them back round to another booking thanks to the positive experience, connecting with passenger before the following journey.
4) Push
Martin, Tim, Tycho, Charlotte, Matthieu
Challenge: Nomad Digital: how to help customers understand why there is a wifi outage during a trip
Idea: when you sign on to the train wifi, you will get asked if you want to receive push notifications. If you opt in, then you can be informed about wifi outages along the track, e.g. ‘in five minutes’ time there will be a 30-second outage’. This information is gathered by knowing the bandwidth at each GPS data point along the track. To enhance the customer experience, you could have a choice of languages in which you would like to receive the information; and other relevant passenger information could also be sent out in this way, e.g. delays.
5) OneRail
Joe, Danny, Ben, Rory
Challenge: personalised customer experience
Idea: to use beacons in carriages that communicate with the unique identifier in customers’ smartphones;
customers who install the app on their phone can then receive certain benefits in return for the train operating company receiving the data it wants. The benefit of this system is that it isn’t operator specific. It’s a platform that all the operators could sign up to so that customers don’t have to download a separate app for every single train that they get on to. This is more convenient for passengers and also more efficient from a development standpoint. Passenger benefits could be getting upgraded or being offered a complimentary drink. This beacon method is also better than some of the alternatives that use cameras because it’s more private.
6) SARA
Alex, Bogdan, Dora, Nando
Challenge: personalised customer experience
Idea: SARA is a chat bot who will accompany your journey before, during and after you travel. She has your booking number and therefore already knows a certain amount of information about you. In addition she can answer questions to make your journey easier, such as what the weather is at your destination, but she can also make suggestions to you that you didn’t necessarily know to ask for. SARA could tell you for example that it is raining at your destination and suggest shops where you could purchase an umbrella or she could tell you about offers at your destination.
7) Team Goat
Mark, Kass, Izz, Bartek
Challenge: reducing friction in stations
Idea: a reliable automated wifi ticketing system: to have app on your phone where you enter bank details at first contact; then use station infrastructure – routers – that allow you to experience travel without having to buy a ticket from a ticket office or vending machine. By passing the contact points upon start and finish, it can automatically bill you and send you notifications about your journeys. The benefit is that you don’t get bottlenecks, waiting to buy tickets, it’s very convenient and also, you know you will get the best ticket for you so it’s less of a headache.
8) Disruption 2.0
Raluca, Hugues, Stefan
Challenge: Arriva: tackle disruptions better, using TfL Tramlink data
Idea: by taking statistical data for passenger numbers on trains, passengers waiting to board trains at stations and time-tabling information, this data can be analysed and presented to the dispatcher so that s/he can take informed decisions based on the number of passengers waiting. The software proposed is therefore a supportive software – it doesn’t make the decision for the dispatcher, nor does it make recommendations. It gives the dispatcher information about what the impact of a decision would be. If passengers have the associated app on their phone, it would also allow them to be informed about disruptions way before they got to the station.
9) Train Crowd
Dalimil, Szen, Willy
Challenge: passenger loading times
Idea: to use historical data about passenger numbers on trams to visualise the data by creating a map that makes it easy to understand where and when trams are busy and when they are empty, to help customers make informed decisions about their travel.
10) Gauge
Challenge: Angel Trains: energy
Alex, Anthony, Vaughan
Idea: to use energy data from trains to make them more efficient. Although trains are considered a very sustainable form of transport, there is still massive room for improvement both for diesel trains and for electric trains. Gauge wants to take that data and present it in a useful manner to determine where the inefficiencies lie and how to improve them. Inefficiencies could come from drivers – the system could tell that from knowing what drivers are working on any given route, they could also come from specific trains if those trains have problems, and finally, there could also be infrastructure issues, particularly with electrified routes. It is worth investigating whether the right level of electricity is being fed into the route at all times and whether regenerative braking is working. Gauge wants to provide the answers here.
