Have you ever felt bored or been wondering why you can see only ads in public transport? We had. Therefore, our inspiration for this weekend was to hack this emptiness: to take full use of available technology with the data obtained from vehicles and internet. Combining the best ideas with their possible implementation, we created a platform that makes public transportation accessible and enjoyable to most of the people, making it even more appealing than private vehicles.
What it does
At the first glance, you will see a platform written to fit public transport screens, website, and mobile apps. But inside the platform, you'll find something more amazing, first of all, a well defined content suiting all age groups and different types of personalities. Moreover, algorithms using onboard positioning and 3D sensors, TinyNode sensor hubs, and Vehicle CAN data are integrated which transform a mass of unuseful before data into up-to-date content and calculating defined information that will help companies in optimization and development of currently existing routes, timing, etc.
Major part of our solution lies in connecting people taking a ride in public transport with the right content. Our platform features: name of and time to the three following stops, name of the next stop with times to interconnecting transport, latest news and weather forecast fetched up from APIs, information about the driver to increase trust and personal attachment, promotion of public transportation as a highly ecological alternative to private cars, statistics obtained from the vehicle’s sensors, advertisements matched to a relevant location, and content to foster good atmosphere inside, like “Enjoy your ride and let others enjoy it too”, not to mention current time and temperature outside.
A fascinating point of our platform is that it brings value to all stakeholders. Starting with a passenger: exclusive, both educational and entertaining, content described in the content section. Next, public transport companies will benefit from increasing the appealing of the public transport among people, thus gaining bigger customer pool, while collecting extra profit from targeted advertisements. As to advertising companies, they are profiting as advertisements are contextual and targeted, it is shown close to a time when the bus is coming near to a stop station and displaying advertisement appropriate for a concrete place by using GPS data and knowing the information about the surroundings. To describe it in more simple words: the bus is coming to a station near which there is a shop "LIDL". At the bus display, a flashing arrow shows the real location of the shops with text "only today apples for 0.50€ kg".
The algorithm is calculating the most wanted data by public transport customers, providers and stakeholders: ecology issues and consumption calculator with an illustrative and easy to understand final data, number of passengers on board (based on weight changes of the bus) and crowdedness in different times (using statistics), timing and temperature collected and given to those vehicles on a line that need it. The time to the next stop is calculated by dividing the distance to the bus’s average speed. Like, the data of time of going from one station to the next one by bus sending it to the next one, "interesting facts" for passengers and useful data for future optimisations to the vehicles host company.
How we built it
We've built it mainly on HTML5. We leveraged AngularJS framework to provide routing, code encapsulation, and separation of concerns on a business-logic level. Styling was done partly using custom classes, partly by those offered by the Bootstrap framework. Business logic is loosely coupled to views and as such can be moved to a different UI implementation.
Challenges we ran into
Finding the ways to use a big amount of data to create something meaningful was quite a challenge, as well as content orienting for different types of people.
Accomplishments that we're proud of
We finally have made a working platform that can be straight integrated into public transport, most content, algorithms, calculations and arising topics are covered and well thought by our team delivering a smooth and stable experience while using it.
What we learned
We've learned to sort out a mess of ideas into one concept with easy-to-understand and at the same time maximum benefit approach.
What's next for Enhancing the public mobility experience
Next, we want to implement a version of the platform accessible from Internet to the mass public for them to know, for example, how many people are on the bus they selected and when to leave home to be on time to the bus with, calculation on its current location and speed and to be able to interact with the display. One of our future concepts is an app to let people know if they want to chat with somebody. The app would matchmake the people and create more pleasant experience. Another option are games or fast pools with data input from the mobile devices.