idalab joins “Smart Data for Mobility – SD4M” consortium, led by Deutsche Bahn Systel

Berlin-based data science agency idalab joins forces with DB Systel (IT-subsidiary of German railway operator Deutsche Bahn), The German Center for Artificial Intelligence (DFKI), init and PS-Team to develop a cross-sector mobility service platform, aggregating data from various sources to provide smarter mobility services. The 3-year research program, funded by the German Federal Ministry for Economic Affairs and Energy, is aimed to enhance intelligent management of mobility-related data and improve mobility quality in Germany.

Improving the intermodal transport experience has been the focal point of recent start-up attention: new mobility apps get launched almost weekly, aiming to provide a smoother travel experience for customers by combining modes of transport into one easy-to-use framework. One of the market leaders is quixxit, an application for intermodal travel in Germany, providing customized options across bike, car, train, bus and various other modes.

However, going beyond quixxit, drawing on faster real-time public data and thus allowing for live bottom-up validation of scheduling information still remains a challenge. Under the auspices of the German Federal Ministry of Economic Affairs, idalab as part a consortium of leading industry experts was chosen to tackle this situation and pave the way towards more innovation in the mobility sector.

Data and mobility experts from Deutsche Bahn, the German Center for Artificial Intelligence, init, PS-Team and idalab will work together to develop a big data analytics platform, geared to aggregate and analyze mobility data from various sources. These sources will not only include scheduling and real-time data from various transport operators, but also social media data from Facebook, Twitter and the likes to enable new, intelligent and innovative data analytics.

The data analytics platform will form the backbone of new mobility services, such as intelligent transportation assistants, which will actively guide travellers during their multi-modal journey, helping to proactively avoid traffic jams, rush hour and navigate new options if public transport runs off-schedule. In the scope of the project, DFKI will be responsible for aggregation and matching of data from structured (schedules etc.) and unstructured sources (primarily social media) to allow for novel insight through semantic interoperability. Using this platform, data science agency idalab will focus on traffic prediction and subsequently optimization of travel route suggestions.

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Paul von Bünau
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