Capture of POI for charging stations


Clearing the way for electromobility

Thinking out of the box. Positioning charging stations with the help of crowd data.

The worldwide widespread use of electric vehicles is still in its infancy. The parties involved are therefore working to eliminate teething problems.

Some key challenges met in electric mobility are the electric vehicles’ (EV) limited driving distance and the availability of charging infrastructure. From a customer point of view, the charging process needs to be integrated into everyday life in order to avoid any time-consuming detour.

Where’s the juice?

In the race for the distribution of this future technology, no one can afford to stay behind – especially, this automotive OEM who is well known for their premium cars’ acceleration and speed! Thus, it was crucial for the OEM to understand their customers’ mobility behaviour to provide charging points for EV’s exactly where they are needed. This is how, well known for its unorthodox solutions, umlaut was asked for help to create transparency through an innovative approach: umlaut’s crowd data!

Motivated by applying new approaches to assess the performance of mobile network services, umlaut developed a Software Development Kit (SDK) which gathers data from end user devices. The SDK is already integrated in more than 800 applications reaching more than 200 million devices worldwide and generating almost 5 billion data points per day. This data has been successfully used to explore many insights related to the network performance and quality of user experience of mobile networks and services.

Digital does it.

It was time to ask new questions! The high penetration of smartphones and the resulting large-scale location information offers a considerable opportunity for commercial, governmental, and academic applications using analysis of people’s locations and movements. Using the OEM’s knowledge of its customer profiles, the solid crowd data base and a clear understanding of electric mobility and charge point requirements, umlaut got started!

Critical success factors were flexibility, scalability, and reliability in handling and processing the data. Thus, the usage of cloud services was indispensable. Special efforts were made to develop methodologies for cleaning the data, dealing with missing features, and deriving statistically valid insights on different metrics.

The power of the crowd.

By combining crowd data with the well-known customer profiles, umlaut was able to find the OEM’s potential customers within the sheer amount of data points. Having identified these users, the samples were aggregated and plotted on a map and frequently driven roads and regularly visited points of interest (POI), such as supermarkets, gym’s and fuel stations, were highlighted.

Having provided the resulting mobility behaviour of the identified users and the list of highly attractive POI, the OEM was now prepared to approach specific asset and infrastructure owners rather than guessing potential cooperation partners.

Thanks to a small piece of software and by thinking out of the box, umlaut was able to provide additional transparency and add value on “töp”, by simultaneously saving both time and manpower.