Skip to main content

Semantic EnrichmEnt of trajectory Knowledge discovery

Article Category

Article available in the folowing languages:

Mobile devices’ whereabouts to help enrich applications

The mobility patterns extracted from our mobile device signals can be very useful in a number of applications. This has led to new research on exploiting the wealth of data provided by these devices.

Digital Economy

Mobile technology is moving at an unprecedented rate and can help citizens and communities in a myriad of ways. The data collected from mobile phones on the move, for example, can help redirect traffic and assist transport management. With this in mind, the EU-funded SEEK (Semantic enrichment of trajectory knowledge discovery) project investigated how to improve data collection from mobile devices’ trajectories. It focused on the semantic aspect — or the meaning of the movement — to exploit the data more efficiently and use it in a number of applications. To achieve its aims, the project team identified several potential applications and studied how best to collect and process the data, including techniques for filtering, manipulating, enriching, storing and analysing movement data. This was achieved through a so-called data warehouse that collects newly defined semantic trajectories. In more detail, the project looked deeply into semantic knowledge discovery. It examined specific discovery methods that look behind the meaning of the trajectory rather than just the trajectory itself. This involved mining different properties of a trajectory, as well as articulating new post-processing and visualisation methods to yield more meaningful information. Furthermore, SEEK studied the social aspects of the movement in question. It looked at social networks and trajectory interactions, opening new and exciting challenges in research. One notable application that has emerged from the project is the TripBuilder digital travel agent prototype, which provides the best itinerary for tourists. It achieves this by balancing the interests and time budgets of individual users with the ‘wisdom of crowds’ mined from Wikipedia, Flickr and Google Maps. Another application is ComeWithMe, which analyses car trajectories in cities to identify carpooling possibilities based on destination, while integrating user flexibility. The project’s results and outcomes have been disseminated to interested parties through workshops, journals and conferences. The technology and know-how could have many positive implications in different sectors and fields, from transport and tourism through to business and security.

Keywords

Mobile devices, semantic trajectories, digital travel agent, wisdom of crowds, carpooling

Discover other articles in the same domain of application