Daiquiri - Data & Artificial intelligence for Quantified Reporting in sports

Journalism
Artificial intelligence (AI)
Storytelling
Broadcast

How can data be generated by sensors or athletes' monitoring devices support commentators with their coverage on sports events for broadcasts?

Daiquiri brings together sports, data and journalism. The project will develop a scalable data workflow to support broadcasters in innovating/augmenting live sports reporting while leveraging the IoT data. The availability of data sources from video or IoT devices, e.g. sensors attached to bikes or athlete wearables, is growing and can make reporting more interactive, informative and attractive. However, these data sources are still hardly used in sports events broadcasts. The Daiquiri project is aimed at the automatic aggregation of data from available sensors or monitoring devices and the generation of meaningful insights about the circumstances of an athlete, team performance, integrating it into professional storytelling formats. To do so, it uses the cases of hockey and cyclo-cross racing.

We at imec-mict-UGent are helping to understand the workflow of commentators and journalists (through observations and interviews), find their pain-points and co create a possible solution with them.

Partners: VRT Innovatie, NextGen Sports, Videohouse, imec-IDLab-Antwerp, imec-IDLab-UGhent

Project Duration: 01/10/2019 - 30/09/2021

Contact: Lieven De Marez