Media-focused sport sensor data platform for professional content creators to create interesting stories using meaningful data.

DAIQUIRI, Data & Artificial Intelligence for QUantifIed Reporting In sports, influences the way in which editors, directors and content makers conduct their job in a profound way. DAIQUIRI is developing AI algorithms that address current challenges associated with data overload, sensor-video matching, dynamic captioning and multi-modal stories. The outcome will be a scalable data workflow to support media channels translate sports sensor data into engaging, real-time messages with visualization.

These days, more data is captured during sports events, e.g. sensors attached to bikes or athlete wearables. However, these data sources still remain insufficiently used in sports coverage on TV. The missing gap is the adequate translation of the sensor data into useful narrative elements tailored to be used and integrated in real-time dynamic visualizations and storytelling for sports events.

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 into professional storytelling formats.

  • Optimize sensor connection, data linking and quality to reduce data flow by 30%.
  • Stimulate personalized user experiences with real-time dynamic visualization and data flow to gain insights.
  • Develop AI algorithms that allow to generate different types of story fragments.
  • Set up various storytelling techniques to enrich traditional reporting with insights from sensor data.

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Prof. Dr. Steven Verstockt

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