Daiquiri Project
Data Management
The DAIQUIRI project aimed to develop a scalable data workflow to support broadcasters in innovating/augmenting live sports reporting while leveraging Internet of Things (IoT) data. This would encompass the automatic aggregation of data from available sensors or monitoring devices, the generation of meaningful insights about the circumstances of an athlete or team performance and the integration of this insight into professional storytelling formats. The approach would be demonstrated in two different use cases: cyclocross and hockey.
The use of artificial intelligence (AI) in professional sports is an emerging trend that will impact nearly every major professional sport in the coming years. Pilot applications include live game information chatbots, automated game reporting and the use of sensors and wearables to provide athletes and coaches with meaningful performance insights. This trend is enabled by an increasing amount of data coming from a larger number of data capturing or generating devices such as sensors attached to bikes, athlete wearables and video cameras.
Currently, these data sources are hardly used in sports events broadcasting, despite the potential to make reporting more interactive, informative, personal and attractive.
Traditional reporting needs to reinvent itself, but that requires adequate translation of the data into useful narrative elements (‘’something happened”), tailored to be used and integrated in real-time dynamic visualizations and storytelling for sports events.
