RAIS: Real-time Analytics and Intelligent Systems for Human Activity
- Sofia Yfantidou
- Oct 1, 2023
- 2 min read
The RAIS (Real-time Analytics for Internet of Sports) project is a Marie Skłodowska-Curie Innovative Training Network (ITN) that set out to train 14 Early-Stage Researchers (PhD fellows) in the rapidly evolving intersection of wearable sensing, blockchain-enabled IoT, and real-time edge analytics.
By fostering collaboration between academia and industry, RAIS aimed to create a new generation of scientists capable of developing intelligent systems that can capture, interpret, and act on human activity data, from daily movement to elite performance.
As an industrial partner, Kinetic Analysis played an active role throughout the project, connecting cutting-edge research with real-world applications in sports science, rehabilitation, and digital health.
Building on the relationships formed during RAIS, Kinetic Analysis remains actively involved with partner universities and former fellows in follow-up research efforts and technology development projects.
Throughout the project, Kinetic Analysis participated in several RAIS network events across Europe, engaging directly with the fellows and the wider research community. During the RAIS Research Meeting in Stockholm (2021), the company interacted closely with the fellows, discussing potential collaboration pathways and secondment opportunities. Later that year, at the RAIS Summer School in Heraklion, Kinetic Analysis delivered a lecture titled “3D Analytics for Human Motion Data.” The session highlighted how three-dimensional representations of the physical world, which are increasingly captured through advanced sensor technologies, can be transformed into valuable knowledge for trainers, clinicians, and researchers. The collaboration culminated in 2023 in Nicosia, where Kinetic Analysis led the RAIS Hackathon: “Field Hockey Drag-Flick Challenge.” In this hands-on event, participants worked with an exclusive dataset of 1,500 field hockey drag-flick movements, recorded using a 17-sensor full-body motion capture setup. Fellows were invited to tackle real-world analytical challenges, from segmenting keyframes and predicting ball speed to identifying minimal yet effective sensor configurations and comparing different analysis methods. Five multidisciplinary teams from universities including the Aristotle University of Thessaloniki, KTH Royal Institute of Technology, University of Cyprus, Foundation for Research and Technology Hellas and University of Insubria, collaborated to propose innovative approaches to motion analytics, blending biomechanics, machine learning, and domain knowledge.
Through its participation in RAIS, Kinetic Analysis reinforced its role at the intersection of AI, movement science, and sports technology. By hosting secondments, sharing expertise, and co-developing solutions with early-stage researchers, the company helped foster a new generation of scientists equipped to build the intelligent systems of tomorrow.
