Reported impact
Business outcome
TRACAB increased collected data to more than 255 million data points per match, achieved average latency of 0.85 seconds, reduced manual work by shifting from two onsite operators to one remote operator, and expanded to nearly 200 stadiums running more than 2,000 matches per year.
- Customer Experience
- Productivity Improvement
- Scalability
- Speed to Market
Solution
TRACAB migrated its sports-tracking platform from on-premises arena servers to AWS so it could scale computer-vision processing and deliver richer match insights in near real time. Video and tracking data from multiple cameras is sent to AWS, where deep-learning models run on Amazon EC2 G4, G5, and G6 GPU instances to identify players, the ball, and new skeleton-tracking signals. Low-latency state and event access is supported by Amazon ElastiCache for Redis and Amazon DynamoDB, letting downstream consumers such as broadcast teams, referees, coaches, and fans use the data quickly. The cloud architecture also let TRACAB automate work that once required two onsite operators, support a remote operator model, and continuously deploy new features such as semi-automated offside technology and virtual cameras across nearly 200 stadiums.
Data flow
Multi-camera match video and tracking data is streamed to AWS, processed by deep-learning models on GPU-backed Amazon EC2 instances, stored for low-latency access in Amazon DynamoDB and Amazon ElastiCache for Redis, and then delivered as near-real-time insights to broadcasters, officials, coaches, players, and fans.