Formula 1 will work with AWS to enhance its race strategies, data tracking systems, and digital broadcasts through a variety of AWS services — including Amazon SageMaker, a fully managed machine learning service that enables everyday developers and scientists to build and deploy machine learning models, AWS Lambda, AWS's event-driven serverless computing service, and AWS analytics services.
Formula 1 has also selected AWS Elemental Media Services to power its video asset workflows, hoping to enhance the viewing experience for its 500 million fans worldwide.
Using Amazon SageMaker, Formula 1’s data scientists are training deep learning models with more than 65 years of historical race data, stored in both Amazon DynamoDB and Amazon Glacier. With this information, Formula 1 can extract critical race performance statistics to make race predictions and give fans insight into the split-second decisions and strategies adopted by teams and drivers.
For example, Formula 1 data scientists can predict when the window of opportunity is opening and closing for teams to pit their cars for maximum advantage, as well as determine the best timing for changing tires.
By streaming real-time race data to AWS using Amazon Kinesis, Formula 1 can capture and process key performance data for each car during every twist and turn of the Formula 1 circuits with unmatched accuracy and speed. Then, by deploying advanced machine learning via Amazon SageMaker, Formula 1 can pinpoint how a driver is performing and whether or not drivers have pushed themselves over the limit. By sharing these insights with fans through television broadcasts and digital platforms, Formula 1 is improving the fan experience, allowing them to dive deep into the inner workings of their favorite teams and drivers.