THE FASTEST CARS DESERVE
THE FASTEST CLOUD
FORMULA 1 is a battle between the world’s best drivers, but it’s also a battle of some of the world’s most innovative engineers. No other sport has been as dynamic in its evolution and embrace of new technology. While some of the tech goes to helping drivers, who are hitting speeds as high as 230 MPH, taking pit stops in under 2 seconds, and flying around corners with a force of 5G, much of it goes to enhance the experiences of its growing base of over a half a billion fans. This is why AWS is proud to be both the official cloud service and machine learning provider for FORMULA 1.
Here’s how it works:
Learn More About Car Analysis / Car Development from the Expert
Rob Smedley, Chief Technical Engineer - F1 Performance Engineering and Analysis, details the importance of the new F1 Insight. Focusing on the three core elements of F1 car development, the graphic will measure development of performance in Aerodynamic Drag, Aerodynamic Downforce, and Engine Power, built on lap time analysis and using telemetry data as the primary source input.
Learn More About Corner Analysis from the Expert
Rob Smedley, Chief Technical Engineer - F1 Performance Engineering and Analysis, details the importance of the new F1 Insight, Corner Analysis. This provides an insight into the detail of why some cars perform better than others through high and low speed corners – the single most important area for performance for an F1 car – by analyzing and comparing the performance through the principal sections of a corner via car telemetry data.
AWS and Formula 1 Announce New Racing Performance Stats for 2020 Season
First of six real-time racing statistics to debut July 3 weekend with the launch of “Car Performance Scores” at the season opening Grand Prix in Spielberg, Austria
Learn More About Car Performance Scores from the Expert
Rob Smedley, Chief Technical Engineer - F1 Performance Engineering and Analysis, details the importance of the new F1 Insight Car Performance Scores. These important aspects of Formula 1 car performance give fans a much clearer understanding from the very outset of how the different cars perform relative to each other.
Formula 1 Works With AWS To Develop Next Generation Race Car
The F1 Computational Fluid Dynamics project utilized over 12,000 hours of compute time to design the race car for the 2021 season. Watch F1 Chief Technical Engineer Rob Smedley’s re:Invent keynote on partnering with AWS to change the design and improve the fan experience. Visit the link below to read the press release about project.
ACCELERATING THE FAN EXPERIENCE
Want to look under the hood and see how it’s done? Learn more about how AWS and F1 are using data to teach Amazon SageMaker complex machine learning algorithms that deliver new insights and increase action for fans, predicting outcomes with impressive accuracy as races unfold, and using data to design the next race car.
IT STARTS WITH THE DATA
During a FORMULA 1 Grand Prix every car contains 120 sensors which generate 1.1M telemetry data points per second transmitted from the cars to the pits. This real-time data is combined with over 69 years of historical race data stored on S3 to inform fans and teams about the unparalleled track-side decision making.
SHIFT THE FAN EXPERIENCE INTO GEAR
By sourcing historical data and using it to teach Amazon SageMaker complex machine learning algorithms, F1 can predict race strategy outcomes with increasing accuracy for teams, cars, and drivers. These models are then able to predict future scenarios using refreshed realtime data as Grand Prix races unfold to deliver a rich and engaging fan experience.
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