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Formula 1 (F1) is a hugely popular sport globally and its popularity continues to grow. The expansion of its fan base was certainly helped by the super entertaining Netflix series Drive to Survive, which engaged even the most casual of viewers and even those who had never even watched the sport. It is also one of the most technically sophisticated sports on the planet which has attracted technology companies like Amazon Web Services (AWS), AMD, Cognizant, Dell and Oracle to sponsor either the F1 organization or a specific team. Their firms’ technologies are used to simulate the impact of new design changes, analyse real-time data from in-car sensors and to host platforms for its fans.
It’s hard to overstate the role technology plays in F1 racing. Every F1 car contains some 300 sensors which generate 1.1 million telemetry data points per second transmitted from the cars to the pits. During each race weekend 160 terabytes of data is sent between the remote race circuit and the F1 Media and Technology Center in Biggin Hill, England.
F1 teams are using cloud technology to shave hundredths of a second off their lap times—a razor-thin margin between winning and losing. Digitizing the research and development also levels the playing field for teams previously at a disadvantage when it comes to budgets, essentially democratizing data of this notoriously expensive sport.
The data-driven approach has changed the sport dramatically over the past few years. Those 300 in-car sensors measure a wide range of inputs, including temperature, fuel, tyre pressure/wear, trajectory, and the drivers themselves. The figures collected from Formula 1’s ten teams over a season can generate more than one billion simulations that shape each team’s race-weekend strategy.
“The car is packed full of sensors because the difference between pole position and the back of the grid can be as little as 4%,” says Edward Green, head of commercial technology for McLaren Racing. “It’s a sport of superfine margins, and you’ve got to find any single way you can in order to gain an advantage.”
Gone are the days when F1 teams sent their data back to their headquarters on portable disk for analysis. Now, they use the cloud to capture terabytes of data during a race weekend and transmit it across the world in near real time, narrowing latency from a few days down to milliseconds.
The ten teams on the grid use a range of cloud technology providers. Among them; Red Bull uses Oracle Cloud software to aid decision making - like pit stops for example. Ferrari has partnered with Amazon Web Services, which provides cloud computing and machine learning to run simulations. McLaren uses Dell prototyping and simulation software. Alfa Romeo have linked up with Zadara, a recognized leader in edge cloud services. KX is the official supplier of real-time data analytics to the Alpine F1 Team. McLaren have also teamed with Splunk to deliver software to monitor and analyse machine generated data and also provided simulator systems. The list goes on.
The next frontier for Formula 1, like a lot of industries, will be artificial intelligence, with teams already using AI across a wide range of its activities – including car setups, development directions and resource deployment.
It's playing a part in race strategy planning too, and after the 2021 campaign, with its thrilling and somewhat controversial finish that saw Max Verstappen edge out Lewis Hamilton for the title on the final lap at Abu Dhabi, it proved how critical strategy is to victory in F1, and how high the penalty can be when the pitwall and race control gets it wrong. It is clear what the attraction could be for a successful AI model. After all, it shouldn't crack under pressure and in theory it should deliver the right answers based on evaluating a data set far wider than a human could ever get through, and it would never be worried about what the media will have to say about it the next day.