Formula One cars are essentially big data factories on wheels. They have hundreds of sensors across many components collecting data on everything from fuel levels and engine performance, to oil temperature and tyre pressure.
Turning that data into useful information to tweak a car’s performance is nothing new in Formula 1. But driving efficiency in the analysis process so that data can shave race-deciding tenths of seconds from lap times could be the difference between winning and losing.
V3 visited the Silverstone racetrack to talk to the Williams F1 team ahead of the British Grand Prix to hear how, having joined with IT services and consulting firm Avanade, it’s aiming to improve the way it uses big data in the quest for glory.
Data driven
Big data collected from F1 cars is vital for maximising performance. It starts at the design stage of a new car, by using previous race data to see where improvements can be made. Further analytics can then be used to maximise component performance as the car is built.
Data collected and analysed during wind tunnel testing is also used to fine tune the aerodynamics of the car to extract the best performance within F1 regulations.
F1 teams will use the data gleaned from the process to configure the cars for the course during the day of track testing ahead of a Grand Prix weekend.
When the race starts, a team of engineers monitors the deluge of data transmitted from the car, and uses it to inform the driver about tactics and strategies.
Graeme Hackland, Williams’ chief information officer, said that his race team generates around 120GB of data from sensors, telemetry and video feeds over the course of a race.
“During the race we’re making decisions on when we should tell the driver to push, when we should tell them to back off,” said the former Lotus F1 CIO.
“There’s a lot around the strategy during the race that relies on multiple data sources.”
However, Hackland explained that preparing this data for analysis was a time- and resources-sapping process for the Williams engineers, who were spending 70 percent of their time during races working on data preparation and just 30 percent actually analysing the data.
“[Williams] has really good engineers and they were spending some of their time doing software development and some of their time on their main job,” he said.
This meant that engineers were losing valuable time getting hold of the data they needed to analyse, rather than quickly gaining the necessary performance information. It also meant that making use of the data back at the Williams factory required more preparation, which also slowed the analysis process.
Stringent F1 regulations mean that a significant amount of testing is needed to extract as much performance from F1 cars as the rules allow.
The time and resources absorbed in preparing data for analysis eats into the engineers’ testing time and can affect the overall performance of the race team.
Accelerated analytics
This problem prompted Williams to acquire external help from Avanade, which became a technology partner in January 2015. Avanade now works with Williams to ease the process of preparing data for the engineers to analyse.
Colin Burrell, Williams client executive at Avanade, said that the partnership has seen the firm provide analytics systems that relax the pressure on the team’s engineers to develop software that can handle big data.
“We’ve taken off the burden of building systems. We came in and helped take vast amounts of data and give [engineers] useful, meaningful feeds so that they can see immediately what’s happening on the car, rather than just having lots of data and trying to interpret what it means,” he said.
Hackland agreed that tapping into Avanade’s expertise allowed Williams’ engineers to be more effective with their data analysis.
“What we’ve been able to do with the relationship with Avanade is give them resources to do their software delivery [for them] so they can focus on their main job,” he said.
“It’s given us a software development capability and an assistance in our digital journey that gives the engineers access to data that they couldn’t get to on time before.”
He added that applications being developed by Avanade for Williams enable engineers working on different parts of the cars to filter the data they need from a combined pool of harvested information.
In turn, this allows the engineers to make better strategic decisions during races, and operate faster and more efficiently when working on the development and configuration of the Williams cars back in the factory.
Pitlane predictions
The technology provided by Avanade can also allow predictive analytics to be brought into play, according to Burrell.
This allows Williams to calculate the performance of the cars on a certain track based on historical data and other sources such as weather forecasts.
The team can then run simulations and establish a better base configuration for the car so that optimising during track testing is more efficient and effective.
“They’ll have a view on what happens if they don’t get away as quickly [off the line] or if they come out of the pit behind someone,” said Burrell.
“They’ll have scenarios and work-through views, so they’ll use the system to do predictive [analytics] as well.”
With all this data in play Williams will be hoping to be challenging for the chequered flag on Sunday at Silverstone.
F1 has always looked to adopt the latest innovations in engineering and IT. Doubtless this will continue, as the sport acts as a showcase for the cutting-edge systems that find their way onto the road and into the enterprise world.
F1 is not the only sport that makes use of analytics. The Extreme Sailing Series uses SAP’s Sailing Analytics to harness cloud-powered big data analytics, which provide insights to sailors, spectators and commentators.
