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O C E A N S O F D A T A

O C E A N S O F D A T A A dedicated team of experts is collaborating behind the scenes to lead the Land Rover BAR team to victory in the 35th America’s Cup. Their tools: advanced computer science, massive data sets, sophisticated algorithms and real-time feedback loops WORDS C H R I S S T O K E L - W A L K E R 42

SMART BOATING 80 MILLION COMPUTATIONAL CELLS ANALYZED PER TEST RUN 56 PER SECOND RECORDINGS LOGGED FROM BOATING MANEUVERS COMPOSING: GETTY IMAGES, DPA PICTURE ALLIANCE, HARRY KENNEY-HERBERT The battle for the America’s Cup is as turbulent now as any time since the first competition was held around the Isle of Wight in 1851. Over the intervening 166 years, there have been battles on sea, on paper and in the courts, to win what’s affectionately known as ‘the Auld Mug’ by those who strive to hold it. But now – as Land Rover BAR prepares its final sprint to bring home one of the most coveted trophies in sporting history – the fight is on a new, more advanced frontier: big data. The full effect of this will be seen in June, when Sir Ben Ainslie and the Land Rover BAR team set sail on the Bermudian waters for the competition’s 35th iteration with the aim of bringing the title back to Britain. To help them underway, Jaguar Land Rover experts and engineers have been tasked with harnessing the power of big data with artificial intelligence in a one-of-a-kind partnership using the very latest sensor technologies and advances in data science to improve boating performance and put the team in front. “We’re working flat out,” admits Jim Johnston, who heads the innovation acceleration team at Jaguar Land Rover. Jim is in charge of finding smart solutions that can help push the Land Rover BAR team to the very front of their field, off and on the water. To help create these smart connections, Jim is supported by people like Jaguar Land Rover engineer Mauricio Muñoz. Mauricio, a former MIT student, is embedded directly with the Land Rover BAR team, spending half his working week at their sleek state-ofthe-art dockside headquarters on the serene Portsmouth sea front, in the UK. His role is to analyze data received from the Land Rover BAR’s America’s Cup Class boat using powerful machine learning techniques that can find patterns across everything the sailing team does during their pre-America’s Cup training. The data comes from close to 300 channels, including fiber optic sensors on the boat that log data at an astonishing 500 times per second. They then feed it back to the team in Portsmouth led by Mauricio, helping him to better understand how improved performance on the water has been achieved. Next, the information is looped back to the design and concept teams in order to validate their theoretical models of how the boat should behave with actual, observed data, allowing them to use the information to improve and adapt their boat designs. Spotting minute differences between modeling concepts and data insights is crucial because the performance differences between boat components aren’t between one to five knots, but rather in the 0.1-0.5 knot range. By logging performance parameters like lift, drag and side force as well as total airflow, the team can calculate what is required to achieve for example optimum straight-line performance, perfect tack and gybe maneuverability or component weight; in other words those elements that make the difference between winning and losing the America’s Cup. “We’ve got sensors logging everything, from which buttons were pressed to the wind speed at the top of the mast. It all adds up,” says Richard Hopkirk, Engineering Manager at Land Rover BAR. Richard joined the team following time at McLaren Racing – where the split-second differences between pole position and a nonpodium finish are derived from harnessing on-track feedback from data streamed back to the paddock by the cars. “A human might spot the odd pattern on screen,” he says. “But they’d have to look pretty hard. Massive data sets combined with machine 43

 

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