The digital twin, artificial intelligence and predictive analytics help fans simulate the races of the IndyCar Series using NTT, including the famous Indianapolis 500. Optical sensing learning combined with crowd-flow monitoring also provides valuable pointers to these US motorsport organizers.
When Chip Ganassi Racing’s Marcus Ericsson won the Indianapolis 500 last May, he was in a car equipped with more than 140 sensors to export data feed in particular to predictive analysis algorithms, but also motor racing enthusiasts. NTT, a Japanese telecommunications company and Penske Entertainment partner of the NTT IndyCar chain, including the Indy 500 race, has collected about 8 billion data points from sensors in Marcus Ericsson’s car and those of his 32 competitors. Using data collected from previous seasons and five events The first in the NTT IndyCar series, NTT uses a combination of data analytics, digital twins and artificial intelligence (AI) to give fans access to in-depth insights and real-time information about overtaking, pit stop predictions and other elements of race.
“From a business and sports perspective, our sport has always been about technology development,” said SJ Luedtke, IndyCar Vice President of Marketing. “If you go back to the early days of Indianapolis Motor Speedway, it was built, in some ways, as a proofing ground for the nascent auto industry and a place where the many automakers based here in Indianapolis and across the Midwest could bring their latest inventions and test them out.” Today, according to SJ Luedtke, NTT and IndyCar continue that tradition by thinking about how they can use off-track data to drive participation. “We want to take all this technology and the data that you generate and find ways to create off-track engagement elements for our fans, sponsors and other stakeholders involved in the sport, in order to make it more engaging, more fun and, ideally, attract other fans who might not be interested in cars. They may be very tech-savvy and love data and/or storytelling.”
Improving the experience of motorsport enthusiasts
To this end, NTT has created a digital twin for every car in the series. Historical data provides a baseline, and each car is equipped with more than 140 sensors that collect millions of data points during the race to feed the digital twin. This data ranges from speed and oil pressure to tire wear and G-forces. NTT uses artificial intelligence and predictive analytics on dual digital data to provide fans with insights previously only available to race team engineers, including race strategies, predictions, interceptions and battles for location, and the impact of performance Pothole stops, the effects of fuel levels and tire wear.
IndyCar provides this information to fans through the interactive app and social media channels. It also provides information for the NBC production team. “There is an opportunity for our most passionate fans to connect with a sport they love or a driver or team they love,” says SJ Luedtke. “That’s where the data and the analytics come in. We’re working with the team to take these millions of data points over a 90-minute run and help fans understand what’s going on.”
Make predictions with artificial intelligence
For example, says S.J. Luedtke, it’s common to watch the front of the race, but sometimes it’s in the middle of the group getting lost in the fight. “People compete for places to move up in the overall points system,” she says. “We are able to look at that data in real time and then start making predictions using AI and the smart platform.” You might not change the channel if an NBC analyst mentions your favorite driver is seventh, but you can overtake sixth in five laps because they’re all racing for the championship, you follow.
“We also have the ability to engage casual viewers to help them understand what’s going on in the race,” she adds. “Being able to tell the story of why someone progressed through different key components, or data based on drivers stopping, allows us to explain the sport to new fans.” In just over three years, IndyCar has doubled participation and time in its racing weekend application, says SJ Luedtke. “It’s about being able to see your favorite driver’s telemetry in real time in conjunction with the onboard camera during the race, so you feel like you’re in the cockpit with them,” she says. “You see a lot of telemetry and key data points running in their cars.”
To a more relevant site
In terms of technology, Bennett Endart, Vice President of Smart World Solutions at NTT, described the partnership as a “priority business approach” to “improve the fan experience, encourage others to exercise, and provide a forum to enrich IndyCar with data.” To this end, NTT also uses the data to improve the site’s fan experience. It has published its Smart Venue solution at Indianapolis Motor Speedway (IMS). The app is inspired by efforts to create connected cities that attract more than 350,000 fans on race days.
“We think of it more as the idea of mobilizing and planning how the city will operate for a day, whether it’s getting people or serving them through emergency services or being able to see around corners where we can send someone before the accident,” says SJ Luedtke. To IndyCar, Smart Venue’s AI technology provides complete visibility of the venue, with data calibrated every 30 seconds with over 90% accuracy.AI-based optical sensing technologies, combined with real-time gate transmission data, allow crowd movement to be monitored, analyzed and escalated alerts They also provide information on congestion and congestion at specific gates and tunnels. Ultimately, this provides better response times to respond more effectively to potential issues and risks.
For supporters, Smart Venue provides better visibility into the fastest and least crowded routes through the world’s largest sporting event. “On any given race day, it becomes the second largest city in Indiana,” Endart says. “You can imagine 350,000 people trying to get to Indianapolis Motor Speedway. For several years, we’ve been helping the operations team understand where the bottlenecks are. This year we’ve added a feature to make that available to the same fans on their mobile devices.” “It’s all about data and data-driven approaches to solving business scenarios,” Endart adds.