Light Reading Podcasts IndyCar and NTT take predictive analytics to the speedway
Behind the wheel, NTT and IndyCar are using tools such as predictive data analytics and digital twins to improve the race experience for both IndyCar teams and fans of the sport.
"NTT is taking a lot of the unseen and we're working to make it more visible to the fans to help them understand what's going on in the race, what they should look for and where they should look for it to happen," said SJ Luedtke, VP of marketing for IndyCar.
Luedtke and Bennett Indart, VP of SMART world solutions for NTT, join the podcast to explain what it takes from a network standpoint to collect and analyze the data produced during the race.
"We're using predictive analytics in a lot of different places," said Indart. That includes analyzing pit strategies and anticipating which drivers will make a move during the race.
"We're trying to take and distill stories buried in billions and billions of messages coming off the cars during the day, and we're allowing artificial intelligence and predictive analytics to do that," he explained.
Editor's note: This podcast was recorded ahead of last weekend's IndyCar race in Detroit, Michigan.
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Here are a few highlights in the podcast:
- Impact of predictive data analytics on the race and fan experience (01:00)
- Data monitoring technologies and private networks (05:20)
- Popularity of IndyCar and the draw for fans (09:06)
- Applying learnings from IndyCar to smart cities applications and other entertainment venues (12:53)
- Digital twins, data twins and visual twins (16:14)
- Utilizing trends in historical data for future races (19:07)
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