AWS for M&E Blog
Racing against time: How SRO Motorsports cut inspection time by 83% with AWS
In the high-octane world of racing, precision and fairness are non-negotiable. SRO Motorsports America (SRO), the organization behind GT World Challenge America, partnered with Amazon Web Services (AWS) Professional Services to revolutionize how race car compliance is verified—transforming a 90-minute manual process into an automated system that takes less than 15 minutes. This collaboration not only streamlined race operations, but also laid the groundwork for future data-driven Balance of Performance (BoP) using machine learning.
Enabling trackside precision with the AWS Cloud
The technical scrutineering process ensures that each race car—whether Toyota, BMW, Hyundai, or Acura—complies with exacting technical regulations for competition and safety standards. Before working with AWS, SRO’s technical officials spent up to 90 minutes manually processing logged vehicle data from onboard systems, which creates operational bottlenecks during already hectic, time constrained race weekends.
The new AWS-powered scrutineering system automates logged vehicle data processing through a sophisticated data processing pipeline that performs 102 unique compliance checks. Potential issues are flagged through intuitive dashboards for technical officials to instantly highlight potential compliance violations. “Working with AWS has fundamentally transformed how we approach technical compliance in our Touring Car series,” said Greg Gill, President and CEO of SRO Motorsports America. “What used to be a manual, time-intensive process is now streamlined, precise, and data-driven—allowing our technical team to focus on what matters most: fair competition and an exceptional racing experience.”
Behind this transformation lies a robust AWS Cloud architecture designed for reliability, scalability, and performance, especially important in the challenging environment of a race weekend. The system begins trackside with edge devices collecting data files from race cars. This data then flows through Amazon Simple Storage Service (Amazon S3), which triggers the automated processing pipeline. Amazon Elastic Compute Cloud (Amazon EC2) instances handle specialized file conversion tasks, while AWS Lambda functions analyze the decoded data against technical regulations. Finally, Amazon QuickSight dashboards provide interactive visualizations used by the technical officials.
This dramatic improvement was proven in real-world conditions during testing at Sebring International Raceway, where the system processed data from multiple vehicles with unprecedented speed and accuracy. This freed technical officials to focus on deeper analysis rather than routine data processing. “The 83 percent reduction in scrutineering time has been extremely valuable for our race operations,” noted Gill. “What previously took our technical teams 90 minutes can now be completed in under 15 minutes. This efficiency gain not only improves the experience for our racing teams but also allows us to allocate resources to enhancing other aspects of the race weekend.”
Machine learning drives fair competition
In multi-brand racing, different manufacturers compete with inherently different vehicle characteristics. The BoP system is the great equalizer to ensure fair competition. BoP adjustments include adding weight ballast, restricting engine power, or modifying aerodynamics. This is done to create a level playing field where driver skill determines the winner, not manufacturer differences.
SRO Motorsports and AWS developed a forward-looking machine learning (ML) approach to BoP that promises to revolutionize this critical aspect of racing. AWS Professional Services built and trained advanced ML models capable of predicting lap times based on driver skill, track characteristics, aerodynamic parameters, and performance ballast. This data-driven foundation will eventually enable more responsive, fair, and transparent performance balancing across diverse vehicle types.
“The machine learning BoP capability we’ve built with AWS represents the future of motorsport competition.” said Gill. “We envision a world where real-time data drives fair competition across diverse vehicle types, enhancing the Touring Car racing experience for drivers and fans alike. This is just the beginning of how we’re using AWS technologies to reimagine motorsport.”
The future implementation roadmap for fully data-driven BoP includes expanded testing with wider ballast variations, model refinement, and a phased deployment. Starting with the ML model providing advisory input alongside traditional methods, SRO plans to enable real-time BoP adjustments in Touring Car in the future.
From checkered flag to digital victory lap
By automating scrutineering and laying the groundwork for continued data-driven Balance of Performance, SRO Motorsports has positioned themselves at the cutting edge of motorsport innovation. The 83 percent reduction in scrutineering time delivers immediate value today, while serving the long-term vision of Balance of Performance promises to transform how fans, teams, and drivers experience racing tomorrow. With future innovations on a strong foundation, SRO hopes to provide the most competitive and balanced racing for fans worldwide.
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