A naukri.com initiative
Amazon
5d
176
Image Credit: Amazon
AWS machine learning supports Scuderia Ferrari HP pit stop analysis
- Formula 1 pit stop analysis has been modernized with AWS machine learning, aiding Scuderia Ferrari HP in developing accurate techniques.
- Previously, manual review of video footage and telemetry data was time-consuming, now AWS solution synchronizes data 80% faster.
- Scuderia Ferrari HP leverages AWS cloud and ML to automate and centralize pit stop analysis, improving efficiency and accuracy.
- AWS partnership helps Ferrari detect errors faster, comply with budget caps, and innovate on and off the track.
- The ML-powered pit stop analysis syncs video with telemetry data, identifying anomalies automatically during pit stops.
- Model trained using YOLO v8 algorithm and PyTorch framework provides greater consistency and reliability in pit stop performance.
- Automated correlation of video progression and telemetry data helps refine processes and reduce errors affecting race results.
- The solution, deployed at the 2024 Japanese Grand Prix, records faster pit stops like the season best of 2 seconds flat in Saudi Arabia.
- The workflow involves using AWS Lambda, SageMaker AI, Amazon ECS, and Amazon S3 to streamline the pit stop analysis process.
- AWS solution enables real-time insights, systematic review, and identification of patterns to enhance pit crew performance.
Read Full Article
10 Likes
For uninterrupted reading, download the app