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Can Real-Time Data Help Win a Race? DS Virgin Thinks So

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Can Real-Time Data Help Win a Race? DS Virgin Thinks So

Formula E race

DS Virgin Racing needed IoT data analytics on the side of the track.

Sep 12, 2016

Name of Organization: DS Virgin Racing

Industry: Sports

Use case: Asset performance and monitoring

Location: Dinnington, South Yorkshire, UK

Business Opportunity or Challenge Encountered:

All-electric cars aren’t just for zipping about town – they now have their own racing event.

The FIA Formula E Championship, launched in September 2014, is a global auto racing competition that uses only electric-powered cars. The maximum power a car can use in a race is limited to 170 kW, and FIA places strict race pit headcount restrictions, allowing only 15 people for each team, including drivers.

Capturing and analyzing real-time race information is key to optimal performance, and DS Virgin Racing –- jointly led by Sir Richard Branson and the Virgin Group and DS Automobiles — is taking advantage of the Internet of Things (IoT) to equip cars with sensors that track performance, wear, and what needs to be tuned.

DS Virgin Racing needed IoT big data analytics at its UK headquarters to analyze and improve race car performance. It also needed trackside support for collecting the data, transmitting it to headquarters, and providing real-time feedback to the driver and racing team.

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How This Business Opportunity or Challenge Was Met:

Implementing, managing, and operating an analytic infrastructure at Formula E races in major global cities and at headquarters is a daunting challenge.

DS Virgin Racing turned to HPE to help design a solution of hardware, software, and services under HPE Foundation Care, including HPE IDOL advanced enterprise search and data analytics. The implementation let the racing team understand the IoT sensor data in real time for  analytics, archiving, discovery, content management, data protection, and marketing optimization.

An implementation of HPE Vertica Advanced Analytics software also let DS Virgin Racing to take advantage of advanced SQL database analytics. The solution also included the HPE Moonshot energy-efficient, integrated server system, Aruba Wireless Networking, and HPE 3Par StoreServ 7400 storage infrastructure.

The implementation involved a complex IT environment that could operate in multiple locations. Since the race travels to major worldwide cities, DS Virgin Racing needed a business-critical support experience in each race location—including the ability to swiftly access spare parts as well as the ability to support the setup, operations, and breakdowns for each race.

At headquarters, the infrastructure is constantly being optimized to support high-speed analytics. Capabilities include 24×7 monitoring, pre-failure alerts, rapid diagnosis, and automatic call logging with parts dispatch for hardware support. HPE scans the connected devices, provides a health check on them, and delivers tailored recommendations to optimize performance.

On Formula E race day, telemetry information is captured from DS Virgin Racing’s cars, and online feeds provide headquarters personnel with information to review race performance.

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Measurable/Quantifiable and “Soft” Benefits From This Initiative:

DS Virgin Racing participates in about a dozen races each season. “We learn a great deal from each race, and we’ve already built the foundation for our analytics,” Sylvain Filippi, CTO of DS Virgin Racing, told HPE. The team is scaling its analytics “to continuously learn more about optimizing race cars and the abilities needed to enable the next generation of electric cars. We’ll be soon ingesting and analyzing video from onboard cameras and race feeds.”

The extracted data is stored for future search and analysis, and is part of the team’s efforts to improve race efficiency and run sophisticated simulation programs to analyze and improve results.

(Source: HPE)

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HPE’s approach to the IoT: servers, security, and Vertica

Case studies: Asset performance management

Special report: Seven things to look for in a streaming analytics platform

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