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Connected Race Car Dashboard

 

McCoy and Partners collaborated with University Racing Eindhoven (URE) to create a dashboard that displays real-time and analytical sensor data on racing cars.

This dashboard is used during races and testing, giving users the ability to see the most important metrics: the limits of the car, the driver's performance, and data about the track. To create the app, the developers used a design thinking approach. With user-centered design workshops, they uncovered the needs of the race-performance engineer and test engineers. In architecture workshops, they discovered optimal ways to send the data from the car to the cloud. With data modeling workshops, they created the design for the data models and calculations.

Today, sensor data is collected in a Raspberry Pi and sent to McCoy’s SAP HANA platform on Amazon Web Services. Two tables are filled with information from the car: sensor data and messages. The dashboard is built as a web app in SAPUI5 using SAP Web IDE, and runs on the SAP HANA platform. The development team shared a Github repository to collaborate on the app. The app consumes data via OData services, and also allows for the creation of metadata about the race and test.

racecar driver

Key Technical Capabilities

56 

sensors and two modes of operation: live view and historic analytical view

10 

updates  can be received per second, with an overview page that has the most important measures in tiles, plus detailed pages for the progression of metrics during the race

4  GB

of data can be processed in 20 minutes

 

Architectural Diagram/Data Flow Chart

mccoy dashboard chart

Technologies Used

  • SAP Cloud Platform
  • SYC Parallel Processing Index
  • SYC Secure Encrypted Index
  • SYC Search Algorithms
  • Apache POI
  • C++
  • Java

Screenshots

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