Control’s solution allows the company to update each car’s connectivity automatically.
Technologies Used:
Short description of project/implementation:
Control improved race performance with a streaming architecture and ML models that connected in-car devices and cloud transformations in real-time.
What problem was the nominee organization looking to solve with Data Streaming Technology?
When an in-car device arrived at a new racetrack, its three modems automatically connected to the first available network, not the best available network. This degraded race performance up to 23% compared to optimal conditions. Control engineers made manual adjustments to correct this discrepancy, but doing so required time-intensive calculations at the beginning of and throughout each race. Devices were missed, and decisions were made on historic data rather than the data at hand.
How did they solve the problem?
Positive outcom
Control’s solution allows the company to update each car’s connectivity automatically. This removed a massive operational burden and eliminates the risk that a customer would needlessly suffer up to 23% performance degradation. The data pipeline is now resilient because it replicates and shards the data and the processing. With Quix, Control’s small team stood up, trained, tested, and deployed 82 ML models in just two weeks. Control is now confident that its product performs consistently.
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