Advanced Driver Assistance Systems

Store, manage and analyze data for self-driving vehicles. Scale easily as your data grows.
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Simplicity that delivers cost-effective performance

Qumulo enables enterprises to easily capture and store sensor data to build AI models for automation.

Customers like Hyundai MOBIS leverage Qumulo for analysis of hundreds of terabytes of video data from vehicle sensors used for designing and building assisted and autonomous cars. Qumulo’s cluster can ingest the steady stream of machine-generated data without constant management—a huge productivity benefit.

How it Works

Qumulo Hybrid Cloud File Storage for ADAS

Here is an example of a SIL workflow, where software simulates the behavior of an electronic control unit (ECU).

The captured sensor data is transferred to Qumulo, typically over SMB. From there the SIL servers retrieve it, resulting in many parallel read streams. The servers send the data, along with the test cases, out to the simulation software and then send the results back to the file storage system.

Data enrichment is the tags that are added to the video. The footage needs to be labeled and indexed so that developers can query for specific video sequences.

Related resources:


Accelerating Autonomous Vehicle Development with Cloud Data Services and Real-time Data Analytics


Hybrid Storage for ADAS Data, Development, and Simulation


The Unified Data Platform for Machine Learning and High Capacity Storage


Hyundai MOBIS Relies on Qumulo in Developing the Future of the Connected Car

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