To simulate various driving and tra­ffic situations under varied environmental conditions faced by unit under test (UUT- Transmission), data must be recorded and distinct driving conditions and tra­ffic situations need to be extracted using a machine learning approach.

This information is being gathered by our customer in order to assess the transmission’s durability on road for multiple R&D Fleet Vehicles. Customer wants to extract the road duty cycle from the log data in order to reproduce severe test conditions in the lab. These data loggers have limited physical storage, data must be extracted and stored into a central server in a timely way. As manually viewing and processing high volume data is extremely diffi­cult, a technique for automatic data ‑Filtering and processing is necessary.

A distributed and parallel computing platform is needed, where data from several cars may be imported in parallel and processed in a distributed way using predefined analytics

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