End-2-End diagnostics

Industry: Automotive

Use case

Large scale roll out and increased usage of connected vehicles requires deep insights in the functions and communication with the Cloud backend. The goal is to properly inform the driver or service center agent about possible errors to be able to act. The solution E2E diagnostics gathers, processes and interpretes information from car online interface calls. It also makes this information understandable for humans like call center agents.

Challenges

The solution will process vast amount of data as the fleet of connected cars is rapidly growing. The key to success were 2 points: ability to connect new data sources very quickly, find an appropriate cloud-based data infrastructure and implement real-time processing application at scale, provide accurate and easily understandable visualisation in the UI and react upon not registered and thus at that moment not known errors.

Solution

The system „End-2-End diagnostics“ (E2E-D) allows the categorization of all mobile service calls and their results through saving, processing, interpreting, visualizing and making them searchable. The solution is based on Java/Spring while using highly scalable, real-time capable Data Management technologies like Cassandra and MongoDB.

Key facts

Highly scalable data ingestion and data processing capabilities Flexible integration of new data sources Combination of deterministic rules and stochastic approach with ML