Validation and Visualization of Vehicle Data

Validation and Visualization of Vehicle Data




To convert massive data streams into actionable insights for refining intelligent systems, cameras, and AI models during live test scenarios.


The team’s efforts culminated in a solution which embodied efficiency, scalability, and versatility.

DEVELOPING THE STRATEGY adapted its strategy in order to develop a system capable of of instantaneous logging, analysis and triggering of real-time alarms for test drivers. The solution was also required to illuminate the car’s intelligent system’s decisions and detections dynamically and in real-time.

​Challenge #1

Managing complex sensor data decoding from various automotive buses like CAN, LIN, FlexRay, and handling communication protocols such as SOME/IP, ensuring synchronization across diverse data streams.

Challenge #2

Addressing CMake and C++ issues, and establishing a seamless Continuous Integration/Continuous Deployment (CI/CD) pipeline via Jenkins to accelerate the development lifecycle

Challenge #3

Decoding intricate network protocols like SOME/IP and tackling the complexities associated with segmented messages.

Challenge #4

Addressing the learning curve associated with complex tech stacks owing to multiple factors.