The number of control units, high-tech features, and functionalities used in today’s automobiles have increased tremendously. With such rise in structure complexity and product variety, it becomes difficult for traditional diagnosis techniques to meet the requirements of fault detection and maintenance.
At Renault, we build an AI-powered car diagnostic system operating on cloud in order to improve the diagnosis and maintenance level as well as root cause analysis efficiency.
A neural network algorithm is introduced and key aspects about model building, validation and production using Tensorflow and GCP services are discussed.
Key Takeaways
- Neural Networks
- Tensorflow
- GCP
- ML production
- TensorFlow Extended
- Pipeline Orchestration
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