How to unlock and monetize data for real-time use cases in series production cars
Learn about new revenue-generating, production-scale use cases and how to efficiently train and update the underpinning, sensor-fed AI models to achieve the highest possible accuracies. Data are driving the future of the global automotive industry, and new revenue streams and products are being made possible by AI models.
These models have one thing in common: they all thrive on the ingestion of sensor data from cars. However, merely increasing sensor resolution and frame-rates is not the way forward as this will create significant challenges. These include in-car CPU&RAM, application latency, in-car energy consumption, data transmission costs, and improving AI-models to achieve near 100% accuracy.
In this webinar, Teraki experts discuss how the company enables use cases for connected and autonomous vehicles, including:
- driver monitoring,
- event and object detection (e.g. crash, lane departure, and traffic lights),
- predictive maintenance,
- range optimization of EVs and PHEVs,
- sensor fusion,
- and SLAM.