eIQ® Auto ML Software Development Environment

Machine learning (ML) applications are expanding rapidly inside vehicles, leveraging sensor and vehicle-generated data to continually improve performance and offer new insights and capabilities. However, ML algorithms vary greatly in their composition and runtime requirements, making their deployment on embedded processors complex and time-consuming.

The NXP eIQ Auto ML software development environment offers a consistent and flexible workflow that is designed to provide high-performance and rapid deployment of ML algorithms across the range of NXP S32 automotive processors for diverse applications such as predictive maintenance, enhanced battery management, ADAS, touch sensing and more.

eIQ Auto ML Typical Applications

eIQ® Auto ML Software Development Environment flexibility allows for deployment of ML Algorithms of all types from very low to very high compute resource need. This unified ML Software Development Environment, by selecting the appropriate MCU/MPU, addresses a very wide range of applications including:

  • ADAS
  • Object Detection, Image Classification and Segmentation
  • Driver Monitoring/Identification
  • Natural Language Processing
  • Battery State of X (Charge, Health, etc.)
  • Anomaly Detection
  • Touch sensing
  • Key Word Spotting