Kontron Industrial AI Platform
Simple integration of artificial intelligence
Kontron is now supporting companies with a compact platform for artificial intelligence, machine learning and deep learning.
It integrates all Google TensorFlow Lite applications and enables rapid development of your own AI applications. The Google Coral Edge TPU (Tensor Processing Acceleration Unit) with up to 4 TOPS (trillion operations per second) ensures higher speeds for image and video data processing. Compared to an application with simple USB cameras without TPU with around 6 frames/s, the TPU provides five times the speed of 30 frames/s.
Artificial intelligence at the intelligent edge is becoming increasingly important in industrial automation. The new compact Kontron AI Platform consists of an M.2 module with the Google Coral accelerator chip for the TensorFlow Lite software ecosystem on a 2.5" pITX single board computer from Kontron with an NXP i.MX8M processor. The TPU supports small and low power applications and requires only 1 Watt for 2 TOPS, i.e. 2 W for 4 TOPS.
All current TensorFlow Lite applications and pre-trained models can be downloaded free of charge, enabling fast and uncomplicated development of your own neural networks with AI/ML/DL applications, and thus a significantly reduced time-to-market.
In the context of Industry 4.0 applications, topics such as object recognition and classification as well as quality inspection of objects and predictive maintenance, which are based on AI algorithms, are being used more and more frequently. Artificial intelligence is also playing an increasingly important role in point-of-sale applications in order to place advertising and relevant information in a more targeted manner. The Kontron solution can also be flexibly adapted to the respective application requirements. The platform is suitable for use in harsh environments with extended temperature ranges from -40 to 85 °C and supports Yocto Linux with the latest kernel. The platform will also be available on other Kontron systems from Q1 2021.
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