AI entry made easy: Kontron delivers AI functionality with the KBox A-203-AI-GC
www.automation-mag.com
23 {{ “2021-04-23T00:00:00+00:00” | date “MMM” }} ’21
Written on {{ “2021-04-23T00:00:00+00:00” | date “longDate” }} Modified on {{ “2021-04-23T00:00:00+00:00” | date “longDate” }}
Kontron News
The Intel Atom®-based Box-PC is now available with an integrated Google Coral Edge TPU for AI image recognition.
Kontron, a leading global provider of IoT/Embedded Computing Technology (ECT), will soon also make its AI-platform available as a KBox PC based on an Intel Atom® x7-E3950 processor.
The KBox is ready-to-use and can be integrated directly into existing X86 landscapes to quickly and efficiently implement own application scenarios around Machine Learning and Artificial Intelligence at the Intelligent Edge. This includes, for example, image and video data processing for visual inspection, quality assurance, predictive maintenance, sorting or object recognition, as a stand-alone device or gateway.
With the integrated Google Coral Edge TPU (Tensor Processing Acceleration Unit) with up to 4 TOPS (trillion operations per second), the speed increases significantly compared to applications with simple USB cameras without TPU. In addition, the TPU supports small and low power applications and requires only one watt for two TOPS.
Unlike the Kontron AI-platform based on the NXP i.MX8M, which is available as a board product, the KBox A-203-AI-GC can be placed directly into the control cabinet or attached to a machine without further preparation. The gateway solution is based on the proven KBox A-203 system, which is used in practice for collecting, processing and distributing sensor data.
It networks different end devices and ensures smooth and secure transmission to a higher-level server infrastructure. With the AI-accelerator, visual information can now also be processed. Two front USB 3.0 ports, connections for displays, two GB Ethernet and an industrial 24 VDC power input are available as interfaces. In addition, there are serial interfaces and a fieldbus option.
In the Deep Learning environment, the close conceptual connection of hardware and software is particularly important in order to optimally solve computationally intensive tasks. The AI-platform runs on Debian Linux, is compatible with TensorFlow Lite and already equipped with application examples.
Users can thus benefit from the wide range of applications offered by Google-AI right from the start. On this basis, own software solutions can be developed quickly and intuitively with a short time-to-market, based on pre-trained models for the respective use case.
