Advantech Launches AIR Edge AI Inference Systems for AI and Vision Analytics Applications

November 12, 2020 Tiera Oliver

Advantech launched their comprehensive AIR series of AI inference systems, to address various AI applications including retail facial recognition, AOI/vision inspection, robotic, intelligent transportation, and more. The offerings include different featured designs to fit different AI applications. Advantech also provides Edge AI Suite, a software toolkit with a graphic user interface (GUI) and pre-trained AI models to help customers enable AI inference on edge devices.

AIR series includes AIR-100, AIR-101 and AIR-200 which integrates Intel Movidius Myriad X VPU, and AIR-300 which supports a PCIe x16 high power graphic card. Powered by Intel Atom x7-E3950 CPU and one Intel Movidius Myriad X VPU, AIR-100 supports multi-4K display and is suitable for interactive kiosks and other retail applications with facial recognition functions.

AIR-101 supports DIN-Rail design and 12V~28V wide-range power input with Intel Atom E3940 Quad Core processors and two Intel Movidius Myriad X VPUs and is ideal for AGV and factory automation applications. For higher computing power needs, AIR-200 is an Intel Core i5 platform with two Intel Movidius Myriad X VPUs and supports up to 1080p video encoding, decoding, and multi-channel processing suitable for traffic monitoring, license plate recognition, and vehicle classification applications. The AIR-300 supports Intel Xeon E3/ 7th & 6th generation Core i series processor and a PCIe x16 high performance graphic card to enable ideal inference and on-premises training for robotics and optical inspection applications.

The AIR series comes with the Edge AI Suite software toolkit that integrates Intel OpenVINO toolkit R3.1 to enable accelerated deep learning inference on edge devices and real-time monitoring of device status on the GUI dashboard. The latest Advantech Edge AI Suite v1.2 includes an optimized pre-trained Yolov3 object detection model popular in surveillance applications which delivers 2.8x better performance on VPU than running with OpenVINO only. Per the company, customers can use Edge AI Suite v1.2 to execute the Yolov3 model with VPU+GPU heterogeneous acceleration to get 5x better AI inference performance than using a single device.

For more information,visit:

About the Author

Tiera Oliver, edtorial intern for Embedded Computing Design, is responsible for web content edits as well as newsletter updates. She also assists in news content as far as constructing and editing stories. Before interning for ECD, Tiera had recently graduated from Northern Arizona University where she received her B.A. in journalism and political science and worked as a news reporter for the university's student led newspaper, The Lumberjack.

Follow on Twitter Follow on Linkedin Visit Website More Content by Tiera Oliver
Previous Article
Approov Partnership with BMW Group Provides Car Share Experience
Approov Partnership with BMW Group Provides Car Share Experience

Car theft risks and business-critical security issues are resolved with Approov API authentication software...

Next Article
Numenta Demonstrates 50x Speed Improvements on Deep Learning Networks Using Brain-Derived Algorithms
Numenta Demonstrates 50x Speed Improvements on Deep Learning Networks Using Brain-Derived Algorithms

Numenta announced it has achieved ideal performance improvements on inference tasks in deep learning networ...