ASUS Small Form Factor SBCs Suit Industrial Edge AI Applications

By Rich Nass

Contributing Editor

Embedded Computing Design

May 11, 2023

Blog

ASUS Small Form Factor SBCs Suit Industrial Edge AI Applications

Some new single-board computers (SBCs) from ASUS IoT up the ante in terms of performance for industrial Edge AI applications.

First, the Tinker Board 3 is designed with a 64-bit Arm quad-core Cortex-A55 processor and includes support for both Linux (Yocto and Debian) and Android OSs. Interfaces include PoE, LVDS, COM and CAN bus, plus M.2 E and M.2 B slots to accommodate wireless or 4G/5G expansion modules. As evidence that “embedded” is the target for the board, ASUS is providing at least seven years of availability. Aimed at industrial applications, the 100- by 100-mm board can operate in temperatures ranging from -40℃ to +85℃.

A relative of the Tinker 3 is the Tinker V, which is based on a RISC-V architecture and fits the compact Pico-ITX form factor. The company claims that this is the first SBC based on the relatively new RISC-V open-source architecture. At 64 bits, it provides the performance needed for higher end industrial IoT (IIoT) applications. Linux Debian and Yocto support is included.

Specifically, the Tinker V is equipped with a Renesas RZ/Five MPU, which incorporates the RISC-V AndesCore AX45MP single-core CPU, running at 1.0 GHz. It is also engineered with an array of peripheral connectors aimed at industrial applications, with GPIO, micro-USB, dual gigabit Ethernet, a pair of CAN bus interfaces, and two RS232 COM ports. It also includes 1 Gbyte of built-in RAM and an optional 16-Gbyte eMMC. Operating temperatures range from -20°C to +60°C.

Finally, the PE6000G system is also aimed at Edge AI applications. It supports up to a 450-W graphics card for high-throughput, demanding GPU-computing applications. Powered by a 12th Gen Intel Core processor and paired with the Intel R680E chipset, the PE6000G is ready for the latest PCI Express (PCIe) 5.0 standard, meeting requirements for real-time AI inferencing and deep learning training at the Edge. It supports up to 64 Gbytes of ECC/non-ECC DDR5 4800 SDRAM, four 2.5-in. SSDs, and one each of M.2 M key (NVMe), M.2 B key (5G NR), and M.2 E key (WiFi 6). It also provides all the connectivity that you’d expect for Edge AI applications.

Rich Nass is a regular contributor to Embedded Computing Design. He has appeared on more than 500 episodes of the popular Embedded Executive podcast series, and is a regular contributor to the Embedded Insiders podcast.

Rich has been in the engineering OEM industry for more than 35 years, and is a recognized expert in the areas of embedded computing, Edge AI, industrial computing, the IoT, and cyber-resiliency and safety and security issues. He writes and speaks regularly on these topics and more.

Rich is currently the Liaison to Industry for the Embedded World North America Exhibition and Conference, and has held similar positions with the global Embedded World Conference and Exhibition.

Previously, Rich was the Brand Director for UBM’s award-winning Design News property. Prior to that, he led the content team for UBM Canon’s Medical Devices Group, as well all custom properties and events.  In prior stints, he led the Content Team at EE Times, handling the Embedded and Custom groups and the TechOnline DesignLine network of design engineering web sites.

Nass holds a BSEE degree from the New Jersey Institute of Technology.

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