ASUS IoT Leverages NVIDIA for Edge Ready Deep Learning

By Chad Cox

Production Editor

Embedded Computing Design

July 18, 2023

News

Image Credit: ASUS IoT

Taipei, Taiwan. ASUS IoT, released its NVIDIA Jetson Orin series powered ultra-compact PE1100N AI inferencing platform. An Arm processer is integrated with the NVIDIA GPU providing flexibility at the edge in applications such as smart city, transportation, traffic analysis, people-tracking, counting, and surveillance. The PE1100N leverages up to 100-trillion operations per second (TOPS) running on low-power (10-25 W) while supporting deep learning and computer-vision.

Asus designed the PE1100N edge ready with an operating temperature range from -20° to 50°C. The solution supports the NVIDIA Isaac Robot Operating System (ROS) SDK for ROS 2 projects. According to ASUS the, “PE1100N provides up to 5X the performance of previous-generation devices. It also realizes up to 18X-better frames-per-watt efficiency than traditional x86-based platforms.”

PE1100N Features:

  • LAN
  • DIO
  • COM
  • USB 3.2
  • Type-A
  • CAN bus
  • Micro-USB debug port
  • Optional WiFi/Bluetooth module
  • M.2 B key is 4G/5G cellular module ready (dual SIM slots)

Supporting GPS delivers accurate data storage and tracking for smart manufacturing solutions including automated guided vehicle (AGVs), autonomous mobile robots (AMRs), AI-powered automated optical inspection (AOI) and robotics applications

For more information, visit iot.asus.com.

Chad Cox is the Production Editor at Embedded Computing Design. His responsibilities are centered around content creation, writing and editing, and article research and development. Chad covers industry news and events and is known to interact with various industrial leaders via on-premise visits and online interviews. He is responsible for the digital footprint and dissemination of news via social media posts, advertising creation and the production of newsletters including the Embedded Computing Design’s Daily.

He is well versed in many facets of industrial computing including Edge AI, IoT, Processing, Security, Open Source, and more.

Chad graduated from the University of Cincinnati with a B.A. in Cultural and Analytical Literature and holds a master’s in education.

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