What processor and GPU does the AIE900A-AO use? + The AIE900A-AO is powered by the NVIDIA® Jetson AGX Orin™ platform, integrating an Arm® Cortex®-A78AE v8.2 64-bit CPU and a 1792-core NVIDIA Ampere™ GPU with 56 Tensor Cores, delivering up to 200 TOPS of AI performance for high-end edge AI and autonomous machine applications. It comes with 32GB LPDDR5 memory and 64GB eMMC onboard. For additional storage, there is one M.2 Key M 2280 SSD socket with PCIe x4 NVMe interface and one Micro SD slot.
What I/O and connectivity features does the system provide? + The system offers eight PoE ports (60W), two 2.5 GbE LAN ports, one GbE LAN, lockable HDMI 2.1, six USB ports, two DB9 for RS-232/422/485/CAN, 8-channel DI/DO, and five SMA-type antenna openings. It also supports M.2 Key E 2230 for Wi-Fi 6E, M.2 Key B 3052/3042 for 5G/LTE, a Nano SIM slot, and a reserved MIPI CSI-2 interface compatible with GMSL, FPD-LINK, and V-by-One cameras.
What operating systems and SDK support are available? + The AIE900A-AO comes with Linux Ubuntu 20.04 and supports NVIDIA JetPack 5.1.1 SDK, enabling cross-industry AI development, AI-assisted operations, and autonomous machine applications.
Why choose the AIE900A-AO for AI-powered autonomous machines? + The AIE900A-AO combines high-performance NVIDIA Jetson AGX Orin™ CPU/GPU, eight PoE ports, MIPI CSI-2 camera compatibility, 5G/Wi-Fi 6E connectivity, and robust industrial-grade design. This enables real-time AI inference, 3D LiDAR processing, and autonomous machine navigation while reducing deployment complexity and ensuring reliability in harsh industrial environments.
What industrial and environmental specifications does the system meet? + It features a rugged design with an operating temperature range from -25°C to +60°C, vibration endurance up to 3 Grms, E-Mark compliance, 9 to 36VDC with ignition power control, and optional OTA deployment support through Allxon device management.
What applications is the AIE900A-AO designed for? + It is designed for AI-powered robotics, autonomous mobile robots (AMRs), drones, industrial AIoT, machine vision, deep learning, autonomous machines, and other edge AI applications requiring high-throughput AI processing and vision navigation.