Aetina launched the DeviceEdge AIE-VN34/44 and AIE-VO24/34, palm-sized in-vehicle edge AI systems built on Nvidia Jetson Orin NX and Jetson Orin Nano modules, delivering up to 100 TOPS and 67 TOPS respectively. Both support four GMSL2 camera connections over distances up to 15 meters for surround-view, blind-spot detection, and environmental perception. Housed in a compact fanless 136.3 × 132 × 63-mm enclosure, they've passed MIL-STD-810H shock/vibration testing and carry E-Mark (E24) automotive certification, operating from -25°C to 55°C on 9–36 VDC power. Target use cases include commercial-vehicle monitoring, AMR obstacle avoidance, production-line inspection, and security monitoring. Systems ship with a JetPack 6.2 board support package, with JetPack 7.2 support planned.
Questions this post answers
What Nvidia Jetson modules power Aetina's new in-vehicle edge AI systems and how much AI performance do they offer?
Aetina's AIE-VN34/44 systems use Jetson Orin NX modules with 8GB or 16GB memory delivering up to 100 TOPS, while the AIE-VO24/34 platforms use Jetson Orin Nano modules with Super Mode and 4GB or 8GB memory delivering up to 67 TOPS. Both support four GMSL2 camera connections for multi-camera edge inference in vehicles and robots. Track new edge AI hardware releases like this on daily.dev when evaluating Jetson-based platforms for a project.
How far can GMSL2 camera connections transmit image data in automotive edge AI systems?
GMSL2 connectivity supports long-distance, low-latency image transmission of up to 15 meters from multiple cameras, enabling real-time AI inference for applications such as surround-view monitoring, blind-spot detection, and environmental perception. This reduces cabling constraints and simplifies camera integration in vehicles and industrial equipment. Developers designing multi-camera vehicle systems can follow GMSL2 hardware developments on daily.dev.