This video looks at an industrial edge-vision camera built by YUAN and thermally enabled by Frore Systems, where cooling is treated as part of the compute stack rather than an afterthought. The enclosure integrates an AirJet PAK 5C-G2 to keep an NVIDIA Jetson Orin NX in “Super Mode” running at sustained power, plus a smaller 1C pack dedicated to the FPGA and local SSD so the whole pipeline stays stable under continuous load. https://www.froresystems.com/products/airjet-r-pak
Instead of a fan or a large passive heat sink, AirJet uses solid-state active air cooling with vibration-free airflow, which matters for imaging modules where micro-vibration can soften detail and hurt downstream inference. Frore quotes up to 45 W of net heat dissipation for the 5C-G2 in a compact 100 mm × 65 mm × 10 mm module, while the AirJet Mini G2 building block is rated around 7.5 W per chip, so designers can scale cooling like they scale throughput.
On the AI side, the demo focuses on real-time vision workloads: object detection, categorization, and a vision-language step that turns the live scene into a short text description. That “image-to-text” output is a practical interface for industrial automation, safety, and inspection because it can feed logs, alerts, and downstream rule engines without streaming video offsite, which is exactly the kind of sustained edge workload shown on the CES Las Vegas 2026 floor.
The underlying point is that fanless edge cameras often throttle or grow into heavy metal blocks when you try to hold peak throughput for long runs. By cooling the Jetson module and the surrounding acceleration and storage components separately, and keeping the system dust-resilient and water-resistant, the design aims for steady frame timing and consistent AI latency in a compact industrial camera.
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