Edge AI Cameras That Run Vision Models On-Device

Edge AI Cameras AI Vision Solution

An edge AI camera runs the vision model on the device instead of sending video to a server or the cloud. That means decisions in milliseconds, far less network traffic, and footage that stays on site. It is the setup most production lines, warehouses, and remote sites end up needing for edge computer vision, where a delayed or dropped result costs real money.

Roboflow AI1 (opens in a new tab) is built for that job: an 8 MP industrial camera (3840 x 2160 at 30 fps) with integrated lighting and an NVIDIA Jetson Orin NX inside an IP54 housing. Models run on the camera with under 100 ms edge round-trip, and every result is stored locally on 256 GB of storage before it syncs to the cloud. When a decision needs a vision-language model, AI1 hands just that step to the cloud.

• Featured: Roboflow AI1 (AI1-8MP-4MM): 8 MP sensor, 4 mm lens with electronic focus, NVIDIA Jetson Orin NX 8 GB, IP54 housing
• Attributes: On-device inference, under 100 ms edge round-trip, local-first event storage, over-the-air model and security updates
• Integration: Results to PLCs over OPC UA, MQTT, or Modbus TCP, a web HMI on the local network, and synced events to MES, Power BI, or Slack

Train a model in Roboflow on images from your own site, then deploy it to every AI1 from Roboflow Deployment Manager. Deployment Manager provisions devices, pushes new models over the air, and shows utilization across every site, so managing ten edge cameras is as simple as managing one.

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Already have cameras on site? Roboflow Inference also runs models at the edge on GigE Vision and RTSP streams from the cameras you already have, so you can bring edge AI to existing cameras and add AI1 where you need a new one.