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AI EventCAM® 2D
AI EventCAM® 2D

AI EventCAM® 2D

XMR-AR950

AI EventCAM 2D is an AI-powered video event trigger camera, which is an upgraded version of EventCAM 2D. Apart from all the original functions of EventCAM 2D, it is also equipped with AI and DSP engines to enhance the video understanding capability at the edge. A   lightweight video processing AI network model and a real-time operating platform are embedded in the system to implement fast and accurate recognition of people's presence, action recognition, trajectory classification, anomaly detection, etc. AI EventCAM 2D also offers ultra-high 4K resolution and 240FPS frame rate. It was   developed on the heterogeneous chip architecture platform, and the self- developed video understanding AI models were highly optimized. It incorporates a low-latency video encoding IP and ISP module to provide high-quality images and videos.

Product specifications

Product Advantages
  • Zero-threshold operation

No software is needed to be installed on the PC. Industrial applications can be implemented without code basics.

  • Powerful AI processing capability

It can efficiently process videos and images for frame rates of over 60FPS.

  • Beyond basic functions

Supports event recording, state monitoring, log recording, cluster management, and more.

  • Wide range of applications

The application can cover most industrial scenarios.

  • Strong adaptability

Adaptable to most of the robots of the mainstream brands and various types of industrial equipment.

  • Openness and ease of use

Various communication interfaces can meet various data exchange requirements, enabling efficient data exchange.

  • Accurate analysis

Embedded with multiple pre-trained 2D video understanding models trained on extensive datasets.

  • Rich software

Video Analysis Platform (SVAP), Artificial Intelligence Integrate Platform (SAIP), Equipment and Data Center (SEDC).

  • Flexible deployment

Various installation methods are supported for complex installation environments.

  • Technological innovation

Terminal video understanding algorithms, model compression, and chip architecture coupling.

Applicable scenarios

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