AI Camera Implementation Process

Key Points for VNX AI Camera Server Requirements Analysis

• Analysis is limited to objects that can be clearly judged by human visual inspection.
• The minimum analysis interval for the VNX AI camera analysis server is 1 minute. One set of data is output from 1 minute of footage every minute, and data in seconds is discarded after analysis.
• The distance from the camera to the object to be analyzed depends on the resolution of the camera image and the size of the object to be analyzed. Although there are differences depending on the requirements, it is desirable that the target area in the camera image is 60 pixels or more.
• The VNX AI camera server uses RTSP streams. Existing cameras that support RTSP can also be used. GigEVision and GenICam are not supported.
• Determine whether tracking is necessary for analysis.
• Determine whether deep learning model is necessary for analysis.
• Get a rough idea of the number of cameras needed and whether or not a buffer recording function is required. The number of cameras and recording function will determine the required server CPU core count, memory capacity, and storage capacity.

If there are no problems with the analysis results of the sample footage, the overall system configuration will be determined. Determine the external API integration, data storage and display locations.

Our development team will develop modules tailored to your requirements. Once the module development is complete, it will be integrated into the AI camera server.