AI is playing an increasingly significant role in the video surveillance industry. AI-based video surveillance systems help customers reduce investigation time, set proactive alerts (e.g., identifying a person with a firearm), and overall save a substantial amount of time. With many vendors offering AI-based security solutions, it is crucial to understand the trade-offs between different architectures and how to select a solution that is:
In this blog, we will explore each of these aspects and compare different architectures and some leading vendors.
In AI video surveillance, the ultimate performance of a camera is measured by the compute power (measured in FLOPS) per camera that the architecture offers. Since streaming video data 24/7 to the cloud is not feasible, all cloud-based solutions store and process data on the camera and push a minimal amount of data to the cloud to preserve bandwidth. This means the quality of AI performance is capped by the amount of compute power per camera that the architecture can offer. There are two broad categories of architecture:
For AI video surveillance systems, the amount of compute (i.e., FLOPS) per camera is the most appropriate measurement of "intelligence per camera." More compute implies the ability to run larger neural networks and achieve higher accuracy results. Different AI NVRs can leverage different GPU accelerators. The CP-E-1 uses A2000 GPUs and is able to achieve more than 3.5 Tera FLOPS per camera. When compared to proprietary cameras such as Verkada or Rhombus Systems, which use chips from Ambarella (such as the CV25S), AI NVRs like Coram Point provide significantly more compute per camera. This means an end customer is able to get a much more intelligent camera system, and architecturally, they will be able to leverage future AI features without having to upgrade the hardware.
In conclusion, understanding the strengths and limitations of different AI video surveillance architectures is essential for making an informed decision. AI NVRs offer significant advantages in terms of performance, future-proofing, and cost-efficiency, making them a compelling choice for modern video surveillance needs.
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