Video Camera Controller Dynamic Analytics Execution
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Solution Overview
Problem
Video cameras in surveillance systems have limited processing resources, making it challenging to dynamically execute video analytic algorithms effectively, as these resources are often utilized for basic operations and vary over time.
Innovation Solution
A video camera system with a controller that determines current processing resource utilization and prioritizes the execution of video analytics algorithms, allowing for the selection and execution of either heavier or lighter weight versions based on available resources to identify events in the video stream and send alerts accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If video analytics algorithms are executed on the video camera, then video analytics capability is improved, but processing resource availability for basic operations deteriorates
Solution Approach 1:
The system dynamically adjusts the execution of video analytics algorithms based on real-time processing resource availability. The controller monitors resource utilization and adaptively selects which algorithms to execute and when, transforming the static resource allocation into a dynamic system that responds to changing operational conditions.
Solution Approach 2:
The system changes operational parameters by adjusting the priority and execution timing of video analytics algorithms based on current resource utilization levels. When resources are abundant, heavier analytics are executed; when resources are constrained, execution is deferred or lighter analytics are performed instead.
2Measurement precision
If heavier weight video analytics algorithms are executed, then event detection accuracy is improved, but processing resource consumption increases
Solution Approach 1:
The system applies different quality levels of video analytics algorithms to different situations based on resource availability and event importance. Heavier weight algorithms with higher accuracy are selectively applied when resources permit or when detecting critical events, while lighter algorithms are used during resource-constrained periods.
Solution Approach 2:
The system performs partial execution of video analytics by selecting specific algorithms based on current needs and resource availability. Rather than continuously executing all analytics algorithms at full capacity, the system applies only the necessary level of analytics processing required at each moment.
3Productivity
If multiple video analytics algorithms are executed simultaneously, then event identification capability is improved, but processing resource utilization increases
Solution Approach 1:
The system segments the execution of video analytics algorithms by dividing them into different priority levels and time slots. Multiple algorithms are executed in a segmented manner rather than all simultaneously, with critical algorithms receiving higher priority execution windows and less critical algorithms executing during lower-resource periods.
Solution Approach 2:
The video camera controller is designed with multi-functionality to handle both basic camera operations and video analytics execution using the same processing resources. The system universally manages diverse workloads by dynamically allocating resources between different functions based on current operational requirements.
Data Source
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AI summary
A video camera includes a camera for capturing a video stream and a controller that is operably coupled to the camera. The controller, which includes processing resources, is configured to determine a current utilization of one or more of the processing resources and to determine which of a plurality of video analytics algorithms should be executed based at least in part on the determined current utilization of the one or more processing resources. The controller is configured to execute two or more of the plurality of video analytics algorithms on the video stream to identify one or more events in the video stream, wherein the controller executes the two or more of the plurality of video analytics algorithms, and sends an alert in response to identifying one or more events in the video stream.