Video Analytics for Scene-Based Camera-to-Recorder Load Balancing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Large-scale CCTV installations face challenges in optimizing the automated assignment of cameras to recorders, as existing methods lack a basis for ensuring optimal load balancing between cameras and recorders with varying specifications.
Innovation Solution
A method and apparatus for load balancing that utilizes scene analysis to determine load balancing factors, including camera scene importance, storage redundancy, activity level, and object proximity, to dynamically assign cameras to recorders with varying specifications, leveraging artificial intelligence and neural networks for classification and assignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If automated load balancing is implemented without scene analysis basis, then automation is improved, but load balancing optimization deteriorates
Solution Approach 1:
The system performs preliminary scene analysis to generate scene importance values before making camera-to-recorder assignments. This advance preparation of scene importance data enables automated decision-making to be both automated and optimized, resolving the contradiction between automation extent and optimization quality.
Solution Approach 2:
The system uses scene analysis feedback to continuously adjust and optimize camera-to-recorder assignments. By analyzing scene importance values and using them as feedback for load balancing decisions, the system achieves both high automation and optimal resource allocation simultaneously.
2Ease of operation
If cameras are assigned to recorders without scene analysis, then assignment simplicity is improved, but resource allocation efficiency deteriorates
Solution Approach 1:
The system enables recorders to self-select based on their capacity and assigned cameras to self-determine optimal scene coverage. This self-service mechanism maintains operational simplicity while achieving efficient resource allocation through scene importance-based decisions without complex manual intervention.
Solution Approach 2:
The system changes the assignment parameter from simple camera-to-recorder mapping to scene importance-weighted assignment. By incorporating scene importance values as a key parameter, the system maintains ease of operation through automated parameter-driven decisions while significantly improving resource allocation efficiency.
3Ease of operation
If manual camera-to-recorder assignment is used, then assignment control is improved, but automation level deteriorates
Solution Approach 1:
The system introduces scene importance values as an intermediary between manual control requirements and automated assignment execution. This intermediary enables the automated system to operate with the same level of control intelligence that would require manual intervention, achieving both high automation and effective control.
4Speed
If load balancing ignores recorder specifications, then assignment speed is improved, but resource utilization deteriorates
Solution Approach 1:
The system performs preliminary analysis of recorder specifications and camera scene importance values before making assignments. This advance preparation enables the system to make rapid, informed decisions that optimize resource utilization without sacrificing assignment speed, as the complex analysis is completed beforehand.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A method and apparatus for performing a load balancing assignment of a set of cameras having different camera specifications to a set of recorders having different recorder specifications/ The aspects include determining a set of load balancing factors configured to match the cameras in the set of cameras to the recorders in the set of recorders responsive to scene analysis information. The set of load balancing factors include at least a camera scene importance. The aspects include assigning one or more of the cameras in the set to record to one or more of the recorders in the set responsive to the set of load balancing factors and the set of recorder specifications. The aspects include recording, by the one or more of the recorders, video information from a corresponding one of the one or more cameras based on the assigning of one or more of the cameras to record to the one or more of the recorders.