Video Monitoring Algorithm Selection Under Compute Node Load Limits
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Solution Overview
Problem
The manual selection of intelligent analysis algorithms for video monitoring equipment is inefficient and requires significant manual work, often leading to improper selections due to the lack of professional knowledge among construction personnel, affecting the analysis effectiveness.
Innovation Solution
An automated method and system for selecting intelligent analysis algorithms based on image data analysis, determining scene contents, and matching algorithms to compute node load capacities, ensuring the total algorithm load does not exceed the compute node's capacity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual selection of intelligent analysis algorithms is performed, then construction personnel can configure monitoring equipment, but the selection efficiency is low and manual workload is high
Solution Approach 1:
The system performs automatic algorithm selection and configuration based on scene analysis, eliminating the need for manual intervention. The compute node automatically analyzes image data, determines scene contents, selects appropriate algorithms, and configures monitoring equipment without human operation, thereby dramatically improving selection efficiency and reducing manual workload
Solution Approach 2:
The system pre-establishes a library of intelligent analysis algorithms and their corresponding scene requirements. Before actual monitoring, the system analyzes scene image data and pre-selects appropriate algorithms from the library, so that when monitoring begins, the configuration is already optimized and ready to use, eliminating time-consuming manual configuration during deployment
2Reliability
If multiple intelligent analysis algorithms are selected to cover all scene contents, then analysis comprehensiveness is improved, but compute node overload occurs
Solution Approach 1:
The system analyzes the specific characteristics of each scene content and selects algorithms with appropriate analysis depths and computational requirements tailored to each local requirement. Not all scene contents require the same level of analysis - the system applies different algorithmic intensities to different regions or types of content, ensuring comprehensive coverage while optimizing resource utilization and preventing compute node overload
Solution Approach 2:
The system dynamically adjusts algorithm parameters such as analysis resolution, processing frequency, and computational complexity based on scene characteristics and compute node status. By changing these parameters, the system maintains comprehensive analysis coverage while adapting the computational load to match available resources, preventing overload while ensuring reliability
3Ease of operation
If construction personnel with insufficient professional knowledge select algorithms, then equipment deployment is simplified, but improper algorithm selection occurs affecting analysis effectiveness
Solution Approach 1:
The system introduces an automatic scene analysis module as an intermediary between the construction personnel and the algorithm selection process. This intermediary automatically analyzes scene image data, identifies scene contents, and selects appropriate algorithms based on pre-established criteria, eliminating the need for personnel to have professional knowledge while ensuring accurate algorithm selection and maintaining high deployment simplicity
Data Source
AI summary
A method, an apparatus, a system, and an electronic device for selecting an intelligent analysis algorithm. The method includes: acquiring image data of a monitoring scene (S101); analyzing the image data to obtain scene contents contained in the image data (S102); determining an intelligent analysis algorithm corresponding to each of the scene contents (S103); and selecting a target intelligent analysis algorithm(s) from intelligent analysis algorithms corresponding to the scene contents according to a load capacity of a compute node used for loading the intelligent analysis algorithms, wherein a total algorithm load of the target intelligent analysis algorithm(s) is not greater than the load capacity of the compute node (S104). The method for selecting an intelligent analysis algorithm realizes an automatic selection of the intelligent analysis algorithm, which can reduce the manual workload, improve the selection efficiency of the intelligent analysis algorithm, reduce overload of the compute node, reduce abnormal analysis results caused by the overload of the compute node, and reduce an improper selection of the intelligent analysis algorithm due to the low degree of professionalism of the construction personnel, which affects the analysis effect.