Alarm Message Processing Using Historical Disposal Feedback
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Solution Overview
Problem
Security protection products generate a large volume of alarm data, leading to time-consuming and labor-intensive manual analysis by security operation personnel, with models providing low accuracy due to complex and dynamic operating environments.
Innovation Solution
An alarm message processing method that matches first alarm data to alarm feature information, retrieves corresponding historical alarm data and disposal information, and uses a target model to generate prompt information for accurate alarm disposal, incorporating feedback mechanisms to optimize the model's performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual analysis of alarm data is performed by security operation personnel, then alarm disposal can be conducted, but the process becomes time-consuming and labor-intensive
Solution Approach 1:
The system performs preliminary actions by pre-processing alarm data, extracting features, and organizing historical alarm information into structured formats before actual disposal is needed. This includes pre-computing alarm feature representations and preparing historical context data, so when an alarm occurs, the analysis can proceed quickly using pre-prepared information.
Solution Approach 2:
The patent introduces an intermediary alarm analysis system that acts as a mediator between raw alarm data and security personnel. This intermediary automatically performs feature extraction, historical alarm matching, and disposal recommendation generation, reducing both the time and manual effort required while maintaining or improving disposal accuracy through systematic analysis.
2Productivity
If models are used for alarm analysis, then processing speed can be improved, but accuracy remains low due to complex and dynamic operating environments
Solution Approach 1:
The system performs preliminary feature extraction and historical alarm matching to create structured input data before feeding it to the model. This pre-processing ensures that the model receives high-quality, context-enriched data including historical patterns and similar alarm cases, improving accuracy without sacrificing the speed benefits of automated model-based analysis.
Solution Approach 2:
The patent implements feedback mechanisms where model predictions are evaluated against actual alarm outcomes and historical disposal results. This feedback is used to continuously refine and retrain the model, enabling it to adapt to complex and dynamic operating environments, thereby improving accuracy while maintaining high processing speed through automated iterative optimization.
3Measurement precision
If historical alarm data is extensively analyzed to improve accuracy, then disposal precision can be enhanced, but system complexity increases
Solution Approach 1:
The system extracts only the most relevant features and characteristics from historical alarm data rather than analyzing entire datasets. It identifies and extracts key alarm patterns, similar case representations, and critical disposal outcomes, discarding redundant information. This extraction approach maintains high accuracy by focusing on essential features while reducing system complexity by eliminating unnecessary data processing burden.
Data Source
AI summary
This application provides an alarm message processing method. The method includes: obtaining first alarm data generated by a security detection module; matching the first alarm data to at least one piece of alarm feature information; obtaining at least one piece of target historical alarm data corresponding to target alarm feature information and alarm disposal information of the at least one piece of target historical alarm data; and generating first prompt information at least based on the first alarm data, the at least one piece of target historical alarm data, and the alarm disposal information of the at least one piece of target historical alarm data, and sending the first prompt information to a target model, and receiving first alarm disposal information for the first alarm data that is returned by the target model.