Research and Design of an Intelligent Judgment Mode for Urban Rail Transit Security Inspection System
To improve the efficiency and accuracy of urban rail-transit security inspection systems,this paper designs a novel pattern-recognition mode to effectively combine artificial intelligence(AI)image recognition technology with manual centralized pattern recognition.First,based on the current liquid inspection,a liquid detection algorithm is introduced to avoid the open inspection of safe liquids.Second,security products are classified according to their risk levels.Finally,AI confidence judgment,manual sampling,or necessary inspection charts are combined to determine the pattern recognition mode,which can flexibly adjust the depth of the AI intervention according to the accuracy of the AI image recognition and the requirements for pattern recognition at different stages.With the continuous improvement in the accuracy of AI image recognition,it gradually changes from an AI-assisted manual-based pattern recognition mode to an AI-based manual-assisted pattern recognition mode and finally achieves a fully intelligent pattern recognition mode.A case analysis reveals that the judgment graph model can further achieve rapid security inspection,cost reduction,and efficiency increase without reducing the safety inspection level of urban rail transit stations.
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