A System for Assessing the Level of Training of the Airport Security Control Operator in Eliminating Dangerous Items from Passengers’ Luggage

Abstract

Ensuring safe transportation of people is a critical responsibility within the air transport industry. One of the primary measures to guarantee safe travel involves preventing the carriage of dangerous items onto aircraft. This is why the aviation sector invests in sophisticated security systems. The airport security control operator (SCO) is a pivotal component of these systems. The operator’s level of training and analytical skills significantly influences their ability to detect items that may jeopardize flight safety. The article discusses a novel system designed to evaluate the training level of security control operators in identifying dangerous items in passenger luggage using X-ray image analysis. This system employs a two-level fuzzy logic model to assess the operator’s proficiency in recognizing four categories of prohibited items. The individual ratings are then combined to generate an overall assessment of the operator’s training level. Extensive testing was conducted by the authors to ensure the system’s consistency and accuracy. The authors’ approach seeks to standardize and objectify the assessment of SCO training, as current systems often exhibit a high level of subjectivity in this regard. Ultimately, this initiative aims to enhance the safety and efficiency of air operations.