A fuzzy model for evaluating metal detection equipment at airport security screening checkpoints

Every passenger who travels by air is exposed to security screening. As part of this procedure, the passenger typically is screened by a walk-through metal detector. Such a device should effectively detect prohibited metal items while simultaneously ensuring adequate throughput at the security screening checkpoint. Therefore, it is necessary to evaluate both these factors when selecting an appropriate walk-through metal detector and its parameters. However, while it is easy to measure passenger throughput, it is much more difficult to determine the effectiveness of a detector, which is a subjective concept. This paper presents a quantitative method for evaluating the effectiveness of walk-through metal detectors. Since the evaluation is subjective and based on incomplete and imprecise input information, a fuzzy inference method is used, where the input values are expressed as linguistic variables. The research presented in this paper involved field measurements of the sensitivity of walk-through metal detectors and a survey of experts in order to correctly determine the detector sensitivity values. The model for evaluating walkthrough metal detectors is implemented in FUGAS (Fuzzy Gate Assessment System), which was tested at the Katowice-Pyrzowice Airport in Poland. The experimental results demonstrate that a fuzzy inference system can be very effective at assisting airport managers in selecting and configuring the equipment used at airport security screening checkpoints. Corresponding author: Jacek Skorupski ([email protected]) Preprint submitted to Elsevier November 16, 2016