A passenger risk assessment method based on 5G-IoT

Abstract For the airports worldwide, it is important to establish a "passenger integrity system" based on basic information of passengers and their related credit system. Correspondingly, this paper develops new risk assessment model for passenger graded security check by introducing several technologies obtain passengers’ real-time status as well historical data. We first propose deploy variety 5G-IoT devices monitor in real time, including high-definition cameras, millimeter-wave detectors, etc. then rely machine learning analyze level integrate improved analytic hierarchy process (AHP) with group decision theory, namely GD-AHP. According level, can be classified into known, ordinary dangerous targets. The differentiated handling different targets could significantly save time improve experience.