Assessment of the Skeletonization and Motion Monitoring System for the Security Efficiency of the United States Airports
The screening processes at airports, including passengers and baggage, have changed dramatically in the past twenty years. The goal of the X-ray scanning is to enhance airport screening by preventing passengers from carrying weapons and contraband. X-ray is more effective compared to traditional pat-down. The X-ray shoots beams through passengers and their baggage, which provides an inner view to the Transportation Security Administration (TSA) screeners. Issues and concerns of the use of X-ray have also been raised, as some passengers complained about possible health issues due to the body exposure of radioactive waves; other experts pointed out possible human factor errors between X-ray scanning and TSA screeners. Artificial intelligence (AI) has been used in various areas and includes surveillance monitoring. Facial recognition assists employees to identify other individuals based on their facial characteristics; and motion monitoring (skeletonization) assists doctors to track patients’ gestures and provides a precautionary warning. The purpose of this paper was to investigate the problem as to whether security screening devices that incorporate skeletonization and AI have a higher detection rate in detecting absconders and contraband than traditional checkpoints without these technologies. The results of the study suggested that airport security checkpoint screening devices incorporating skeletonization and AI had a different detection rate in detecting absconders and contraband as compared to traditional technologies that do not incorporate skeletonization and AI. However, there were no conclusive results that these checkpoints had a higher detection rate in detecting absconders and contraband as compared to traditional technologies that do not incorporate skeletonization and AI.