Use of artificial intelligence in the passenger list of the Brazilian international private air system

Abstract

Given the uninterrupted technological advances of recent years, the paradigm of artificial intelligence (AI) has progressed and is currently capable of proposing solutions to everyday challenges. The primary input used by applications based on Artificial Intelligence is information, which is generated constantly and from different sources, raising questions related to collection, storage, representation, recovery, and use. The Federal Police, established by law as a permanent body, organized and maintained by the Union, and structured in a career, among other responsibilities, is intended to prevent and repress illicit trafficking in narcotics and similar drugs and to exercise the functions of maritime, airport, and borders. One way to exercise this prevention at Brazilian airports is by analyzing the pre-list of passengers on commercial airline flights in search of traffickers or “mules”. It is also worth mentioning the complexity of the possible categorical combinations that characterize him as a potential suspected trafficker of illicit drugs. It is known that traffickers are altering this profile to deceive or confuse police investigations. In this way, there is a need to optimize and improve police investigations in the searches of these profiles related to the crime above. Therefore, this research aimed to investigate the possibility of using a neural network to search for profiles and operating modes of the main suspects of international drug trafficking in Brazilian international airports. This research reports difficulties obtaining a reliable, robust database capable of training and testing an AI effectively for passenger list analysis at Brazilian international airports.