Systematic mapping review of facial recognition applications in airports

Today's intensified travel flows and the issues associated with them force airports to implement more advanced identity and security systems. One of the profitable artificial intelligence technologies that can be utilized in this regard is facial recognition. This research aims to find the articles that are most related to the topic of face recognition technology utilized in airports by use of a systematic mapping review. The methodology utilized in this article comprises three procedures; defining research questions, research process, and filtering process. Finally, these papers were thoroughly evaluated, analyzed, and classified in order to address eight Analytical and statistical questions. This study proposes a two-level taxonomy of the literature for the application of facial recognition in airports. The first level classification is structured into three primary categories; Identity, security, and security-identity. Furthermore, there are four subcategories for facial recognition application in airports; security cameras, check-in, border control, and airports’ staff access control. Identity is the main category with the most papers and security cameras rank first in the ranking of subcategories. Furthermore, different algorithms and systems that had been utilized by scholars to enhance the efficiency of airports facial recognition systems are mentioned, as well as benefits outcomes and limitation of the proposed algorithm or system. The results also show that researchers mainly focus on proposing a new method for increasing the efficiency of face recognition technology in airports, indicating that there is more room for qualitative studies that focus on other aspects of airport face recognition.