Use of Machine Learning Algorithms in improving the efficiency of flight check-in in Muscat International Airport

Abstract

Check-in area in airports is the first step before departure. Usually these areas are very crowded by the passengers who are very sensitive about the time before their flight check-in. Thus, delays while check-in process will have an impact on the passengers in which will have a consequences on the airline company. Delays in check-in process can happen due to various kind of reasons such as airline agent absence where the airline agent is not available at the check-in desk when the time of check-in is started. Artificial intelligence and machine learning are a computer science technologies that can help preventing such problems from occurring. In this paper the machine learning algorithms are studied to detect the staff availability in the check-in desk. The staff is detected by a camera using facial recognition algorithm of machine learning and then analysis are made upon the results found. Whenever there is no staff found the system will notify the airline company and send an expected delay time. The implementation of this solution can be built as a smart based system i.e. based on artificial intelligence and machine learning concepts. All solutions suggested can reduce cost and effect on airline companies and passengers rates respectively.