CVG explores the use of AI to predict terminal crowding
03/01/2022
Future Travel Experience / March, 2022
Cincinnati/Northern Kentucky International Airport (CVG), a member of the FTE Innovation Hub, has teamed up with the University of Cincinnati (UC) to explore the use of artificial intelligence (AI) to predict crowding and enhance the passenger experience throughout the airport.
CVG engaged UC College of Engineering and Applied Science aerospace engineering doctoral student Javier Viaña to utilize airport data to create a software programme to help the airport predict when travelers arrive at the airport, broken down into 15-minute increments. By leveraging data collected by another programme previously developed by CVG, Viaña has been able to specifically model queue lines at the security checkpoint.
“The main objective of this work is to improve the passenger experience and inform operational decision-making at the airport,” said Candace McGraw, Chief Executive Officer, CVG. “The modelling done by Javier provides the airport and our business partners reliable data to prepare our operations based on passenger arrival predictions, potentially reducing crowding and wait times along the travel journey from parking and check-in to security screening and concessions.”
CVG engaged UC College of Engineering and Applied Science aerospace engineering doctoral student Javier Viaña (pictured) to utilise airport data to help the airport predict when travelers arrive at the terminal. “What makes this model unique is how UC is using artificial intelligence based on fuzzy logic, a type of computer decision making that allows us to provide a human-like explanation for its predictions,” said Javier Viaña. “We refer to this type of algorithms as explainable and transparent.”
The collaboration is a direct result of a multi-year memorandum of understanding (MOU) between UC and CVG. The MOU provides the University’s research talent and emergent technologies a living-laboratory environment (the airport) that is a mutually beneficial relationship.
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