Author
Listed:
- PalaȘcă Andreea
(National University of Science Technology POLITEHNICA Bucharest, Bucharest, Romania)
- Stăncel Ion
(National University of Science Technology POLITEHNICA Bucharest, Bucharest, Romania)
- SEMENESCU Augustin
(National University of Science and Technology Politehnica Bucharest, Bucharest, Romania Academy of Romanian Scientists, 3 Ilfov St., 050044, Bucharest, Romania)
Abstract
The rapid development of global aviation traffic requires the development of more sophisticated management and marketing strategies to enhance airport operations and improve passenger services. In modern airport management systems, real time data from security cameras, check-in counters and handling agents are extracted to establish a configurable framework that enhances the efficiency of smart airports in both commercial and operational sectors. In response to the increasing demand for seamless travel experiences, modern airports are testing and adopting automation systems, predictive analytics, and customizable services to address passenger requirements. The proposed MATLAB developed system provides real-time personalized recommendations for transit passengers, heightens airport marketing strategies and resource distribution in order to satisfy the passenger’s needs. The system can employ predictive algorithms to determine variations in demand based on historical passenger data. This will enhance non-aeronautical sources of revenue and improve the utilization of limited commercial area. Research results indicate that AI driven recommendation systems may alleviate traffic congestion, facilitate employee management, and enhance passenger satisfaction. Future project may employ IoT sensors and big data analytics to implement real time adjustments to passenger flow systems, hence enhancing travel efficiency and fluidity. The paper demonstrates the significance of customer experience marketing in transforming airports into commercial and service centers that respond to various traveler needs. The suggested approach facilitates real time adjustments to passenger flow, resulting in a more efficient and tailored travel experience. This research demonstrates that AI driven recommendation systems may be utilized in airport management, marking a progression in the digital transformation of aviation management systems. The suggested program offers versatile and scalable architecture suitable for integration into modern smart airports. This will enhance their efficiency and increase passenger satisfaction, and revenue.
Suggested Citation
PalaȘcă Andreea & Stăncel Ion & SEMENESCU Augustin, 2025.
"Personalized Passenger Experience in Airports: A Data-Driven Approach,"
Proceedings of the International Conference on Business Excellence, Sciendo, vol. 19(1), pages 2724-2739.
Handle:
RePEc:vrs:poicbe:v:19:y:2025:i:1:p:2724-2739:n:1014
DOI: 10.2478/picbe-2025-0210
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