Enhancing Boarding Efficiency with Facial Recognition in Smart Airport Terminals

The facial recognition boarding system represents a significant innovation in the aviation industry and is frequently regarded as essential for enhancing operational efficiency and security. The facial recognition technology utilized by airlines is continually advancing, offering passengers a quicker and more precise boarding experience. This study investigates the potential impact of implementing a facial recognition boarding system for Taiwanese airlines in promoting smart airport technologies. Additionally, the research employs the Diffusion of Innovations (DOI) theory to assess the acceptance level of airline employees toward the system and its contribution to improving operational quality.

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Publication Details

Published
2025-03-29
DOI
https://doi.org/10.1109/icct-pacific63901.2025.11012833
Citations
1
Primary Topic
Aviation Industry Analysis and Trends
Type
article
Field-Weighted Citation Impact
3.09
Controls
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article

Enhancing Boarding Efficiency with Facial Recognition in Smart Airport Terminals

Szu‐Yu Kuo, Liang-Bi Chen, Chun-Ting You
1 citations
Aviation Industry Analysis and Trends
3.09
article

Enhancing Boarding Efficiency with Facial Recognition in Smart Airport Terminals

Szu‐Yu Kuo, Liang-Bi Chen, Chun-Ting You
article en
1 citations

Abstract

The facial recognition boarding system represents a significant innovation in the aviation industry and is frequently regarded as essential for enhancing operational efficiency and security. The facial recognition technology utilized by airlines is continually advancing, offering passengers a quicker and more precise boarding experience. This study investigates the potential impact of implementing a facial recognition boarding system for Taiwanese airlines in promoting smart airport technologies. Additionally, the research employs the Diffusion of Innovations (DOI) theory to assess the acceptance level of airline employees toward the system and its contribution to improving operational quality.

National Penghu University of Science and Technology (TW), National Kaohsiung Marine University (TW), National Kaohsiung University of Science and Technology (TW)
Decent work and economic growth
Openalex Percentile: Top 10%
Aviation Industry Analysis and Trends
3.09
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Enhancing Boarding Efficiency with Facial Recognition in Smart Airport Terminals — Szu‐Yu Kuo, Liang-Bi Chen, et al. · (2025) | TGRS Research Map | TGRS