Jiang, Yirui, Tran, Trung Hieu and Williams, Leon (2023). Machine learning and mixed reality for smart aviation: Applications and challenges. Journal of Air Transport Management, 111 ,
Abstract
The aviation industry is a dynamic and ever-evolving sector. As technology advances and becomes more sophisticated, the aviation industry must keep up with the changing trends. While some airlines have made investments in machine learning and mixed reality technologies, the vast majority of regional airlines continue to rely on inefficient strategies and lack digital applications. This paper investigates the state-of-the-art applications that integrate machine learning and mixed reality into the aviation industry. Smart aerospace engineering design, manufacturing, testing, and services are being explored to increase operator productivity. Autonomous systems, self-service systems, and data visualization systems are being researched to enhance passenger experience. This paper investigate safety, environmental, technological, cost, security, capacity, and regulatory challenges of smart aviation, as well as potential solutions to ensure future quality, reliability, and efficiency.
Publication DOI: | https://doi.org/10.1016/j.jairtraman.2023.102437 |
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Divisions: | College of Business and Social Sciences College of Business and Social Sciences > Aston Business School Aston University (General) |
Additional Information: | Crown Copyright © 2023 Published by Elsevier Ltd. This is an open access article under the CC BY license (https://creativecommons.org/licenses/by/4.0/). |
Uncontrolled Keywords: | Aerospace engineering,Artificial intelligence,Intelligent aviation,Machine learning,Mixed reality,Passenger experience,Smart aviation,Transportation,Strategy and Management,Management, Monitoring, Policy and Law,Law |
Publication ISSN: | 0969-6997 |
Last Modified: | 25 Apr 2025 07:12 |
Date Deposited: | 24 Apr 2025 13:37 |
Full Text Link: | |
Related URLs: |
http://www.scop ... tnerID=8YFLogxK
(Scopus URL) https://www.sci ... 0807?via%3Dihub (Publisher URL) |
PURE Output Type: | Article |
Published Date: | 2023-08 |
Published Online Date: | 2023-06-04 |
Accepted Date: | 2023-05-14 |
Authors: |
Jiang, Yirui
Tran, Trung Hieu ( ![]() Williams, Leon |