 Machine learning and mixed reality for smart aviation: Applications and challengesYirui Jiang, Trung Hieu Tran and Leon Williams Journal of Air Transport Management, 2023, vol. 111, issue C 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. Keywords: Aerospace engineering; Artificial intelligence; Intelligent aviation; Machine learning; Mixed reality; Passenger experience; Smart aviation (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:jaitra:v:111:y:2023:i:c:s0969699723000807 DOI: 10.1016/j.jairtraman.2023.102437 Access Statistics for this article Journal of Air Transport Management is currently edited by Anne Graham More articles in Journal of Air Transport Management from Elsevier |
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