Artificial Intelligence of Things as New Paradigm in Aviation Health Monitoring Systems

Igor Kabashkin () and Leonid Shoshin
Additional contact information
Igor Kabashkin: Engineering Faculty, Transport and Telecommunication Institute, Lauvas iela 2, LV-1019 Riga, Latvia
Leonid Shoshin: Sky Net Technics, Business Center 03, Ras Al-Khaimah B04-223, United Arab Emirates

Future Internet, 2024, vol. 16, issue 8, 1-33

Abstract: The integration of artificial intelligence of things (AIoT) is transforming aviation health monitoring systems by combining extensive data collection with advanced analytical capabilities. This study proposes a framework that enhances predictive accuracy, operational efficiency, and safety while optimizing maintenance strategies and reducing costs. Utilizing a three-tiered cloud architecture, the AIoT system enables real-time data acquisition from sensors embedded in aircraft systems, followed by machine learning algorithms to analyze and interpret the data for proactive decision-making. This research examines the evolution from traditional to AIoT-enhanced monitoring, presenting a comprehensive architecture integrated with satellite communication and 6G technology. The mathematical models quantifying the benefits of increased diagnostic depth through AIoT, covering aspects such as predictive accuracy, cost savings, and safety improvements are introduced in this paper. The findings emphasize the strategic importance of investing in AIoT technologies to balance cost, safety, and efficiency in aviation maintenance and operations, marking a paradigm shift from traditional health monitoring to proactive health management in aviation.

Keywords: artificial intelligence of things; aviation; health monitoring system; health management; maintenance; diagnostics (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1999-5903/16/8/276/pdf (application/pdf)
https://www.mdpi.com/1999-5903/16/8/276/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jftint:v:16:y:2024:i:8:p:276-:d:1448881

Access Statistics for this article

Future Internet is currently edited by Ms. Grace You

More articles in Future Internet from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().