Predictive Maintenance in Aviation using Artificial Intelligence

Kondala Rao Patibandla ()

Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, 2024, vol. 4, issue 1, 325-333

Abstract: Predictive maintenance in aviation using artificial intelligence (AI) is transforming the way aircraft are maintained and operated. By analyzing data from various aircraft sensors, AI algorithms can predict potential failures before they happen, allowing for timely and efficient maintenance. This proactive approach reduces unplanned downtime, enhances safety, and lowers maintenance costs. The implementation of AI in predictive maintenance leverages technologies such as machine learning, data analytics, and the Internet of Things (IoT) to monitor and analyze the health of aircraft components continuously. This abstract provides a comprehensive overview of how AI-driven predictive maintenance works, its benefits, and its impact on the aviation industry, making it easier for anyone to understand its significance and potential.

Keywords: Aircraft Predictive Maintenance; AI; AWS; IoT; SageMaker Trainings; Prediction Models (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
https://newjaigs.com/index.php/JAIGS/article/view/214 (application/pdf)

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:das:njaigs:v:4:y:2024:i:1:p:325-333:id:214

Access Statistics for this article

Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023 is currently edited by Justyna Żywiołek

More articles in Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023 from Open Knowledge
Bibliographic data for series maintained by Open Knowledge ().