航空疲劳和睡眠问题检测策略综述:人工智能的启示

IF 9.7 2区 工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Yan Li, Jibo He
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引用次数: 0

摘要

在过去几年中,由于人为因素造成的航空灾难性事故越来越多,给人类带来了一些毁灭性的威胁。最近,人工智能(AI)在飞行员疲劳识别方面取得了进展,通过识别和警告航空专业人员认知能力受损导致的潜在灾难性事故,开始大力加强航空领域的安全。在本综述中,我们深入研究了基于人工智能的疲劳检测方法在航空领域的应用。据我们所知,这篇综述文章显然是一篇新论文,专门研究了基于人工智能的方法在解决航空领域睡眠和疲劳问题方面所取得的进展和面临的挑战。首先,我们介绍了疲劳的基本定义、在航空专业人员中引发这些问题的各个方面及其对航空安全的影响。其次,我们回顾了为评估航空业疲劳和睡眠问题而开发的基于人工智能的方法。第三,对各种方法进行了比较,总结了现有工作的效率。最后,我们讨论了最先进的方法所遇到的挑战,以确定未来的研究方向,并提出了建议的解决方案,以提高疲劳检测方法的效率。这项综合研究清楚地表明,基于人工智能的疲劳识别方法的发展具有更广阔的空间,可以通过提前识别飞行员的精神状态并提供适当的干预措施来缓解飞行员的疲劳。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A Review of Strategies to Detect Fatigue and Sleep Problems in Aviation: Insights from Artificial Intelligence

A Review of Strategies to Detect Fatigue and Sleep Problems in Aviation: Insights from Artificial Intelligence

Over the past few years, the increasing occurrence of catastrophic accidents in aviation owing to human factors has raised several devastating threats to mankind. Recent progress in fatigue recognition among pilots made by Artificial intelligence (AI) has intensely begun to enhance the safety of the aviation sector by identifying and warning the potential catastrophic incidents caused by the impaired cognitive condition of aviation professionals. In this review, we have thoroughly investigated the implementation of AI-based approaches in the domain of aviation for fatigue detection. To the extent of our knowledge, it is clear that this review article is a new paper extremely devoted for investigating the advancements and challenges rendered by the AI-based approaches for addressing sleep and fatigue issues in aviation. Initially, we provided the basic definition of fatigue, various aspects provoking these problems among aviation professionals, and its effects in compromising aviation safety. Secondly, we illustrated a review of AI-based approaches developed for assessing fatigue and sleep problems in the context of aviation. Thirdly, the comparisons of various approaches are provided to summarize the efficiency of the existing works. Finally, we talked about the challenges encountered by the state-of-the-art approaches for identifying future research direction, and our suggested solutions are well presented for improving the efficiency of the fatigue detection approaches. This comprehensive research clearly depicts that the advancement of fatigue recognition approaches based on AI has a wider scope for mitigating pilot’s fatigue by identifying the mental state of the pilot earlier and providing adequate interventions.

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来源期刊
CiteScore
19.80
自引率
4.10%
发文量
153
审稿时长
>12 weeks
期刊介绍: Archives of Computational Methods in Engineering Aim and Scope: Archives of Computational Methods in Engineering serves as an active forum for disseminating research and advanced practices in computational engineering, particularly focusing on mechanics and related fields. The journal emphasizes extended state-of-the-art reviews in selected areas, a unique feature of its publication. Review Format: Reviews published in the journal offer: A survey of current literature Critical exposition of topics in their full complexity By organizing the information in this manner, readers can quickly grasp the focus, coverage, and unique features of the Archives of Computational Methods in Engineering.
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