Applications and Technologies of Big Data in the Aerospace Domain

Author:

Adamopoulou Evgenia1ORCID,Daskalakis Emmanouil1ORCID

Affiliation:

1. Institute of Communication and Computer Systems, National Technical University of Athens, 15773 Athens, Greece

Abstract

Over the last few years, Big Data applications have attracted ever-increasing attention in several scientific and business domains. Biomedicine, transportation, entertainment, and aerospace are only a few examples of sectors which are increasingly dependent on applications, where knowledge is extracted from huge volumes of heterogeneous data. The main goal of this paper was to conduct an academic literature review of prominent publications revolving around the application of BD in aerospace. A total of 67 publications were analyzed, highlighting the sources, uses, and benefits of BD. For categorizing the publications, a novel 6-fold approach was introduced including applications in aviation technology and aviation management, UAV-enabled applications, applications in military aviation, health/environment-related applications, and applications in space technology. Aiming to provide the reader with a clear overview of the existing solutions, a total of 15 subcategories were also utilized. The results indicated numerous benefits deriving from the application of BD in aerospace. These benefits referred to the aerospace domain itself as well as to many other sectors including healthcare, environment, humanitarian operations, network communications, etc. Various data sources and different Machine Learning models were utilized in the analyzed publications and the use of BD-based techniques enabled us to extract useful correlations and gain useful insights from large volumes of data.

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering

Reference82 articles.

1. Directorate-General for Justice and Consumers (European Commission) (2016). The EU Data Protection Reform and Big Data, Publications Office of the European Union.

2. Big Data Analytics and Firm Performance: Findings from a Mixed-Method Approach;Mikalef;J. Bus. Res.,2019

3. A Survey on Blockchain for Big Data: Approaches, Opportunities, and Future Directions;Deepa;Future Gener. Comput. Syst.,2022

4. Piazolo, F., Geist, V., Brehm, L., and Schmidt, R. (2016, January 14). Towards Differentiating Business Intelligence, Big Data, Data Analytics and Knowledge Discovery. Proceedings of the Innovations in Enterprise Information Systems Management and Engineering, Hagenberg, Austria.

5. Khan, N., Alsaqer, M., Shah, H., Badsha, G., Abbasi, A.A., and Salehian, S. (2018, January 9–11). The 10 Vs, Issues and Challenges of Big Data. Proceedings of the 2018 International Conference on Big Data and Education (ICBDE ’18), Honolulu, HI, USA.

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3