Applications and Technologies of Big Data in the Aerospace Domain
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 extrac...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-05-01
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| Series: | Electronics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-9292/12/10/2225 |
| _version_ | 1797600293094948864 |
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| author | Evgenia Adamopoulou Emmanouil Daskalakis |
| author_facet | Evgenia Adamopoulou Emmanouil Daskalakis |
| author_sort | Evgenia Adamopoulou |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-11T03:46:27Z |
| format | Article |
| id | doaj.art-28e95d76ba254cfc809a2f9fb7c4bea1 |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-11T03:46:27Z |
| publishDate | 2023-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-28e95d76ba254cfc809a2f9fb7c4bea12023-11-18T01:09:28ZengMDPI AGElectronics2079-92922023-05-011210222510.3390/electronics12102225Applications and Technologies of Big Data in the Aerospace DomainEvgenia Adamopoulou0Emmanouil Daskalakis1Institute of Communication and Computer Systems, National Technical University of Athens, 15773 Athens, GreeceInstitute of Communication and Computer Systems, National Technical University of Athens, 15773 Athens, GreeceOver 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.https://www.mdpi.com/2079-9292/12/10/2225big databig data analyticsaviation technologyaviation managementunmanned aerial vehiclesaerospace |
| spellingShingle | Evgenia Adamopoulou Emmanouil Daskalakis Applications and Technologies of Big Data in the Aerospace Domain Electronics big data big data analytics aviation technology aviation management unmanned aerial vehicles aerospace |
| title | Applications and Technologies of Big Data in the Aerospace Domain |
| title_full | Applications and Technologies of Big Data in the Aerospace Domain |
| title_fullStr | Applications and Technologies of Big Data in the Aerospace Domain |
| title_full_unstemmed | Applications and Technologies of Big Data in the Aerospace Domain |
| title_short | Applications and Technologies of Big Data in the Aerospace Domain |
| title_sort | applications and technologies of big data in the aerospace domain |
| topic | big data big data analytics aviation technology aviation management unmanned aerial vehicles aerospace |
| url | https://www.mdpi.com/2079-9292/12/10/2225 |
| work_keys_str_mv | AT evgeniaadamopoulou applicationsandtechnologiesofbigdataintheaerospacedomain AT emmanouildaskalakis applicationsandtechnologiesofbigdataintheaerospacedomain |