Classi-fly inferring aircraft categories from open data
In recent years, air traffic communication data has become easy to access, enabling novel research in many fields. Exploiting this new data source, a wide range of applications have emerged, from weather forecasting to stock market prediction, or the collection of intelligence about military and gov...
| Main Authors: | , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Association for Computing Machinery
2021
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| _version_ | 1826261515363155968 |
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| author | Strohmeier, M Smith, MJ Lenders, V Martinovic, I |
| author_facet | Strohmeier, M Smith, MJ Lenders, V Martinovic, I |
| author_sort | Strohmeier, M |
| collection | OXFORD |
| description | In recent years, air traffic communication data has become easy to access, enabling novel research in many fields. Exploiting this new data source, a wide range of applications have emerged, from weather forecasting to stock market prediction, or the collection of intelligence about military and government movements. Typically, these applications require knowledge about the metadata of the aircraft, specifically its operator and the aircraft category.
armasuisse Science + Technology, the R&D agency for the Swiss Armed Forces, has been developing Classi-Fly, a novel approach to obtain metadata about aircraft based on their movement patterns. We validate Classi-Fly using several hundred thousand flights collected through open source means, in conjunction with ground truth from publicly available aircraft registries containing more than 2 million aircraft. We show that we can obtain the correct aircraft category with an accuracy of greater than 88%. In cases, where no metadata is available, this approach can be used to create the data necessary for applications working with air traffic communication. Finally, we show that it is feasible to automatically detect particular sensitive aircraft such as police and surveillance aircraft using this method. |
| first_indexed | 2024-03-06T19:22:39Z |
| format | Journal article |
| id | oxford-uuid:1a9fee32-29a9-4c38-b7fa-99d56d8a11bc |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T19:22:39Z |
| publishDate | 2021 |
| publisher | Association for Computing Machinery |
| record_format | dspace |
| spelling | oxford-uuid:1a9fee32-29a9-4c38-b7fa-99d56d8a11bc2022-03-26T10:55:58ZClassi-fly inferring aircraft categories from open dataJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:1a9fee32-29a9-4c38-b7fa-99d56d8a11bcEnglishSymplectic ElementsAssociation for Computing Machinery2021Strohmeier, MSmith, MJLenders, VMartinovic, IIn recent years, air traffic communication data has become easy to access, enabling novel research in many fields. Exploiting this new data source, a wide range of applications have emerged, from weather forecasting to stock market prediction, or the collection of intelligence about military and government movements. Typically, these applications require knowledge about the metadata of the aircraft, specifically its operator and the aircraft category. armasuisse Science + Technology, the R&D agency for the Swiss Armed Forces, has been developing Classi-Fly, a novel approach to obtain metadata about aircraft based on their movement patterns. We validate Classi-Fly using several hundred thousand flights collected through open source means, in conjunction with ground truth from publicly available aircraft registries containing more than 2 million aircraft. We show that we can obtain the correct aircraft category with an accuracy of greater than 88%. In cases, where no metadata is available, this approach can be used to create the data necessary for applications working with air traffic communication. Finally, we show that it is feasible to automatically detect particular sensitive aircraft such as police and surveillance aircraft using this method. |
| spellingShingle | Strohmeier, M Smith, MJ Lenders, V Martinovic, I Classi-fly inferring aircraft categories from open data |
| title | Classi-fly inferring aircraft categories from open data |
| title_full | Classi-fly inferring aircraft categories from open data |
| title_fullStr | Classi-fly inferring aircraft categories from open data |
| title_full_unstemmed | Classi-fly inferring aircraft categories from open data |
| title_short | Classi-fly inferring aircraft categories from open data |
| title_sort | classi fly inferring aircraft categories from open data |
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