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https://bura.brunel.ac.uk/handle/2438/33912Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Ali, Kareem | - |
| dc.contributor.author | Ioannou, Georgios | - |
| dc.contributor.author | Louvieris, Panos | - |
| dc.contributor.author | Cosmas, John | - |
| dc.contributor.author | Taylor, Marcus | - |
| dc.contributor.author | Dimitrakakis, Georgios | - |
| dc.contributor.author | Chome, Edward | - |
| dc.contributor.author | Mete, Sahin | - |
| dc.contributor.author | Kizil, Taskin | - |
| dc.contributor.author | Celik, Semih | - |
| dc.contributor.author | Bulut, Betul | - |
| dc.coverage.spatial | London, United Kingdom | - |
| dc.date.accessioned | 2026-09-29T15:43:06Z | - |
| dc.date.available | 2026-09-29T15:43:06Z | - |
| dc.date.issued | 2025-09-12 | - |
| dc.identifier.citation | Ali, K. et al. (2025) 'IoT Data Mining of Air Cargo for Autonomous Artificial Intelligent Raising of Import Duties by Revenue and Customs', 6th International Conference on Computer Vision and Data Mining (ICCVDM), London, United Kingdom, 12–14 September, pp. 365–369. doi: 10.1109/iccvdm66874.2025.11290038. | en_US |
| dc.identifier.isbn | 9798331566210 | - |
| dc.identifier.isbn | 9798331566203 | - |
| dc.identifier.isbn | 9798331566227 | - |
| dc.identifier.other | https://doi.org/10.1109/iccvdm66874.2025.11290038 | - |
| dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/33912 | - |
| dc.description.abstract | The vision presented by OECD's Forum on Tax Administration proposes a digital transformation of tax administration by embedding tax collecting process into the everyday activities that taxpayers use to service their needs rather than being an add-on process. The ATTACC project demonstrates how this could be achieved through Generic Radio Access Network (GRAN)-IoT-enabled cross-border trading. This project seeks to reduce frictions in international trade that stem from data duplication and complex administrative processes to deliver an automated cross-border tax and customs compliance capability and apply AI to analyze large datasets to spot discrepancies between declared income and actual financial activity. | en_US |
| dc.description.sponsorship | CELTIC NEXT Research Project ATTACC (AuTomated TAx Compliance for Cross-border Trading with GRAN-IoT) No C2023/2-23. | en_US |
| dc.format.extent | pp. 365–369 | - |
| dc.language | English | en_US |
| dc.language.iso | en_US | en_US |
| dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en_US |
| dc.rights | Re-use licence for this version: CC BY | - |
| dc.rights | Licence for published version: Publisher's own licence | - |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | - |
| dc.source | 6th International Conference on Computer Vision and Data Mining (ICCVDM) | - |
| dc.title | IoT Data Mining of Air Cargo for Autonomous Artificial Intelligent Raising of Import Duties by Revenue and Customs | en_US |
| dc.type | Conference paper | en_US |
| dc.date.dateAccepted | 2025-07-15 | - |
| dc.identifier.doi | https://doi.org/10.1109/iccvdm66874.2025.11290038 | - |
| dc.relation.isPartOf | 2025 6th International Conference on Computer Vision and Data Mining (ICCVDM) | en_US |
| pubs.finish-date | 2025-09-14 | - |
| pubs.publication-status | Published | - |
| pubs.start-date | 2025-09-12 | - |
| dc.rights.license | https://creativecommons.org/licenses/by/4.0/legalcode.en | - |
| dcterms.dateAccepted | 2025-07-15 | - |
| dcterms.issued | 2025-09-12 | - |
| dc.date.updated | 2026-09-29T15:38:07Z | - |
| dc.rights.holder | The Author(s) | - |
| dc.contributor.orcid | Ioannou, Georgios [0000-0002-1986-5472] | - |
| dc.contributor.orcid | Louvieris, Panos [0000-0001-7685-0309] | - |
| dc.contributor.orcid | Cosmas, John [0000-0003-4378-5576] | - |
| Appears in Collections: | Department of Computer Science Research Papers Department of Electronic and Electrical Engineering Research Papers | |
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|---|---|---|---|---|
| FullText.pdf | Copyright ‘For the purpose of open access, the author has applied a ‘Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising.’ | 1.6 MB | Adobe PDF | View/Open |
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