Please use this identifier to cite or link to this item: https://bura.brunel.ac.uk/handle/2438/33912
Title: IoT Data Mining of Air Cargo for Autonomous Artificial Intelligent Raising of Import Duties by Revenue and Customs
Authors: Ali, Kareem
Ioannou, Georgios
Louvieris, Panos
Cosmas, John
Taylor, Marcus
Dimitrakakis, Georgios
Chome, Edward
Mete, Sahin
Kizil, Taskin
Celik, Semih
Bulut, Betul
Issue Date: 12-Sep-2025
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
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.
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.
URI: https://bura.brunel.ac.uk/handle/2438/33912
DOI: https://doi.org/10.1109/iccvdm66874.2025.11290038
ISBN: 9798331566210
9798331566203
9798331566227
Appears in Collections:Department of Computer Science Research Papers
Department of Electronic and Electrical Engineering Research Papers

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