Project description
AI-based tools to streamline airport customs control
The increasing number of air travellers presents a challenge to customs control at airports, as the large volume of passengers impacts the effectiveness of control measures. The EU-funded BAG-INTEL project will enhance the efficiency of customs control for air traveller baggage at inland border airports, utilising advanced detection systems and information tools based on artificial intelligence (AI). The project's goal is to reduce reliance on human customs resources while ensuring effective customs control in response to the growing number of air travellers at inland border airports. BAG-INTEL will develop a comprehensive system solution that includes AI features to improve contraband detection during X-ray scanning, AI camera-based luggage re-identification, and a digital twin for system visualisation.
Objective
The BAG-INTEL project will provide robust AI based information utilization and decision support tools, within the context of advanced detection systems to support customs for increased effectiveness and efficiency of the customs control of air traveller baggage in inland border airports, while minimizing the human customs resources needed. This aim addresses the challenge of maintaining effective and efficient customs control of passenger baggage in the situation of the substantial growth of the volume of air travellers arriving in inland border airports with the limited human customs resources available. For this aim, the project will develop an integrated system solution comprising: (1) new AI powered functionality for enhanced detection of contraband in x-ray scanning of luggage, (2) AI camera based end-to-end reidentification of luggage, (3) digital twin for system visualisation and performance optimization for the operational context of an airport, (4) use case for test demonstration and evaluation in 3 European airports, a small, a medium sized, and a big airport, and (5) wide dissemination and elaboration of easy-to-use training material for end users. For the customs, BAG-INTEL solution aims to: increase the successful detection of contraband in luggage by at least 20%; demonstrate the possibility and utility in automatically to derive risk indicators from external data such as the Advanced Passenger Information; demonstrate the effectivity of AI camera based reidentification of luggage, when the traveller carries it into the customs space at the exit of the carousel area; increase the fluidity of passenger flow and control by at least 20%; decrease the customs personal resources mobilisation by at least 20%; derive data useful in flights risk assessment; derive data useful in flights risk assessment; demonstrate the autolearning capacity of this smart risk engine.
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HORIZON-RIA - HORIZON Research and Innovation ActionsCoordinator
4690 Haslev
Denmark
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
Participants (21)
75015 PARIS 15
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18071 Granada
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16129 Genova Ge
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
1253 Luxembourg
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15232 ATHINA
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
10178 Berlin
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106 82 ATHINA
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76 801 SAINT ETIENNE DU ROUVRAY
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65205 Wiesbaden
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118 54 ATHENS
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
28040 Madrid
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80539 Munchen
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10177 Athina
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
151 23 ATHINA
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101 84 Athens
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11415 TALLIN
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8310 TRANBJERG J
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28020 Madrid
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101 77 Athens
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28071 Madrid
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00153 Roma
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Partners (2)
1217 Meyrin 1
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
8600 Dubendorf
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.