Summary
The number of goods and parcels shipped is growing with unstoppable speed. With more individual shipments the means of logistics have changed from central locations to small logistics companies, postal agencies, airports, ports, private vehicles etc. However, the analysis and detection capabilities of such locations are very low, making it an easy target for transporting illicit goods.
Currently, there are no effective technologies available that would be able to cope with this growing problem. Despite the widespread use of X-ray technologies, they are still inefficient when it comes to mobile scenarios. In addition, their detection capability is based solely on visual imaging with no way to examine the exact material content of small shipments.
We are proposing a completely novel, yet highly effective solution for this. The CosmoPort project will develop the next generation of scanner systems using Atmospheric Ray Tomography (ART). Such systems are equipped with advanced Machine Learning-based risk assessment tool. As muon tomography itself is a technique already in use, then we will develop the first mobile solution combined with AI/ML tools to enhance material and object classification for the first time ever.
Currently, there are no effective technologies available that would be able to cope with this growing problem. Despite the widespread use of X-ray technologies, they are still inefficient when it comes to mobile scenarios. In addition, their detection capability is based solely on visual imaging with no way to examine the exact material content of small shipments.
We are proposing a completely novel, yet highly effective solution for this. The CosmoPort project will develop the next generation of scanner systems using Atmospheric Ray Tomography (ART). Such systems are equipped with advanced Machine Learning-based risk assessment tool. As muon tomography itself is a technique already in use, then we will develop the first mobile solution combined with AI/ML tools to enhance material and object classification for the first time ever.
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| Web resources: | https://cordis.europa.eu/project/id/101121379 |
| Start date: | 01-10-2023 |
| End date: | 30-09-2026 |
| Total budget - Public funding: | 3 035 260,50 Euro - 2 480 335,00 Euro |
Cordis data
Original description
The number of goods and parcels shipped is growing with unstoppable speed. With more individual shipments the means of logistics have changed from central locations to small logistics companies, postal agencies, airports, ports, private vehicles etc. However, the analysis and detection capabilities of such locations are very low, making it an easy target for transporting illicit goods.Currently, there are no effective technologies available that would be able to cope with this growing problem. Despite the widespread use of X-ray technologies, they are still inefficient when it comes to mobile scenarios. In addition, their detection capability is based solely on visual imaging with no way to examine the exact material content of small shipments.
We are proposing a completely novel, yet highly effective solution for this. The CosmoPort project will develop the next generation of scanner systems using Atmospheric Ray Tomography (ART). Such systems are equipped with advanced Machine Learning-based risk assessment tool. As muon tomography itself is a technique already in use, then we will develop the first mobile solution combined with AI/ML tools to enhance material and object classification for the first time ever.
Status
SIGNEDCall topic
HORIZON-CL3-2022-BM-01-03Update Date
12-03-2024
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