The PhD research will develop the latest techniques in deep learning to improve automated threat detection in next-generation airport baggage scanners.
The introduction of x-ray baggage scanners and their automated threat detection capabilities was a significant milestone in aviation security and although they prove highly successful there’s still further challenges to meet. As threats evolve and demand for air travel increases, technology must adapt and become more sophisticated. The UK Government’s Department for Transport (DfT) has identified the ability to detect emerging threat materials and objects in baggage, whilst maintaining or even enhancing the passenger transit experience as a critical challenge.
Thanks to funding from the UK Government’s Department for Transport (DfT) and the Home Office, the Imperial College London’s Institute for Security Science and Technology (ISST) and Smiths Detection will now try to meet this challenge in their collaborative Future Aviation Security Solutions (FASS) programme.
These next generation scanners aim to address the changing nature of terrorist and criminal methods, the need to process more passengers in a short time, and the increase in carry-on electronic items which can obscure scans. Evolving from the 2D images scanners currently produce, the next step is to use Computed Tomography to generate 3D images, which provide human operators greater clarity with what they are seeing.
According to Professor Deeph Chana, Co-Director of the ISST:
“The next generation of security technologies for aviation will need to provide increased operational efficiency, together with improvements in detection capability. The ability to have X-ray computed tomography screening at passenger check-points has been a goal in this regard for some time and numerous engineering challenges have had to be addressed to get us to the point where this has become a reality.
Imperial College London is recognised as a world-leader in artificial intelligence and machine learning, enabling the collaboration to focus on developing convoluted neural networks – a class of deep learning algorithms – for analysing the 3D images from this new generation of scanners.
“The partnership between Smiths Detection and Imperial’s Institute for Security Science and technology on this PhD studentship aims to advance what can be done using machine learning to optimise the use of the data generated by such platforms, bringing together world leading commercial and academic STEM expertise in aviation security systems.” Said Deeph.
Matt Clark, Smiths Detection Vice President expressed his excitement in the project:
“This is an exciting next step in our strategic partnership with Imperial College London and the ISST, allowing us to collaborate on the development of innovative technology for aviation security and expand this field of knowledge. This PhD and our ongoing partnership with one of the leading science and technology universities in the world, aligns with our ambition to provide next-generation security solutions that help to make the world a safer place,”