Leveraging Artificial Intelligence Is Smart for Explosive Detection

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Source: Courtney Maxson, U.S. Army
Source: Courtney Maxson, U.S. Army

January 5, 2024 | Originally published by The Department of Homeland Security on December 14, 2023

Harnessing the power and possibilities of artificial intelligence (AI) and machine learning (ML) and applying these emerging capabilities to the Department of Homeland Security (DHS) mission has been, and will continue to be, a high priority for the Science and Technology Directorate (S&T). One way S&T is demonstrating this commitment to applying emerging technologies to pressing national threats is by investing in the development of AI/ML technologies. Specifically in this case, the funding is directed at AI/ML that could soon be used to identify dangerous compounds, like those found in explosives and narcotics.

When the DHS Small Business Innovation Research (SBIR) Program released a solicitation back in FY2020, under the topic “Machine Learning Module for Detection Technologies,” the goal was to develop innovative solutions that would ultimately provide DHS operational components with an enhanced ability to identify new threats at aviation checkpoints. In the spring of 2021, following their 6-month Phase I awards to demonstrate concept feasibility, Physical Sciences Inc. (PSI) and Alakai Defense Systems, Inc. (Alakai) were each awarded a $1 million, 24-month SBIR Phase II contract. These awards further lean into the ultimate goal of developing advanced AI/ML-based detection algorithms that can shorten the timeline for deployment of capabilities able to identify threats in the field. The research and development (R&D) being done is important because it addresses a capability gap in the detection of certain types of new threats. S&T believes that AI/ML solutions can help close that gap.

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