Airport security screening could get a lot faster, thanks to a T2 agreement between the Department of Homeland Security (DHS) Science and Technology Directorate (S&T) and Analytical AI of Birmingham, Alabama.
The DHS S&T awarded $199,536 in Phase 1 funding to Analytical AI, to explore the use of artificial intelligence to improve efficiency at airport security checkpoints by reducing the cognitive load on Transportation Security Officers.
“The airport screening process engages human experts in a repetitive, visually learned task with inherent inefficiencies,” said Karl Harris, S&T Object Recognition Program Manager. “With appropriate training, deep learning techniques can match or exceed human expert accuracy and augment the efficiency of the screening process.”
Analytical AI received its award under the Silicon Valley Innovation Program’s (SVIP’s) “Object Recognition and Adaptive Algorithms in Passenger Property Screening” solicitation, which focuses on using adaptive image interpretation and object recognition to enhance the Transportation Security Administration’s (TSA’s) detection and screening capabilities.
The company proposes to generate deep learning algorithms to develop an object identification engine that can rapidly and accurately detect common Stream of Commerce items. Machine learning algorithms that can rapidly and accurately label baggage and passenger items have the potential to revolutionize airport screening by increasing throughput, reducing false alarms, and improving detection.
The proposed product will provide both stand-alone and cloud-based interaction across a network of screening devices, which will rapidly implement new algorithms across the network as they are organically updated with new screening data and priorities.
SVIP is one of the programs and tools available for S&T to fund innovation and engage with private sector partners to advance homeland security solutions. Companies participating in SVIP are eligible for up to $800,000 of non-dilutive funding over four phases to develop and adapt commercial technologies for homeland security use cases.
Read more: https://www.dhs.gov/science-and-technology/news/2020/04/10/news-release-...