Analytical AI of Birmingham, Ala., received a Department of Homeland Security (DHS) Science and Technology Directorate (S&T) funding award to aid Transportation Security Administration (TSA) detection and screening capabilities.
The $199,536 allotment through the Silicon Valley Innovation Program’s (SVIP’s) “Object Recognition and Adaptive Algorithms in Passenger Property Screening” solicitation focuses on using adaptive image interpretation and object recognition.
“The airport screening process engages human experts in a repetitive, visually learned task with inherent inefficiencies,” Karl Harris, S&T Object Recognition program manager, said. “With appropriate training, deep learning techniques can match or exceed human expert accuracy and augment the efficiency of the screening process.”
The scope of work involves generating deep learning algorithms to develop an object identification engine rapidly and accurately detect common Stream of Commerce (SoC) items. The application of artificial intelligence techniques possesses the potential to enhance screening efficiency at security checkpoints by reducing the cognitive load on Transportation Security Officers (TSOs).
“Our goal is to help TSA use artificial intelligence techniques to differentiate stream-of-commerce items,” SVIP Managing Director Melissa Oh said. “Analytical AI has proposed to develop robust, network-ready screening tools that would meet current TSA requirements with the flexibility to adapt to future TSA mission priorities.”