Enhanced Cargo Screening Analysis via Image-Manifest Correlation

Physical Sciences Inc. (PSI) proposes to develop an air cargo screening software suite that automatically parses air cargo waybills and detects and localizes the reported cargo contents within X-ray images obtained during screening. The software will utilize state-of-the-art machine-learning (ML) and natural language processing techniques to rapidly analyze and correlate manifests with associated X-ray/CT imagery. The resulting prototype software will be deployed on a lightweight external device that interfaces with existing screening systems via wired connection. The software will feature a novel vision-language model that exhibits a natural language understanding of X-ray imagery. This software is designed to relieve mental fatigue experienced by the screener and facilitate rapid decision-making, with the result of increasing throughput and accuracy in the overall screening process. The AIMACS capability will enable a 50% reduction in time to form screening decisions, and a 30% reduction in secondary searches in the event of anomalous cargo contents. Additionally, the object detection and localization capabilities will reduce the scope of required secondary screenings, reducing the time and liability costs associated with manual inspection.