Decision-level information fusion to assess threat likelihood in shipped containers

A significant challenge in the distribution of goods is assessing the potential threat that an individual shipping container poses. Due to the high volume of shipped goods, a primary concern is balancing accuracy and container scan time. The application of information fusion to the problem enables automated threat determination and the presentation of relevant data to an operator, in a decision support capacity, in order to maintain a sufficient level of processing. This paper outlines an approach to container threat assessment that combines data from multiple sources in order to reliably score the likelihood that a given container holds a threat. Fused data is also leveraged as a tool to optimize the routing of containers through a scanning system comprised of multiple data acquisition stations and providing data in multiple modes. Furthermore, we propose methods for the consolidated presentation of fused data to an operator in order to both minimize the time expended in container evaluation and maximize the accuracy of the assessment.