Fusion of VMS and Radiation Sensor Data for Real-Time Identification and Tracking

Traditionally, implementation of dedicated, continuous nuclear and radiological monitoring systems for identifying and tracking nuclear materials out of regulatory control is associated with high operational burdens. Although video and images from cameras are helpful in assessing threats, the raw, unstructured data require time-intensive human interaction to extract the relevant actionable information for adjudicating a threat. A solution to this is to automatically combine spatiotemporal information from radiological sensors and cameras with video and data analytics within a computing platform such as a Video Management System (VMS), to produce structured, annotated video information that allows security stakeholders to adjudicate potential threats rapidly. The purpose of the proposed work is to exploit video/data analytics and camera control solutions of VMSs in order to support the detection, identification, and tracking of nuclear/radiological objects moving within the monitored environment, as well as to generate actionable information about the object that is carrying/conveying the threat materials. The results will be design specifications and trade space assessments of different VMS integrations, a prototype integrated system that validates the proposed system design, and a final selection of VMS platforms for full development in Phase II. The potential commercial applications of the effort is the offering of radiation detection and the integration/tracking algorithms as an enhancement of camera-enabled existing security infrastructure in federal, local, and state venues.