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

Incorporating video and camera data into radiological and nuclear (R/N) security systems enables better threat attribution and tracking, but building a dedicated camera network for and assessing the raw data is burdensome. Instead, existing networks of security cameras, often connected in a Video Management System (VMS), can be leveraged for R/N threat adjudication by combining spatiotemporal information from radiological sensor networks with the video and images from a VMS. The purpose of this work is to leverage the large install base of VMS-connected cameras to support the detection, identification, and tracking of R/N objects within the monitored environment. This effort will include two system design spirals, partner field tests, and development of attribution algorithms. The result of the proposed work will be a prototype system designed for scalability through integration with different types of VMSs. This prototype will be tested in deployments with two partners. The commercial application of the effort is to offer a secure, low-barrier method of making camera feeds available for security infrastructure in federal, state, and local venues.