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This paper describes the evolution of our research from video analytics to aglobal security system with focus on the video surveillance component. Indeedvideo surveillance has evolved from a commodity security tool up to the mostefficient way of tracking perpetrators when terrorism hits our modern urbancenters. As number of cameras soars, one could expect the system to leveragethe huge amount of data carried through the video streams to provide fastaccess to video evidences, actionable intelligence for monitoring real-timeevents and enabling predictive capacities to assist operators in theirsurveillance tasks. This research explores a hybrid platform for videointelligence capture, automated data extraction, supervised Machine Learningfor intelligently assisted urban video surveillance; Extension to othercomponents of a global security system are discussed. Applying KnowledgeManagement principles in this research helps with deep problem understandingand facilitates the implementation of efficient information and experiencesharing decision support systems providing assistance to people on the field aswell as in operations centers. The originality of this work is also thecreation of "common" human-machine and machine to machine language and asecurity ontology.

Video Intelligence as a component of a Global Security system