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Multi-agent system for knowledge-based event recognition and composition



Abstract: This work presents a multi-agent system for knowledge-based high-level event composition, which interprets activities, behaviour and situations semantically in a scenario with multi-sensory monitoring. A perception agent (plurisensory agent and visual agent)-based structure is presented. The agents process the sensor information and identify (agent decision system) significant changes in the monitored signals, which they send as simple events to the composition agent that searches for and identifies pre-defined patterns as higher-level semantic composed events. The structure has a methodology and a set of tools that facilitate its development and application to different fields without having to start from scratch. This creates an environment to develop knowledge-based systems generally for event composition. The application task of our work is surveillance, and event composition/inference examples are shown which characterize an alarming situation in the scene and resolve identification and tracking problems of people in the scenario being monitored.