A multi-sensor cognitive approach for active security monitoring of abnormal overcrowding situations

Intelligent camera networks have been lately employed for a wide range of heterogeneous purposes, concerning both security and safety oriented systems. Military and civil applications ranging from border surveillance and public spaces monitoring to ambient intelligence and road safety are representative of such various applications. In this paper a discussion on the exploitation of a cognitive-based architecture, coupling simulation tools to real scenarios for interaction modelling and analysis, is presented. The application of the proposed general framework, which is given the name of Cognitive Node - CN, to crowd monitoring is hereby presented.