An Agent-Based Approach to Understand Events in Surveillance Environments

Intelligent surveillance aims at providing artificial systems in order to monitor and improve the security of public and private spaces. Since these environments are complex and the information is distributed through them, agent-based solutions represent a good approach when monitoring moving objects. This paper describes how an existing agent platform has been adopted and used to carry out intelligent surveillance. Within this context, agents implement a behavior-based model that is flexible enough to deal with the challenges that the surveillance tasks pose. The experimental results show how this agent-based approach can contribute to understand events in urban traffic environments.