A multi-agent architecture for supporting distributed normality-based intelligent surveillance

作者：Vallejo D^*; Albusac J; Castro Schez J J; Glez Morcillo C; Jimenez L

来源：Engineering Applications of Artificial Intelligence, 2011, 24(2): 325-340.

DOI：10.1016/j.engappai.2010.11.005

• Distributed Intelligent Surveillance
• Complex Monitoring
• Multi-Agent Architecture
• Knowledge Acquisition
• Machine Learning

Intelligent surveillance involves the use of Al techniques to monitor environments whose analysis is becoming more and more complex because of the large number of sensors used and the need of monitoring multiple events of interest simultaneously. Most of the current surveillance systems provide solutions for particular problems but still suffer from lack of flexibility and scalability when they are used on different or related surveillance problems. To overcome this limitation, two aspects should be addressed: a knowledge-based surveillance model flexible enough to deal with different events of interest and an architecture that gives support to this model when deploying the surveillance system within a particular scenario. This paper discusses the architecture devised to deploy intelligent surveillance systems by means of a set of autonomous agents that are responsible for the management of different surveillance tasks and for cooperating to monitor complex environments. This multi-agent architecture is inspired by a normality-based formal model used to define the knowledge needed to analyze general-purpose surveillance concepts. We use the architecture to deploy a surveillance system to monitor an urban traffic scenario.

• 出版日期2011-3