Communications of the ACM
Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
On agent-based software engineering
Artificial Intelligence
Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence
Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence
Privacy: The Achilles Heel of Pervasive Computing?
IEEE Pervasive Computing
Ubiquitous Computing in the Automotive Domain (Abstract)
Pervasive '02 Proceedings of the First International Conference on Pervasive Computing
A new approach to the BDI agent-based modeling
Proceedings of the 2004 ACM symposium on Applied computing
A web-based surveillance system for mobile phones
Proceedings of the 1st international conference on MOBILe Wireless MiddleWARE, Operating Systems, and Applications
Survey on contemporary remote surveillance systems for public safety
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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This paper illustrates how the adoption of techniques typical of artificial intelligence (AI) could improve the performance of monitoring and control systems (MCSs). Traditional MCSs are designed according to a three-level architectural pattern in which intelligent devices are usually devoted to evaluate whether the data acquired by a set of sensors could be interpreted as anomalous or not. Possible mistakes in the evaluation process, due to faulty sensors or external factors, can cause the generation of undesirable false alarms. To solve this problem, the traditional three-tier architecture of MCSs has been extended with a fourth level, named the correlation level, where an intelligent module, usually a knowledge-based system, collects the local interpretations made by each evaluation device, building a global view of the monitored field. In this way, possible local mistakes are identified by the comparison with other local interpretations.