2011
DOI: 10.1007/978-3-642-24769-9_5
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Organizations of Agents in Information Fusion Environments

Abstract: Information fusion in a context-aware system is understood as a process that assembles assessments of the environment based on its goals. Advantages of intelligent approaches such as Multi-Agent Systems (MAS) and the use of Wireless Sensor Networks (WSN) within the information fusion process are emerging, especially in context-aware scenarios. However, it has become critical to propose improved and efficient ways to handle the enormous quantity of data provided by these approaches. Agents are a suitable option… Show more

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Cited by 3 publications
(2 citation statements)
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“…To deal with the challenges of developing context across distributed data collection nodes, a number of authors have utilized agent-based approaches. Tapia et al [78] proposed a distributed multi-agent system approach, where a group of deliberative agents acting as controllers and administrators for the applications and services could better handle contextinformation in dynamic environments and distributed environments. Verstichel et al [79] designed a service platform for context-aware collaboration enabling distributed reasoning.…”
Section: B Contextual Awareness In Service Modelsmentioning
confidence: 99%
“…To deal with the challenges of developing context across distributed data collection nodes, a number of authors have utilized agent-based approaches. Tapia et al [78] proposed a distributed multi-agent system approach, where a group of deliberative agents acting as controllers and administrators for the applications and services could better handle contextinformation in dynamic environments and distributed environments. Verstichel et al [79] designed a service platform for context-aware collaboration enabling distributed reasoning.…”
Section: B Contextual Awareness In Service Modelsmentioning
confidence: 99%
“…However, more sophisticated methods such as KDE or dynamic Eigen not always produce more accurate results, especially in noisy images, and due to their consumption of CPU and memory are not suitable for image processing in real time [3], so we have chosen the Gaussian Mixture Model (GMM) method as the basis of this detection phase [16]. This filtering process consists of enclosing the area of mobile contours considered valid between a maximum and a minimum values to ensure that the areas in which motion has been detected by size may correspond with pedestrians or vehicles.…”
Section: Detection Agentmentioning
confidence: 99%