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Information fusion for wireless sensor networks: Methods, models, and classifications

Nakamura, Eduardo ; Loureiro, Antonio ; Frery, Alejandro

ACM computing surveys, 2007-09, Vol.39 (3), p.9-es [Periódico revisado por pares]

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Título:
Information fusion for wireless sensor networks: Methods, models, and classifications
Autor: Nakamura, Eduardo ; Loureiro, Antonio ; Frery, Alejandro
Assuntos: Applied sciences ; architectures and models ; Computer science; control theory; systems ; Computer systems and distributed systems. User interface ; data aggregation ; data fusion ; Exact sciences and technology ; Information fusion ; Software ; wireless sensor networks
É parte de: ACM computing surveys, 2007-09, Vol.39 (3), p.9-es
Notas: ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
Descrição: Wireless sensor networks produce a large amount of data that needs to be processed, delivered, and assessed according to the application objectives. The way these data are manipulated by the sensor nodes is a fundamental issue. Information fusion arises as a response to process data gathered by sensor nodes and benefits from their processing capability. By exploiting the synergy among the available data, information fusion techniques can reduce the amount of data traffic, filter noisy measurements, and make predictions and inferences about a monitored entity. In this work, we survey the current state-of-the-art of information fusion by presenting the known methods, algorithms, architectures, and models of information fusion, and discuss their applicability in the context of wireless sensor networks.
Editor: New York, NY: ACM
Idioma: Inglês

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