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Data alignment for data fusion in wireless multimedia sensor networks based on M2M
JOSE ROBERTO PEREZ CRUZ
SAUL EDUARDO POMARES HERNANDEZ
JOSE ENRIQUE MUÑOZ DE COTE FLORES LUNA
Acceso Abierto
Atribución-NoComercial-SinDerivadas
Data alignment
Data fusion
In-network processing
Wireless sensor networks
Advances in MEMS and CMOS technologies have motivated the development of low cost/power sensors and wireless multimedia sensor networks (WMSN). The WMSNs were created to ubiquitously harvest multimedia content. Such networks have allowed researchers and engineers to glimpse at new Machine-to-Machine (M2M) Systems, such as remote monitoring of biosignals for telemedicine networks. These systems require the acquisition of a large number of data streams that are simultaneously generated by multiple distributed devices. This paradigm of data generation and transmission is known as event-streaming. In order to be useful to the application, the collected data requires a preprocessing called data fusion, which entails the temporal alignment task of multimedia data. A practical way to perform this task is in a centralized manner, assuming that the network nodes only function as collector entities. However, by following this scheme, a considerable amount of redundant information is transmitted to the central entity. To decrease such redundancy, data fusion must be performed in a collaborative way. In this paper, we propose a collaborative data alignment approach for event-streaming. Our approach identifies temporal relationships by translating temporal dependencies based on a timeline to causal dependencies of the media involved.
KSII Transaction on Internet and Information Systems
2012
Artículo
Inglés
Estudiantes
Investigadores
Público en general
Perez-Cruz, J.R., et al., (2012). Data alignment for data fusion in wireless multimedia sensor networks based on M2M, KSII Transaction on Internet and Information Systems, Vol. 6 (1): 229-240
CIENCIA DE LOS ORDENADORES
Versión aceptada
acceptedVersion - Versión aceptada
Aparece en las colecciones: Artículos de Ciencias Computacionales

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