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Distributed Service-Based Approach for Sensor Data Fusion in IoT Environments

The Internet of Things (IoT) enables the communication among smart objects promoting the pervasive presence around us of a variety of things or objects that are able to interact and cooperate jointly to reach common goals. IoT objects can obtain data from their context, such as the home, office, ind...

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Detalles Bibliográficos
Autores principales: Rodríguez-Valenzuela, Sandra, Holgado-Terriza, Juan A., Gutiérrez-Guerrero, José M., Muros-Cobos, Jesús L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4239875/
https://www.ncbi.nlm.nih.gov/pubmed/25320907
http://dx.doi.org/10.3390/s141019200
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author Rodríguez-Valenzuela, Sandra
Holgado-Terriza, Juan A.
Gutiérrez-Guerrero, José M.
Muros-Cobos, Jesús L.
author_facet Rodríguez-Valenzuela, Sandra
Holgado-Terriza, Juan A.
Gutiérrez-Guerrero, José M.
Muros-Cobos, Jesús L.
author_sort Rodríguez-Valenzuela, Sandra
collection PubMed
description The Internet of Things (IoT) enables the communication among smart objects promoting the pervasive presence around us of a variety of things or objects that are able to interact and cooperate jointly to reach common goals. IoT objects can obtain data from their context, such as the home, office, industry or body. These data can be combined to obtain new and more complex information applying data fusion processes. However, to apply data fusion algorithms in IoT environments, the full system must deal with distributed nodes, decentralized communication and support scalability and nodes dynamicity, among others restrictions. In this paper, a novel method to manage data acquisition and fusion based on a distributed service composition model is presented, improving the data treatment in IoT pervasive environments.
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spelling pubmed-42398752014-11-21 Distributed Service-Based Approach for Sensor Data Fusion in IoT Environments Rodríguez-Valenzuela, Sandra Holgado-Terriza, Juan A. Gutiérrez-Guerrero, José M. Muros-Cobos, Jesús L. Sensors (Basel) Article The Internet of Things (IoT) enables the communication among smart objects promoting the pervasive presence around us of a variety of things or objects that are able to interact and cooperate jointly to reach common goals. IoT objects can obtain data from their context, such as the home, office, industry or body. These data can be combined to obtain new and more complex information applying data fusion processes. However, to apply data fusion algorithms in IoT environments, the full system must deal with distributed nodes, decentralized communication and support scalability and nodes dynamicity, among others restrictions. In this paper, a novel method to manage data acquisition and fusion based on a distributed service composition model is presented, improving the data treatment in IoT pervasive environments. MDPI 2014-10-15 /pmc/articles/PMC4239875/ /pubmed/25320907 http://dx.doi.org/10.3390/s141019200 Text en © 2014 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Rodríguez-Valenzuela, Sandra
Holgado-Terriza, Juan A.
Gutiérrez-Guerrero, José M.
Muros-Cobos, Jesús L.
Distributed Service-Based Approach for Sensor Data Fusion in IoT Environments
title Distributed Service-Based Approach for Sensor Data Fusion in IoT Environments
title_full Distributed Service-Based Approach for Sensor Data Fusion in IoT Environments
title_fullStr Distributed Service-Based Approach for Sensor Data Fusion in IoT Environments
title_full_unstemmed Distributed Service-Based Approach for Sensor Data Fusion in IoT Environments
title_short Distributed Service-Based Approach for Sensor Data Fusion in IoT Environments
title_sort distributed service-based approach for sensor data fusion in iot environments
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4239875/
https://www.ncbi.nlm.nih.gov/pubmed/25320907
http://dx.doi.org/10.3390/s141019200
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