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Advances in Multi-Sensor Information Fusion: Theory and Applications 2017

The information fusion technique can integrate a large amount of data and knowledge representing the same real-world object and obtain a consistent, accurate, and useful representation of that object. The data may be independent or redundant, and can be obtained by different sensors at the same time...

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Detalles Bibliográficos
Autores principales: Jin, Xue-Bo, Sun, Shuli, Wei, Hong, Yang, Feng-Bao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5948597/
https://www.ncbi.nlm.nih.gov/pubmed/29641434
http://dx.doi.org/10.3390/s18041162
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author Jin, Xue-Bo
Sun, Shuli
Wei, Hong
Yang, Feng-Bao
author_facet Jin, Xue-Bo
Sun, Shuli
Wei, Hong
Yang, Feng-Bao
author_sort Jin, Xue-Bo
collection PubMed
description The information fusion technique can integrate a large amount of data and knowledge representing the same real-world object and obtain a consistent, accurate, and useful representation of that object. The data may be independent or redundant, and can be obtained by different sensors at the same time or at different times. A suitable combination of investigative methods can substantially increase the profit of information in comparison with that from a single sensor. Multi-sensor information fusion has been a key issue in sensor research since the 1970s, and it has been applied in many fields. For example, manufacturing and process control industries can generate a lot of data, which have real, actionable business value. The fusion of these data can greatly improve productivity through digitization. The goal of this special issue is to report innovative ideas and solutions for multi-sensor information fusion in the emerging applications era, focusing on development, adoption, and applications.
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spelling pubmed-59485972018-05-17 Advances in Multi-Sensor Information Fusion: Theory and Applications 2017 Jin, Xue-Bo Sun, Shuli Wei, Hong Yang, Feng-Bao Sensors (Basel) Editorial The information fusion technique can integrate a large amount of data and knowledge representing the same real-world object and obtain a consistent, accurate, and useful representation of that object. The data may be independent or redundant, and can be obtained by different sensors at the same time or at different times. A suitable combination of investigative methods can substantially increase the profit of information in comparison with that from a single sensor. Multi-sensor information fusion has been a key issue in sensor research since the 1970s, and it has been applied in many fields. For example, manufacturing and process control industries can generate a lot of data, which have real, actionable business value. The fusion of these data can greatly improve productivity through digitization. The goal of this special issue is to report innovative ideas and solutions for multi-sensor information fusion in the emerging applications era, focusing on development, adoption, and applications. MDPI 2018-04-11 /pmc/articles/PMC5948597/ /pubmed/29641434 http://dx.doi.org/10.3390/s18041162 Text en © 2018 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 (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Editorial
Jin, Xue-Bo
Sun, Shuli
Wei, Hong
Yang, Feng-Bao
Advances in Multi-Sensor Information Fusion: Theory and Applications 2017
title Advances in Multi-Sensor Information Fusion: Theory and Applications 2017
title_full Advances in Multi-Sensor Information Fusion: Theory and Applications 2017
title_fullStr Advances in Multi-Sensor Information Fusion: Theory and Applications 2017
title_full_unstemmed Advances in Multi-Sensor Information Fusion: Theory and Applications 2017
title_short Advances in Multi-Sensor Information Fusion: Theory and Applications 2017
title_sort advances in multi-sensor information fusion: theory and applications 2017
topic Editorial
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5948597/
https://www.ncbi.nlm.nih.gov/pubmed/29641434
http://dx.doi.org/10.3390/s18041162
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