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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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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. |
format | Online Article Text |
id | pubmed-5948597 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT jinxuebo advancesinmultisensorinformationfusiontheoryandapplications2017 AT sunshuli advancesinmultisensorinformationfusiontheoryandapplications2017 AT weihong advancesinmultisensorinformationfusiontheoryandapplications2017 AT yangfengbao advancesinmultisensorinformationfusiontheoryandapplications2017 |