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A Survey of Data Semantization in Internet of Things
With the development of Internet of Things (IoT), more and more sensors, actuators and mobile devices have been deployed into our daily lives. The result is that tremendous data are produced and it is urgent to dig out hidden information behind these volumous data. However, IoT data generated by mul...
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/PMC5795333/ https://www.ncbi.nlm.nih.gov/pubmed/29361772 http://dx.doi.org/10.3390/s18010313 |
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author | Shi, Feifei Li, Qingjuan Zhu, Tao Ning, Huansheng |
author_facet | Shi, Feifei Li, Qingjuan Zhu, Tao Ning, Huansheng |
author_sort | Shi, Feifei |
collection | PubMed |
description | With the development of Internet of Things (IoT), more and more sensors, actuators and mobile devices have been deployed into our daily lives. The result is that tremendous data are produced and it is urgent to dig out hidden information behind these volumous data. However, IoT data generated by multi-modal sensors or devices show great differences in formats, domains and types, which poses challenges for machines to process and understand. Therefore, adding semantics to Internet of Things becomes an overwhelming tendency. This paper provides a systematic review of data semantization in IoT, including its backgrounds, processing flows, prevalent techniques, applications, existing challenges and open issues. It surveys development status of adding semantics to IoT data, mainly referring to sensor data and points out current issues and challenges that are worth further study. |
format | Online Article Text |
id | pubmed-5795333 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-57953332018-02-13 A Survey of Data Semantization in Internet of Things Shi, Feifei Li, Qingjuan Zhu, Tao Ning, Huansheng Sensors (Basel) Article With the development of Internet of Things (IoT), more and more sensors, actuators and mobile devices have been deployed into our daily lives. The result is that tremendous data are produced and it is urgent to dig out hidden information behind these volumous data. However, IoT data generated by multi-modal sensors or devices show great differences in formats, domains and types, which poses challenges for machines to process and understand. Therefore, adding semantics to Internet of Things becomes an overwhelming tendency. This paper provides a systematic review of data semantization in IoT, including its backgrounds, processing flows, prevalent techniques, applications, existing challenges and open issues. It surveys development status of adding semantics to IoT data, mainly referring to sensor data and points out current issues and challenges that are worth further study. MDPI 2018-01-22 /pmc/articles/PMC5795333/ /pubmed/29361772 http://dx.doi.org/10.3390/s18010313 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 | Article Shi, Feifei Li, Qingjuan Zhu, Tao Ning, Huansheng A Survey of Data Semantization in Internet of Things |
title | A Survey of Data Semantization in Internet of Things |
title_full | A Survey of Data Semantization in Internet of Things |
title_fullStr | A Survey of Data Semantization in Internet of Things |
title_full_unstemmed | A Survey of Data Semantization in Internet of Things |
title_short | A Survey of Data Semantization in Internet of Things |
title_sort | survey of data semantization in internet of things |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5795333/ https://www.ncbi.nlm.nih.gov/pubmed/29361772 http://dx.doi.org/10.3390/s18010313 |
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