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Real-time GIS data model and sensor web service platform for environmental data management

BACKGROUND: Effective environmental data management is meaningful for human health. In the past, environmental data management involved developing a specific environmental data management system, but this method often lacks real-time data retrieving and sharing/interoperating capability. With the de...

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Autores principales: Gong, Jianya, Geng, Jing, Chen, Zeqiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4298078/
https://www.ncbi.nlm.nih.gov/pubmed/25572659
http://dx.doi.org/10.1186/1476-072X-14-2
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author Gong, Jianya
Geng, Jing
Chen, Zeqiang
author_facet Gong, Jianya
Geng, Jing
Chen, Zeqiang
author_sort Gong, Jianya
collection PubMed
description BACKGROUND: Effective environmental data management is meaningful for human health. In the past, environmental data management involved developing a specific environmental data management system, but this method often lacks real-time data retrieving and sharing/interoperating capability. With the development of information technology, a Geospatial Service Web method is proposed that can be employed for environmental data management. The purpose of this study is to determine a method to realize environmental data management under the Geospatial Service Web framework. METHODS: A real-time GIS (Geographic Information System) data model and a Sensor Web service platform to realize environmental data management under the Geospatial Service Web framework are proposed in this study. The real-time GIS data model manages real-time data. The Sensor Web service platform is applied to support the realization of the real-time GIS data model based on the Sensor Web technologies. RESULTS: To support the realization of the proposed real-time GIS data model, a Sensor Web service platform is implemented. Real-time environmental data, such as meteorological data, air quality data, soil moisture data, soil temperature data, and landslide data, are managed in the Sensor Web service platform. In addition, two use cases of real-time air quality monitoring and real-time soil moisture monitoring based on the real-time GIS data model in the Sensor Web service platform are realized and demonstrated. The total time efficiency of the two experiments is 3.7 s and 9.2 s. CONCLUSIONS: The experimental results show that the method integrating real-time GIS data model and Sensor Web Service Platform is an effective way to manage environmental data under the Geospatial Service Web framework.
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spelling pubmed-42980782015-01-20 Real-time GIS data model and sensor web service platform for environmental data management Gong, Jianya Geng, Jing Chen, Zeqiang Int J Health Geogr Methodology BACKGROUND: Effective environmental data management is meaningful for human health. In the past, environmental data management involved developing a specific environmental data management system, but this method often lacks real-time data retrieving and sharing/interoperating capability. With the development of information technology, a Geospatial Service Web method is proposed that can be employed for environmental data management. The purpose of this study is to determine a method to realize environmental data management under the Geospatial Service Web framework. METHODS: A real-time GIS (Geographic Information System) data model and a Sensor Web service platform to realize environmental data management under the Geospatial Service Web framework are proposed in this study. The real-time GIS data model manages real-time data. The Sensor Web service platform is applied to support the realization of the real-time GIS data model based on the Sensor Web technologies. RESULTS: To support the realization of the proposed real-time GIS data model, a Sensor Web service platform is implemented. Real-time environmental data, such as meteorological data, air quality data, soil moisture data, soil temperature data, and landslide data, are managed in the Sensor Web service platform. In addition, two use cases of real-time air quality monitoring and real-time soil moisture monitoring based on the real-time GIS data model in the Sensor Web service platform are realized and demonstrated. The total time efficiency of the two experiments is 3.7 s and 9.2 s. CONCLUSIONS: The experimental results show that the method integrating real-time GIS data model and Sensor Web Service Platform is an effective way to manage environmental data under the Geospatial Service Web framework. BioMed Central 2015-01-09 /pmc/articles/PMC4298078/ /pubmed/25572659 http://dx.doi.org/10.1186/1476-072X-14-2 Text en © Gong et al.; licensee BioMed Central. 2015 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Methodology
Gong, Jianya
Geng, Jing
Chen, Zeqiang
Real-time GIS data model and sensor web service platform for environmental data management
title Real-time GIS data model and sensor web service platform for environmental data management
title_full Real-time GIS data model and sensor web service platform for environmental data management
title_fullStr Real-time GIS data model and sensor web service platform for environmental data management
title_full_unstemmed Real-time GIS data model and sensor web service platform for environmental data management
title_short Real-time GIS data model and sensor web service platform for environmental data management
title_sort real-time gis data model and sensor web service platform for environmental data management
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4298078/
https://www.ncbi.nlm.nih.gov/pubmed/25572659
http://dx.doi.org/10.1186/1476-072X-14-2
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