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An Integrated GIS-Expert System Framework for Live Hazard Monitoring and Detection

In the context of hazard monitoring, using sensor web technology to monitor and detect hazardous conditions in near-real-time can result in large amounts of spatial data that can be used to drive analysis at an instrumented site. These data can be used for decision making and problem solving, howeve...

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Autores principales: McCarthy, James D., Graniero, Phil A., Rozic, Steven M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3927503/
https://www.ncbi.nlm.nih.gov/pubmed/27879737
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author McCarthy, James D.
Graniero, Phil A.
Rozic, Steven M.
author_facet McCarthy, James D.
Graniero, Phil A.
Rozic, Steven M.
author_sort McCarthy, James D.
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description In the context of hazard monitoring, using sensor web technology to monitor and detect hazardous conditions in near-real-time can result in large amounts of spatial data that can be used to drive analysis at an instrumented site. These data can be used for decision making and problem solving, however as with any analysis problem the success of analyzing hazard potential is governed by many factors such as: the quality of the sensor data used as input; the meaning that can be derived from those data; the reliability of the model used to describe the problem; the strength of the analysis methods; and the ability to effectively communicate the end results of the analysis. For decision makers to make use of sensor web data these issues must be dealt with to some degree. The work described in this paper addresses all of these areas by showing how raw sensor data can be automatically transformed into a representation which matches a predefined model of the problem context. This model can be understood by analysis software that leverages rule-based logic and inference techniques to reason with, and draw conclusions about, spatial data. These tools are integrated with a well known Geographic Information System (GIS) and existing geospatial and sensor web infrastructure standards, providing expert users with the tools needed to thoroughly explore a problem site and investigate hazards in any domain.
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spelling pubmed-39275032014-02-18 An Integrated GIS-Expert System Framework for Live Hazard Monitoring and Detection McCarthy, James D. Graniero, Phil A. Rozic, Steven M. Sensors (Basel) Full Research Paper In the context of hazard monitoring, using sensor web technology to monitor and detect hazardous conditions in near-real-time can result in large amounts of spatial data that can be used to drive analysis at an instrumented site. These data can be used for decision making and problem solving, however as with any analysis problem the success of analyzing hazard potential is governed by many factors such as: the quality of the sensor data used as input; the meaning that can be derived from those data; the reliability of the model used to describe the problem; the strength of the analysis methods; and the ability to effectively communicate the end results of the analysis. For decision makers to make use of sensor web data these issues must be dealt with to some degree. The work described in this paper addresses all of these areas by showing how raw sensor data can be automatically transformed into a representation which matches a predefined model of the problem context. This model can be understood by analysis software that leverages rule-based logic and inference techniques to reason with, and draw conclusions about, spatial data. These tools are integrated with a well known Geographic Information System (GIS) and existing geospatial and sensor web infrastructure standards, providing expert users with the tools needed to thoroughly explore a problem site and investigate hazards in any domain. Molecular Diversity Preservation International (MDPI) 2008-02-08 /pmc/articles/PMC3927503/ /pubmed/27879737 Text en © 2008 by MDPI Reproduction is permitted for noncommercial purposes.
spellingShingle Full Research Paper
McCarthy, James D.
Graniero, Phil A.
Rozic, Steven M.
An Integrated GIS-Expert System Framework for Live Hazard Monitoring and Detection
title An Integrated GIS-Expert System Framework for Live Hazard Monitoring and Detection
title_full An Integrated GIS-Expert System Framework for Live Hazard Monitoring and Detection
title_fullStr An Integrated GIS-Expert System Framework for Live Hazard Monitoring and Detection
title_full_unstemmed An Integrated GIS-Expert System Framework for Live Hazard Monitoring and Detection
title_short An Integrated GIS-Expert System Framework for Live Hazard Monitoring and Detection
title_sort integrated gis-expert system framework for live hazard monitoring and detection
topic Full Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3927503/
https://www.ncbi.nlm.nih.gov/pubmed/27879737
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