An integrated GIS-expert system framework for live hazard monitoring and detection

Abstract

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. © 2008 by MDPI.