A knowledge-oriented meta-framework for integrating sensor network infrastructures
In this paper, we describe a meta-framework that helps guide development of sensor network (SN) cyberinfrastructure in a way that enables emerging sensor infrastructures, including advances in sensor hardware, communication, monitoring applications, and knowledge representation, to interoperate. This framework is guided by the DAST principle. That is, the overall goal of any SN infrastructure is essentially the same: to acquire the right Data from the right Area using the right Sensors at the right Time. In conformity with this principle, our meta-framework integrates SN infrastructures along axes related to the answers to five questions: Why has processing been requested? What are the goals of the processing? Where is it carried out? How is it carried out? And, when will the results be provided? The infrastructure components are integrated by using various data standards and technologies currently available from various SN research groups, and mapping them to an overarching knowledge-based meta-framework. In concrete terms, we show in this paper how four distinct sensor technology projects under development in our research lab are used to fit these five axes of SN infrastructure and how they can be indirectly integrated through the use of software agent-based tools, which embody the meta-framework: an ontology-based decision support system that applies models of SN infrastructure to its evaluation techniques; SN configuration tools that enable network configurations to be exported into common geospatial standards; a transformation engine that converts these SN configurations, along with collected data, into a representation that meshes with our infrastructure models so that they may be used within our decision support environment; and a Virtual SN to handle many of the management and control aspects of SNs.
interoperability sensor webs sensor network integration agent-based software