Deploying a Wireless Sensor Network on an Active Volcano
IEEE Internet Computing
Data Management in the Worldwide Sensor Web
IEEE Pervasive Computing
SenseWeb: An Infrastructure for Shared Sensing
IEEE MultiMedia
IEEE Internet Computing
Hydrological Sensor Web for the South Esk Catchment in the Tasmanian state of Australia
ESCIENCE '08 Proceedings of the 2008 Fourth IEEE International Conference on eScience
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Infrastructure for Data Processing in Large-Scale Interconnected Sensor Networks
MDM '07 Proceedings of the 2007 International Conference on Mobile Data Management
Five challenges for the Semantic Sensor Web
Semantic Web
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This paper presents an ontology-based approach for data quality inference on streaming observation data originating from large-scale sensor networks. We evaluate this approach in the context of an existing river basin monitoring program called the Intelligent River®. Our current methods for data quality evaluation are compared with the ontology-based inference methods described in this paper. We present an architecture that incorporates semantic inference into a publish/subscribe messaging middleware, allowing data quality inference to occur on real-time data streams. Our preliminary benchmark results indicate delays of 100ms for basic data quality checks based on an existing semantic web software framework. We demonstrate how these results can be maintained under increasing sensor data traffic rates by allowing inference software agents to work in parallel. These results indicate that data quality inference using the semantic sensor network paradigm is viable solution for data intensive, large-scale sensor networks.