Query processing of streamed XML data
Proceedings of the eleventh international conference on Information and knowledge management
Attribute grammars for scalable query processing on XML streams
The VLDB Journal — The International Journal on Very Large Data Bases
Capturing Personal Health Data from Wearable Sensors
SAINT '08 Proceedings of the 2008 International Symposium on Applications and the Internet
Recognising activities of daily life using hierarchical plans
EuroSSC'07 Proceedings of the 2nd European conference on Smart sensing and context
An effective XML-based sensor data stream processing middleware for ubiquitous service
ICCSA'07 Proceedings of the 2007 international conference on Computational science and its applications - Volume Part III
MaD-WiSe: a distributed stream management system for wireless sensor networks
Software—Practice & Experience
Converting conversation protocols using an XML based differential behavioral model
DEXA'11 Proceedings of the 22nd international conference on Database and expert systems applications - Volume Part II
Enabling knowledge extraction from low level sensor data
DEXA'11 Proceedings of the 22nd international conference on Database and expert systems applications - Volume Part II
Data transformation and query management in personal health sensor networks
Journal of Network and Computer Applications
Optimizing queries for web generated sensor data
ADC '11 Proceedings of the Twenty-Second Australasian Database Conference - Volume 115
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Sensor networks generate a compact form of data in order to efficiently use the available power of the device. Query engines require a richer form of this data in order that users can express meaningful and useful queries. This enrichment of the sensor stream leads to an inevitable increase in the volume of data transported across the network. If this data is enriched and stored in a database on the same server and used only for offline queries, matters such as enrichment time and increased data volumes can usually be managed quite efficiently. However, when there is a requirement to query sensor output in real time, the time required to enrich data and increased data volumes lead to slow query response times. In this research, we present the liveSensor system which offers the benefits of an enriched sensor stream, providing a high level query interface to the user. However, it delays the enrichment of sensor data until after query results have been generated and thus, maintains a high level of performance by processing raw sensor streams.