Authors:
Bommersbach, R.;
Hilbring, D.;
Jacques, P.;
Kunz, S.;
Lidstone, M.;
Middleton, S.E.;
Shu, T.;
Veres, G.;
Watson, K.;
Zlatev, Z.
Source:
SANY Sensors Anywhere Integrated Project, p.159 (2009)
Call Number:
FP5-2005-IST-5
URL:
http://sany-ip.eu/publications/3372
Keywords:
SANY; Sensor Web Enablement; Sensor Service Architecture; data fusion; fusion services; uncertainity; best practices
Abstract:
Data fusion and modelling is an effective way to add value to existing datasets of sensor measurements. This can be achieved via aggregation of datasets or inference of new data from relationships and patterns within existing datasets. Generic fusion provisions data fusion in a way that separates configuration and data from the algorithmic processing itself, allowing re-use of algorithms and pre/post-processing between datasets. Re-use of algorithms and techniques lowers the cost of development, configuration and deployment of fusion services.
The SANY project has a high level objective to develop fusion services that allow environmental risk applications to combine available information into comprehensive knowledge about the problem in hand. We have broken down this objective [D3.3.1.3] into several concrete sub-objectives, the combination of which we hope fulfils this high level objective:
Generic algorithm design contributing towards a Generic Fusion and Modelling engine (GFME) concept
Fusion capabilities integrated into the SANY service environment
Propagation of sensor uncertainty information throughout algorithmic processing
Support for ad-hoc and mobile sensor information sources Concrete algorithm implementations as case studies applied to available datasets
SANY fusion services use the OGC service infrastructure, and in particular the SWE standard set for all communication with end-users. Support for such standards allows our processing work to be more easily integrated both now and in the future with other third party services, either hosting new datasets or new processing capabilities.
The metadata provided as part of the SWE standards has allowed us to make progress towards the goal of supporting ad-hoc and mobile sensors through support for an automated 'plug and play' dataset capability. Once processing services can automatically self-configure to the data they are processing, the resulting sensor network processing capability become agile and robust in response to network changes.
Notes:
Copyright University of Southampton, Fraunhofer-Institute IITB, BMT Cordah, Spacebel, 2009. Published under the terms of the SANY contract.
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Acknowledgement: This document is a result of the Integrated Project SANY (Sensors Anywhere, IP 033564) which is supported by funding from the European Union under the Sixth Research Framework Programme.
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