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Advanced Data Fusion System for River Monitoring

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Advances in Human-Computer Interaction

Part of the book series: Research Reports Esprit ((3319,volume 1))

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Abstract

This paper describes the River Quality Monitoring System RQMS, under development which is a part of the ESPRIT project EMS (Environmental Monitoring Systems, project 6757). The partners are Atlas Elektronik, Lyonnaise des Eaux Dumez, Centre National de la Recherche Scientifique (U.R.A. 817 Heudiasyc) and Technische Universität München. This project aims at developing a sufficiently general framework for data fusion and decision support in environmental monitoring, in order to obtain a coherent picture of the environment in terms of its pollution state and its possible evolution [4]. Fusion and interpretation will result in a state description on different levels of abstraction, catering for the varying needs of different end-user groups. At first the RQMS application will be briefly described. The data and the encountered fusion problems will then be presented, introducing the data fusion techniques to be implemented.

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References

  1. Denoeux T. “Application of evidence theory to k-nn pattern classification”, in Proc. of Pattern Recognition in Practice I V, 1994.

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  2. Kohonen T. “Self-Organization and Associative Memory”, Springer-Verlag, Berlin, 1988.

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  3. Shafer G. “A mathematical theory of evidence”, Princenton University Press, Princenton, N.J,. 1976.

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  4. Wittig T. and H.-N. Pham “Data Fusion for Environmental Monitoring” Technical Report of l.May 1993, Atlas Electronik and Lyonnaise des Eaux- Dumez, 1993.

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© 1995 ECSC-EC-EAEC, Brussels-Luxembourg

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Clément, M., Denoeux, T., Trautmann, T. (1995). Advanced Data Fusion System for River Monitoring. In: Pfleger, S., Gonçalves, J., Varghese, K. (eds) Advances in Human-Computer Interaction. Research Reports Esprit, vol 1. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-85220-6_27

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  • DOI: https://doi.org/10.1007/978-3-642-85220-6_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-60145-6

  • Online ISBN: 978-3-642-85220-6

  • eBook Packages: Springer Book Archive

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