Information Fusion in Monitoring Applications using the Category Model
In many application areas similar monitoring tasks can be identified. The fundamental monitoring tasks are reported based on a technical domain analysis within different application areas. Common to most of the monitoring tasks are the recognition, surveillance, and control of objects, states and/or processes within a specific area.
Important for performing those basic tasks is the collection and processing of data coming from different sources. A typical characteristic of data acquired from different sources is the different type of data and the varying level of information. The process of combining data concerning a specific goal stated by a monitoring task is often called Data Fusion.
Here the more general term Information Fusionwill be introduced to describe the process of condensing data on varying level of information. The process of Information Fusion is based on an approach for a goal-oriented handling of information, the Category Model, which serves as the representational framework for the fundamental monitoring tasks.
Several results of this work have been performed within a cooperation with the ESPRIT-Project 5345 DIMUS (Data Integration in Multisensor Systems).
KeywordsCategory Model Information Fusion Monitoring Application Monitoring Task Logical Object
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- 1.Hansen, C., Henderson, T.C., Shilcrat, E., “Logical sensor specification”, Proceedings of the 3rd International Conference of Robot Vision and Sensor Systems, pp.321–326, 1983Google Scholar
- 2.Wechsler, H., “Computational vision”, Computer Science and Scientific Computing, pp.406–421, Academic Press, 1990Google Scholar
- 3.Miles, J.A.H., Faulkner, H.C., “Knowledge-based techniques for tactical situation assessment”, Conference Proceedings MILCOMP 88, pp.313–318, 1988Google Scholar
- 4.Waltz, E.L., Buede, D.M., “Data fusion and decision support for command and control”, IEEE Transactions on SMC-16, no.6, pp.865–879, Nov./Dec. 1986Google Scholar
- 5.Wilson, G.B., “Some aspects on data fusion” in Advances in Command, Control & Communication Systems, editor Harris C.J., pp.321–338, P.Pere-grinus, London, 1987Google Scholar
- 6.Azarewicz, J., Fala, G., Heithecker C., “Template-based multi-agent plan recognition for tactical situation assessment”, Proceedings of the 5th conference on Artificial Intelligence applications, pp. 248–254, Miami, March 1989Google Scholar
- 7.EUROCONTROL, “MADAP-System Description”, Issue 02, EURO-CONTROL Brussels, Belgium, 1986Google Scholar
- 8.BFS, “Flight Track Monitoring System FTMS — Functional System Description”, Bundesanstalt fuer Flugsicherung, Frankfurt a.M., 1984Google Scholar
- 10.Luo, R.C., Lin, M.-N., “Hierarchical robot multi-sensor data fusion system”, NATO ASI series, vol.58, pp.67–86,1988Google Scholar
- 11.Lenat, D.B., Clarkson, A., Kiremidjian, G., “An expert system for indication & warning analysis”, IJCAI-83, pp.259–262,1983Google Scholar
- 12.ESPRIT Project 5345 “DIMUS—Data integration in multi-sensor systems”, “1st Design Specification Report”, DIMUS/12/dv/0001–01/b/Pl, 12.09.91Google Scholar
- 13.Luo, R.C., Kay, M.G., “Multisensor integration and fusion in intelligent systems”, IEEE Transactions on SMC-19, pp.901–931,1989Google Scholar