Demonstrating principal component aggregation for distributed spatial pattern recognition

Authors:
Yann-Aël Le Borgne;Ann Nowé;Kris Steenhaut;Etro Lab;Gianluca Bontempi
Affiliations:
Vrije Universiteit Brussel, Brussels, Belgium;Vrije Universiteit Brussel, Brussels, Belgium;Vrije Universiteit Brussel, Brussels, Belgium;Vrije Universiteit Brussel, Brussels, Belgium;Université Libre de Bruxelles, Brussels, Belgium
Venue:
Proceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks
Year:
2010

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Abstract

The Principal Component Aggregation has recently been proposed as a versatile distributed information extraction technique for sensor networks [3]. This demonstration illustrates its use for a network-level pattern recognition task. Four different patterns, or events, may be sensed by light measurements of a network of 27 nodes. The sens measurements are fused on the fly along a routing tree up to the base station, where the monitored pattern is recognized by a prediction algorithm.