A Learning-Theory Approach to Sensor Networks

Authors:
Slobodan N. Simic
Affiliations:
University of California, Berkeley
Venue:
IEEE Pervasive Computing
Year:
2003

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Abstract

Supervised learning techniques have been applied in many diverse scenarios. They also might provide an effective approach to sensor network applications. A well-known learning-theory algorithm effectively applies to environmental monitoring, tracking of moving objects and plumes, and localization. This research, although preliminary, offers a beneficial perspective for the sensor network community to consider.