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Intelligent Data Acquisition and Processing Using Wavelet Neural-Networks

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2 Author(s)
Andrea Kulakov ; Computer Science Department, Faculty of Electrical Engineering, University "Sts Cyril and Methodius", Skopje, Macedonia, kulak@etf.ukim.edu.mk ; Danco Davcev

Most of the problems for data management in today's wireless sensor networks were already dealt with during the past thirty years of the artificial neural-networks tradition and that kind of algorithms can be easily implemented to wireless sensor network platforms. These problems include the need for simple parallel distributed computation, possibility for distributed storage, fault-tolerance and in some cases the possibility of auto-classification of sensor readings. We will present data acquisition through hierarchical two-level architecture with algorithms which will use wavelets for initial data-processing of the sensory inputs and neural-networks which use unsupervised learning for categorization of the sensory inputs. They are tested on a data obtained from a set of 4 motes, equipped with seven sensors each.

Published in:

2005 IEEE Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications

Date of Conference:

5-7 Sept. 2005