Nano Science and Technology Institute
Nanotech 2005 Vol. 3
Nanotech 2005 Vol. 3
Technical Proceedings of the 2005 NSTI Nanotechnology Conference and Trade Show, Volume 3
 
Chapter 7: Smart Sensors and Systems
 

Intelligent Data Aggregation in Sensor Networks Using Artificial Neural-Networks Algorithms

Authors:A. Kulakov and D. Davcev
Affilation:Ss. Cyril and Methodius University, MK
Pages:427 - 430
Keywords:sensor networks, neural networks, intellignet data aggregation, dimensionality reduction, data robustness, self-organization of input data, auto-classification of sensor readings
Abstract:Most of the current in-network data processing algorithms are modified regression techniques like multidimensional data series analysis. In our opinion, some of the algorithms well developed within the artificial neural-networks tradition, for over 40 years, can be easily adopted to wireless sensor network platforms and will meet the requirements for sensor networks like: simple parallel distributed computation, distributed storage, data robustness and auto-classification of sensor readings. As a result of the dimensionality reduction obtained simply from the outputs of the neural-networks clustering algorithms, lower communication costs and energy savings can also be obtained. In this paper we will present three possible implementations of the ART and FuzzyART neural-networks algorithms, which are unsupervised learning methods for categorization of the sensory inputs. They are tested on a data obtained from a set of several Smart-It motes, each equipped with several sensors of different types. Results from simulations of purposefully faulty sensors show the data robustness of these architectures.
Intelligent Data Aggregation in Sensor Networks Using Artificial Neural-Networks AlgorithmsView PDF of paper
ISBN:0-9767985-2-2
Pages:786
Hardcopy:$109.95
 
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