Sensors 2011, 11(10), 9136-9159; doi:10.3390/s111009136
Article

An Architecture for Performance Optimization in a Collaborative Knowledge-Based Approach for  Wireless Sensor Networks

1 Telecommunications Department, University of Jaen, Alfonso X El Sabio 28, Linares, Jaen 23700, Spain 2 Department of Automatic, University of Alcala, Alcala de Henares, Madrid 28801, Spain
* Author to whom correspondence should be addressed.
Received: 12 August 2011; in revised form: 13 September 2011 / Accepted: 20 September 2011 / Published: 27 September 2011
(This article belongs to the Special Issue Sensorial Systems Applied to Intelligent Spaces)
PDF Full-text Download PDF Full-Text [1218 KB, uploaded 27 September 2011 10:13 CEST]
Abstract: Over the past few years, Intelligent Spaces (ISs) have received the attention of many Wireless Sensor Network researchers. Recently, several studies have been devoted to identify their common capacities and to set up ISs over these networks. However, little attention has been paid to integrating Fuzzy Rule-Based Systems into collaborative Wireless Sensor Networks for the purpose of implementing ISs. This work presents a distributed architecture proposal for collaborative Fuzzy Rule-Based Systems embedded in Wireless Sensor Networks, which has been designed to optimize the implementation of ISs. This architecture includes the following: (a) an optimized design for the inference engine; (b) a visual interface; (c) a module to reduce the redundancy and complexity of the knowledge bases; (d) a module to evaluate the accuracy of the new knowledge base; (e) a module to adapt the format of the rules to the structure used by the inference engine; and (f) a communications protocol. As a real-world application of this architecture and the proposed methodologies, we show an application to the problem of modeling two plagues of the olive tree: prays (olive moth, Prays oleae Bern.) and repilo (caused by the fungus Spilocaea oleagina). The results show that the architecture presented in this paper significantly decreases the consumption of resources (memory, CPU and battery) without a substantial decrease in the accuracy of the inferred values.
Keywords: intelligent spaces; wireless sensor networks; fuzzy rule-based systems

Article Statistics

Load and display the download statistics.

Citations to this Article

Cite This Article

MDPI and ACS Style

Gadeo-Martos, M.A.; Fernandez-Prieto, J.A.; Canada-Bago, J.; Velasco, J.R. An Architecture for Performance Optimization in a Collaborative Knowledge-Based Approach for  Wireless Sensor Networks. Sensors 2011, 11, 9136-9159.

AMA Style

Gadeo-Martos MA, Fernandez-Prieto JA, Canada-Bago J, Velasco JR. An Architecture for Performance Optimization in a Collaborative Knowledge-Based Approach for  Wireless Sensor Networks. Sensors. 2011; 11(10):9136-9159.

Chicago/Turabian Style

Gadeo-Martos, Manuel Angel; Fernandez-Prieto, Jose Angel; Canada-Bago, Joaquin; Velasco, Juan Ramon. 2011. "An Architecture for Performance Optimization in a Collaborative Knowledge-Based Approach for  Wireless Sensor Networks." Sensors 11, no. 10: 9136-9159.

Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert