An Architecture for Performance Optimization in a Collaborative Knowledge-Based Approach for Wireless Sensor Networks
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 Fuz...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2011-09-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/11/10/9136/ |
| _version_ | 1818014581421768704 |
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| author | Juan Ramon Velasco Manuel Angel Gadeo-Martos Joaquin Canada-Bago Jose Angel Fernandez-Prieto |
| author_facet | Juan Ramon Velasco Manuel Angel Gadeo-Martos Joaquin Canada-Bago Jose Angel Fernandez-Prieto |
| author_sort | Juan Ramon Velasco |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-14T06:47:18Z |
| format | Article |
| id | doaj.art-1711a2ed23be47c99782037646d6985c |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-14T06:47:18Z |
| publishDate | 2011-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-1711a2ed23be47c99782037646d6985c2022-12-22T02:07:08ZengMDPI AGSensors1424-82202011-09-0111109136915910.3390/s111009136An Architecture for Performance Optimization in a Collaborative Knowledge-Based Approach for Wireless Sensor NetworksJuan Ramon VelascoManuel Angel Gadeo-MartosJoaquin Canada-BagoJose Angel Fernandez-PrietoOver 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.http://www.mdpi.com/1424-8220/11/10/9136/intelligent spaceswireless sensor networksfuzzy rule-based systems |
| spellingShingle | Juan Ramon Velasco Manuel Angel Gadeo-Martos Joaquin Canada-Bago Jose Angel Fernandez-Prieto An Architecture for Performance Optimization in a Collaborative Knowledge-Based Approach for Wireless Sensor Networks Sensors intelligent spaces wireless sensor networks fuzzy rule-based systems |
| title | An Architecture for Performance Optimization in a Collaborative Knowledge-Based Approach for Wireless Sensor Networks |
| title_full | An Architecture for Performance Optimization in a Collaborative Knowledge-Based Approach for Wireless Sensor Networks |
| title_fullStr | An Architecture for Performance Optimization in a Collaborative Knowledge-Based Approach for Wireless Sensor Networks |
| title_full_unstemmed | An Architecture for Performance Optimization in a Collaborative Knowledge-Based Approach for Wireless Sensor Networks |
| title_short | An Architecture for Performance Optimization in a Collaborative Knowledge-Based Approach for Wireless Sensor Networks |
| title_sort | architecture for performance optimization in a collaborative knowledge based approach for wireless sensor networks |
| topic | intelligent spaces wireless sensor networks fuzzy rule-based systems |
| url | http://www.mdpi.com/1424-8220/11/10/9136/ |
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