Fuzzy decision fusion for single target classification in wireless sensor networks

Sercan Gók, Adnan Yazici, Ahmet Coşar, Roy George

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

With the advances in technology, low cost and low footprint sensors are being used more and more commonly. Especially for military applications wireless sensor networks (WSN) have become an attractive solution as they have great use for avoiding deadly danger in combat. For military applications, classification of a target in a battlefield plays an important role. A wireless sensor node has the ability to sense the raw signal data in battlefield, extract the feature vectors from sensed signal and produce a local classification result using a classifier. Although only one sensor is sufficient to produce a classification result, decision fusion of the local classification results for a number of sensor nodes improves classification accuracy. In our approach, we propose fuzzy decision fusion methods for single target classification in a WSN environment. Our proposed fusion algorithms use fuzzy logic for selecting the most appropriate sensor nodes to be used for classification. Our algorithms provide better classification accuracy over some popular decision fusion algorithms.

Original languageEnglish
Title of host publication2010 IEEE World Congress on Computational Intelligence, WCCI 2010
DOIs
Publication statusPublished - 2010
Event2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - Barcelona, Spain
Duration: Jul 18 2010Jul 23 2010

Publication series

Name2010 IEEE World Congress on Computational Intelligence, WCCI 2010

Other

Other2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010
Country/TerritorySpain
CityBarcelona
Period7/18/107/23/10

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computational Theory and Mathematics

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