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Author Jesus, G. ♦ Oliveira, A. ♦ Azevedo, A. ♦ Casimiro, A.
Sponsorship IEEE
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2015
Language English
Subject Domain (in DDC) Technology ♦ Engineering & allied operations ♦ Applied physics
Subject Keyword Monitoring ♦ Predictive models ♦ Data models ♦ Temperature measurement ♦ Sensor fusion ♦ Temperature sensors ♦ Heuristic algorithms ♦ Sensor Quality ♦ Data Fusion ♦ Outdoor WSNs ♦ Faulty Sensors
Abstract This paper presents an algorithm to improve sensor fusion results in outdoor WSNs using environmental models to redefine periodically which sensors to use and the amount of weight for each particular sensor in the fusion solution. Using daily forecast simulations of the monitored environment dynamics, clusters of sensor nodes sharing data correlation can be defined, for priority sensor selection in a fusion algorithm. The strategy was validated in an operational aquatic sensor network comprised of several sensors scattered over a multiple square kilometers area. It allowed the use of geographically separated nodes with confidence and sometimes even in alternative of closer nodes, unlike most fusion approaches that use quasi-redundant information provided by nearby sensor nodes. This approach represents a major step in the creation of a framework to assess the validity of the monitoring data in WSNs.
Description Author affiliation: Dept. of Hydraulics, LNEC, Lisbon, Portugal (Jesus, G.; Oliveira, A.; Azevedo, A.) || Dept. of Inf., Univ. of Lisbon, Lisbon, Portugal (Casimiro, A.)
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2015-11-01
Publisher Place South Korea
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
e-ISBN 9781479982035
Size (in Bytes) 1.34 MB
Page Count 4
Starting Page 1
Ending Page 4

Source: IEEE Xplore Digital Library