D-FLER - A Distributed Fuzzy Logic Engine for Rule-Based Wireless Sensor Networks

Mihai Marin Perianu; Paul J.M. Havinga

doi:10.1007/978-3-540-76772-5_7

D-FLER - A Distributed Fuzzy Logic Engine for Rule-Based Wireless Sensor Networks

Mihai Marin Perianu
, Paul J.M. Havinga

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic › peer-review

177 Downloads (Pure)

Abstract

We propose D-FLER, a distributed, general-purpose reasoning engine for WSN. D-FLER uses fuzzy logic for fusing individual and neighborhood observations, in order to produce a more accurate and reliable result. Thorough simulation, we evaluate D-FLER in a fire-detection scenario, using both fire and non-fire input data. D-FLER achieves better detection times, while reducing the false alarm rate. In addition, we implement D-FLER on real sensor nodes and analyze the memory overhead, the numerical accuracy and the execution time.

Original language	Undefined
Title of host publication	Ubiquitous Computing Systems
Place of Publication	Germany
Publisher	Springer
Pages	86-101
Number of pages	16
ISBN (Print)	978-3-540-76771-8
DOIs	https://doi.org/10.1007/978-3-540-76772-5_7
Publication status	Published - Nov 2007
Event	Ubiquitous Computing Systems - Tokyo, Japan Duration: 25 Nov 2007 → 28 Nov 2007

Publication series

Name
Publisher	Springer Verlag
Number	7
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	Ubiquitous Computing Systems
Period	25/11/07 → 28/11/07
Other	25-28 Nov 2007

Keywords

CAES-PS: Pervasive Systems
METIS-245954
IR-62119
EWI-11749

Access to Document

10.1007/978-3-540-76772-5_7

D-FLER

Cite this

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abstract = "We propose D-FLER, a distributed, general-purpose reasoning engine for WSN. D-FLER uses fuzzy logic for fusing individual and neighborhood observations, in order to produce a more accurate and reliable result. Thorough simulation, we evaluate D-FLER in a fire-detection scenario, using both fire and non-fire input data. D-FLER achieves better detection times, while reducing the false alarm rate. In addition, we implement D-FLER on real sensor nodes and analyze the memory overhead, the numerical accuracy and the execution time.",

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AU - Havinga, Paul J.M.

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AB - We propose D-FLER, a distributed, general-purpose reasoning engine for WSN. D-FLER uses fuzzy logic for fusing individual and neighborhood observations, in order to produce a more accurate and reliable result. Thorough simulation, we evaluate D-FLER in a fire-detection scenario, using both fire and non-fire input data. D-FLER achieves better detection times, while reducing the false alarm rate. In addition, we implement D-FLER on real sensor nodes and analyze the memory overhead, the numerical accuracy and the execution time.

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