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Fuzzy-Probabilistic Approach for Dense Wireless Sensor Network

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Intelligent Systems Design and Applications (ISDA 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1351))

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Abstract

The deformations of the scalar field of an appropriate physical variable can indicate significant events such as the presence of a vehicle, the occurrence of a firing or the movement of soldiers in a region. It is considered the scenario of continuous monitoring of a scalar field by a Sensor Network in applications that require very limited nodes in power, processing, communication and storage capacities. In this scenario, typical in some military applications in a hostile environment that requires discretion of the presence of the nodes, the extension of the useful life of the network via energy saving becomes even more critical. The need for discretion implies reducing the physical dimensions of the node and thus also the size of the battery. The paper proposes a decentralized low processing strategy to suppress sensing and transmission of messages and evaluates the trade off between transmitted messages reduction versus accuracy of scalar field reconstruction. Your results can be used to tune applications.

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Notes

  1. 1.

    http://www.ulb.ac.be/di/labo/code/PCAgExpe.zip.

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Author information

Authors and Affiliations

  1. Universidade Estadual do Ceará - UECE, Fortaleza, CE, 60714-903, Brazil

    Flávio R. S. Nunes, Crislânio de S. Macêdo, Jéferson do N. Soares, Haniel G. Cavalcante, Marcelo Q. L. Brilhante & José E. B. Maia

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  1. Flávio R. S. Nunes
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  2. Crislânio de S. Macêdo
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  3. Jéferson do N. Soares
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  4. Haniel G. Cavalcante
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  5. Marcelo Q. L. Brilhante
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  6. José E. B. Maia
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Editor information

Editors and Affiliations

  1. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Ajith Abraham

  2. Department of Computer Science, Università degli Studi di Milano, Milan, Milano, Italy

    Vincenzo Piuri

  3. Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Niketa Gandhi

  4. Campus Centre de Créteil, Université Paris-Est Créteil, Créteil, France

    Patrick Siarry

  5. Department of Construction Management and Real Estate, Vilnius Gediminas Technical University, Vilnius, Lithuania

    Arturas Kaklauskas

  6. School of Engineering, Instituto Superior de Engenharia do Porto, Porto, Portugal

    Ana Madureira

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Nunes, F.R.S., de S. Macêdo, C., do N. Soares, J., Cavalcante, H.G., Brilhante, M.Q.L., Maia, J.E.B. (2021). Fuzzy-Probabilistic Approach for Dense Wireless Sensor Network. In: Abraham, A., Piuri, V., Gandhi, N., Siarry, P., Kaklauskas, A., Madureira, A. (eds) Intelligent Systems Design and Applications. ISDA 2020. Advances in Intelligent Systems and Computing, vol 1351. Springer, Cham. https://doi.org/10.1007/978-3-030-71187-0_94

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