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Convegno Nazionale Sensori

CNS 2018: Sensors pp 371–376Cite as

IEEE 21451-001 Signal Treatment Applied to Smart Transducers

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Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 539))

Abstract

Control and monitoring systems base their decisions on the information provided by transducers. These signals must be acquired, processed and transmitted. There is an exchange between sensor signal processing and data rate, more signal processing inside the transducer implies lower data rate over the networks. This paper presents the standard IEEE 21451-001 whose main purpose is to extract knowledge of transducer signals that can be shared with others to increase system reliability, infer shapes, normal/abnormal states and to provide a normalized building structure for extracting knowledge. This standard extracts information directly from sampling based on a more complete structure. The standard is described highlighting the purpose and the main algorithms.

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References

  1. Di Lecce, V.: Towards intelligent sensor evolution: a holonic based system architecture. In: SENSORCOMM 2012: The Sixth International Conference on Sensor Technologies and Applications (2012)

    Google Scholar 

  2. Carratù, M., Pietrosanto, A., Sommella, P., Paciello, V.: Suspension velocity prediction from acceleration measurement for two wheels vehicle. In: I2MTC 2017 (2017). https://doi.org/10.1109/i2mtc.2017.7969943

  3. Angrisani, L., Capriglione, D., Cerro, G., Ferrigno, L., Miele, G.: On employing a Savitzky-Golay filtering stage to improve performance of spectrum sensing in CR applications concerning VDSA approach. Metrol. Meas. Syst. 23(2), 295–308. https://doi.org/10.1515/mms-2016-0019

    Article  Google Scholar 

  4. Capriglione, D., Carratù, M., Liguori, C., Paciello, V., Sommella, P.: A Soft stroke sensor for motorcycle rear suspension (2017). https://doi.org/10.1016/j.measurement.2017.04.011

    Article  Google Scholar 

  5. Betta, G., Capriglione, D., Cerro, G., Ferrigno, L., Miele, G.: The effectiveness of Savitzky-Golay smoothing method for spectrum sensing in cognitive radios. In: 2015 XVIII AISEM Annual Conference, Trento, 2015, pp. 1–4. https://doi.org/10.1109/aisem.2015.7066819

  6. Sivakumar, K.: Internet of Things (IoT). Cisco Systems. http://www.ethernetsummit.com/English/Collaterals/Proceedings/2014/20140430_1D_Sivakumar.pdf (2014)

  7. Edge Computing-Ryan LaMothe Research Scientist Pacific Northwest National Laboratory, Jan 2013

    Google Scholar 

  8. Lu, Y.M., Do, M.N.: A theory for sampling signals from a union of subspaces. IEEE Trans. Signal Process. 56(6), 2334–2345 (2008)

    Article  MathSciNet  Google Scholar 

  9. Monte, G.: Sensor signal preprocessing techniques for analysis and prediction. In: 34th Annual Conference of IEEE. Industrial Electronics, 2008. IECON 2008, pp 1788–1793. ISBN 978-114244-1766-7

    Google Scholar 

  10. Monte, G., Liu, Z., Abate, F., Paciello, V., Pietrosanto, A., Huang, V.: Normalizing transducer signals: An overview of a proposed standard. In: Proceedings IEEE International Instrumentation Measurement Technology Conference (I2MTC), Montevideo, Uruguay, May 2014, pp. 614–619

    Google Scholar 

  11. Monte, G., Abate, F., Huang, V, Paciello, V., Pietrosanto, A.: Real time transducer signal features extraction: a standard approach. In: 2015 IEEE 13th International Conference Industrial Informatics (INDIN). http://dx.doi.org/10.1109/INDIN.2015.7281740

  12. Monte, G., et al.: A novel time-domain signal processing algorithm for real time ventricular fibrillation detection. J. Phys.: Conf. Ser. 332, 012015 (2011). https://doi.org/10.1088/1742-6596/332/1/012015

    Google Scholar 

  13. Abate, F., Paciello, V., Pietrosanto, A., Guia, S.S., Santo, A.E.: Period measurement with an ARM microcontroller. In: Proceedings of the 2015 18th AISEM Annual Conference, AISEM 2015, pp. 1–4. ISBN 9781479985913. https://doi.org/10.1109/aisem.2015.7066785

  14. Abate, F., Paciello, V., Pietrosanto, A., Monte, G.: Preliminary analysis of a real time segmentation and labeling algorithm. In: 2015 IEEE Workshop on Environmental, Energy, and Structural Monitoring Systems, EESMS 2015—Proceedings, pp. 215–219 (2015) ISBN 9781479982141. https://doi.org/10.1109/eesms.2015.7175880

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Author information

Authors and Affiliations

  1. Department of Industrial Engineering, University of Salerno, Salerno, Italy

    F. Abate & M. Carratù

  2. Department of Electromechanical Engineering, University of Beira Interior, Covilhã, Portugal

    A. Espírito-Santo

  3. Georgia Institute of Technology, 791 Atlantic Drive NW, Atlanta, GA, 30332, USA

    V. Huang

  4. Facultad Regional del Neuquén, Universidad Tecnológica Nacional, Buenos Aires, Argentina

    G. Monte

  5. DIEI University of Cassino and Southern Lazio, Cassino, Italy

    V. Paciello

Authors
  1. F. Abate
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  2. M. Carratù
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  3. A. Espírito-Santo
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  4. V. Huang
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  5. G. Monte
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  6. V. Paciello
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Corresponding author

Correspondence to V. Paciello .

Editor information

Editors and Affiliations

  1. University of Catania, Catania, Italy

    Bruno Andò

  2. IFAC-CNR, Sesto Fiorentino, Florence, Italy

    Francesco Baldini

  3. University of Rome Tor Vergata, Rome, Italy

    Corrado Di Natale

  4. Department of Information Engineering (DII), University of Brescia, Brescia, Italy

    Vittorio Ferrari

  5. University of Catania, Catania, Italy

    Vincenzo Marletta

  6. Department of Chemistry, University of Florence, Sesto Fiorentino, Florence, Italy

    Giovanna Marrazza

  7. University of Palermo, Palermo, Italy

    Valeria Militello

  8. University of Padova, Padua, Italy

    Giorgia Miolo

  9. Sapienza University of Rome, Rome, Italy

    Marco Rossi

  10. Università Politecnica delle Marche (UNIVPM), Ancona, Italy

    Lorenzo Scalise

  11. IMM-CNR, Lecce, Italy

    Pietro Siciliano

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Abate, F., Carratù, M., Espírito-Santo, A., Huang, V., Monte, G., Paciello, V. (2019). IEEE 21451-001 Signal Treatment Applied to Smart Transducers. In: Andò, B., et al. Sensors. CNS 2018. Lecture Notes in Electrical Engineering, vol 539. Springer, Cham. https://doi.org/10.1007/978-3-030-04324-7_46

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  • DOI: https://doi.org/10.1007/978-3-030-04324-7_46

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-04323-0

  • Online ISBN: 978-3-030-04324-7

  • eBook Packages: EngineeringEngineering (R0)

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