Skip to main content
SpringerLink
Log in

Adaptive Vehicle Mode Monitoring Using Embedded Devices with Accelerometers

  • Conference paper
Highlights on Practical Applications of Agents and Multi-Agent Systems

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 156))

  • 734 Accesses

Abstract

Monitoring of specific attributes such as vehicle speed and fuel consumption as well as cargo safety is an important problem for transport domain. This task is performed using specific multiagent monitoring systems. To ensure secure operation of such systems they should have autonomous and adaptive behaviour.

The paper is describing an adaptive agent for vehicle mode monitoring using embedded devices with accelerometers. Data processing algorithm and adaptive functionality are discussed and their evaluation is presented with vehicle standing mode detection as high as true positive rate of 97% using real world data. Optimization of parameters for data processing algorithm is performed as well as suggestions for their application described.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Baker, P., Catterson, V., McArthur, S.: Integrating an agent-based wireless sensor network within an existing multi-agent condition monitoring system. In: 15th International Conference on Intelligent System Applications to Power Systems, ISAP 2009, pp. 1–6 (2009), doi:10.1109/ISAP.2009.5352888

    Google Scholar 

  2. Chowdhary, M., Zhang, Q., Chansarkar, M., Zhang, G.: Systems and methods for detecting a vehicle static condition (2011), http://patents.com/us-7979207.html

  3. Fokum, D.T., Frost, V.S., Depardo, D., Kuehnhausen, M., Oguna, A.N., Searl, L.S., Komp, E., Zeets, M., Deavours, D., Evans, J.B., Minden, G.J.: Experiences from a transportation security sensor network field trial. Tech. rep. (2009)

    Google Scholar 

  4. Gleason, S., Gebre-Egziabher, D.: GNSS applications and methods. In: GNSS Technology and Applications. Artech House (2009), http://books.google.com/books?id=juXAE3SHQroC

  5. Martín, P., Sánchez, M., Álvarez, L., Alonso, V., Bajo, J.: Multi-Agent System For Detecting Elderly People Falls Through Mobile Devices. In: Novais, P., Preuveneers, D., Corchado, J.M. (eds.) ISAmI 2011. AISC, vol. 92, pp. 93–99. Springer, Heidelberg (2011), http://dx.doi.org/10.1007/978-3-642-19937-0_12 , doi:10.1007/978-3-642-19937-0_12

    Chapter  Google Scholar 

  6. Mednis, A., Strazdins, G., Zviedris, R., Kanonirs, G., Selavo, L.: Real time pothole detection using android smartphones with accelerometers. In: DCOSS, pp. 1–6. IEEE (2011)

    Google Scholar 

  7. Rammal, A., Trouilhet, S., Singer, N., Pécatte, J.M.: An adaptive system for home monitoring using a multiagent classification of patterns. Int. J. Telemedicine Appl. 2008, 3:1–3:8 (2008), http://dx.doi.org/10.1155/2008/136054 , doi:10.1155/2008/136054

    Google Scholar 

  8. Sánchez, M., Martín, P., Álvarez, L., Alonso, V., Zato, C., Pedrero, A., Bajo, J.: A New Adaptive Algorithm for Detecting Falls through Mobile Devices. In: Corchado, J.M., Pérez, J.B., Hallenborg, K., Golinska, P., Corchuelo, R. (eds.) Trends in Practical Applications of Agents and Multiagent Systems. AISC, vol. 90, pp. 17–24. Springer, Heidelberg (2011), http://dx.doi.org/10.1007/978-3-642-19931-8_3 , doi:10.1007/978-3-642-19931-83

    Chapter  Google Scholar 

  9. Schwartz, R.: Vehicle state detection (2010), http://ip.com/patapp/US20100204877

  10. Wang, J.H., Gao, Y.: Multi-sensor data fusion for land vehicle attitude estimation using a fuzzy expert system. Data Science Journal 4, 127–139 (2005)

    Article  Google Scholar 

  11. Zviedris, R., Elsts, A., Strazdins, G., Mednis, A., Selavo, L.: LynxNet: Wild Animal Monitoring Using Sensor Networks. In: Marrón, P.J., Voigt, T., Corke, P.I., Mottola, L. (eds.) REALWSN 2010. LNCS, vol. 6511, pp. 170–173. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Digital Signal Processing Laboratory, Institute of Electronics and Computer Science, 14 Dzerbenes Str., Riga, LV, 1006, Latvia

    Artis Mednis & Georgijs Kanonirs

  2. Faculty of Computing, University of Latvia, 19 Raina Blvd., Riga, LV, 1586, Latvia

    Leo Selavo

Authors
  1. Artis Mednis
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Georgijs Kanonirs
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Leo Selavo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Artis Mednis .

Editor information

Editors and Affiliations

  1. Escuela Universitaria de Informática, Universidad Pontificia de Salamanca, Compañía 5, Salamanca, 37002, Spain

    Javier Bajo Pérez

  2. , Facultad de Informática, Universidad Pontificia de Salamanca, Compañía 5, Salamanca, 37002, Spain

    Miguel A. Sánchez

  3. Technologies de Lille, LIFL UMR CNRS 8022, Université des Sciences et, Bâtiment M3 (extension), Villeneuve d’Ascq, 59655, France

    Philippe Mathieu

  4. Faculty of Science, Department of Computing Science, University of Salamanca, Plaza de la Merced S/N, Salamanca, 37008, Spain

    Juan M. Corchado Rodríguez

  5. , LAMIH (UMR CNRS 8530), Universite de Valenciennes, Le Mont Houy, Valenciennes, 59313, France

    Emmanuel Adam

  6. , Departamento de Ingeniería, Ciudad Universitaria de Cantoblanco, Madrid, 28049, Spain

    Alfonso Ortega

  7. Universidad de Salamanca, Plaza de la Merced S/N, Salamanca, 37008, Spain

    María N. Moreno

  8. , Departamento de Informática, University of Castilla-La Mancha, Campus Universitario s/n, Albacete, 02071, Spain

    Elena Navarro

  9. EBTIC, Khalifa University, Abu Dhabi Campus, Abu Dhabi, Utd.Arab.Emir.

    Benjamin Hirsch

  10. , Departamento de Engenharia Informática, Universidade do Porto, Rua Dr. Roberto Frias, s/n, Porto, 4200-465, Portugal

    Henrique Lopes-Cardoso

  11. Universidad Politécnica de Valencia, Camino de Vera s/n, Valencia, 46022, Spain

    Vicente Julián

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Mednis, A., Kanonirs, G., Selavo, L. (2012). Adaptive Vehicle Mode Monitoring Using Embedded Devices with Accelerometers. In: Pérez, J., et al. Highlights on Practical Applications of Agents and Multi-Agent Systems. Advances in Intelligent and Soft Computing, vol 156. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28762-6_28

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-28762-6_28

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28761-9

  • Online ISBN: 978-3-642-28762-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation