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MACRo 2015

Proceedings of the 5th International Conference on Recent Achievements in Mechatronics, Automation, Computer Sciences and Robotics

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Open Access
Online
ISSN
2247-0948
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Sensor Fusion for Intrusion Detection With Sensor Networks

Bence Koszteczky
  • Department of Computer Science and System Technologies, Faculty of Information Technology, University of Pannonia, Veszprém
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/ Gyula Simon
  • Department of Computer Science and System Technologies, Faculty of Information Technology, University of Pannonia, Veszprém
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  • De Gruyter OnlineGoogle Scholar
Published Online: 2015-05-09 | DOI: https://doi.org/10.1515/macro-2015-0027

Abstract

A sensor fusion algorithm is proposed, which can be used to fuse measurements from a distributed sensor network, containing inexpensive, easily deployable and energy efficient magnetic sensor devices. The sensor measurements are collected and transferred to a central base station, where the sensor fusion is performed, using the sensor location. The algorithm provides location, direction, and speed information about the detected vehicles. The paper describes the sensor technology and the fusion method, and the performance of the system is illustrated by real test measurements.

Keywords : sensor network; magnetometer; sensor fusion; vehicle detection

References

  • [1] Mimbela, L.E.Y., and Klein, L.A., “Summary of vehicle detection and surveillance technologies used in intelligent transportation systems.” Federal Highway Administration’s (FHWA) Intelligent Transportation Systems Joint 2000.Google Scholar

  • [2] Freescale Semiconductor, “Xtrinsic MAG3110 Three-Axis, Digital Magnetometer Data Sheet”. Online: http://www.freescale.com/files/sensors/doc/data_sheet/MAG3110.pdfGoogle Scholar

  • [3] B. Koszteczky, G. Simon, „Magnetic-based vehicle detection with sensor networks“, in Proc. 2013 IEEE International Instrumentation and Measurement Technology Conference, Minneapolis, USA, 2013, pp. 265-270Google Scholar

About the article

Received: 2015-01-12

Revised: 2015-02-09

Published Online: 2015-05-09

Published in Print: 2015-03-01


Citation Information: MACRo 2015, ISSN (Online) 2247-0948, DOI: https://doi.org/10.1515/macro-2015-0027.

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© 2015. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0

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