• DocumentCode
    519267
  • Title

    Robust vehicle detection algorithm with magnetic sensor

  • Author

    Kanathantip, Pisit ; Kumwilaisak, Wuttipong ; Chinrungrueng, Jatuporn

  • Author_Institution
    Electron. & Telecommun. Dept., King Mongkut´´s Univ. of Technol., Bangkok, Thailand
  • fYear
    2010
  • fDate
    19-21 May 2010
  • Firstpage
    1060
  • Lastpage
    1064
  • Abstract
    This paper presents a robust real-time vehicle detection algorithm. The proposed algorithm is performed on wireless magnetic sensor node to instrument roadways. The sensor node measures the Earth´s magnetic field disturbed by vehicle body moving within the neighborhood. This is performed in real-time and can be useful for detecting the vehicles consisting of 88.9% yield of motorcycles (small vehicles) and 99.3% yield of road vehicles (cars, pickups, vans, trucks, buses and SUVs) under various places and environment. Especially, the temperature effect resulting in performance can be resolved by the automatic adaptive baseline method. In addition, the algorithm can detect both the passing and the stationary vehicles. Moreover, the automatic check process is combined for checking the errors; the double detection due to low speed and the instant baseline level changing.
  • Keywords
    magnetic sensors; object detection; road traffic; road vehicles; automatic adaptive baseline method; automatic check process; earths magnetic field; instant baseline level; instrument roadways; motorcycles; road traffic; robust road vehicle detection algorithm; wireless magnetic sensor node; Earth; Instruments; Magnetic field measurement; Magnetic sensors; Motorcycles; Road vehicles; Robustness; Temperature; Vehicle detection; Wireless sensor networks; Vehicle Detection; Wireless Magnetic Sensor;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical Engineering/Electronics Computer Telecommunications and Information Technology (ECTI-CON), 2010 International Conference on
  • Conference_Location
    Chaing Mai
  • Print_ISBN
    978-1-4244-5606-2
  • Electronic_ISBN
    978-1-4244-5607-9
  • Type

    conf

  • Filename
    5491638