We describe an algorithm and experimental work for vehicle detection using sensor node data. Both acoustic and magnetic signals are processed for vehicle detection. We propose a real-time vehicle detection algorithm called the adaptive threshold algorithm (ATA). The algorithm first computes the time-domain energy distribution curve and then slices the energy curve using a threshold updated adaptively by some decision states. Finally, the hard decision results from threshold slicing are passed to a finite-state machine, which makes the final vehicle detection decision. Real-time tests and offline simulations both demonstrate that the proposed algorithm is effective.


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    Title :

    Signal processing of sensor node data for vehicle detection


    Contributors:
    Ding, J. (author) / Cheung, S.-Y. (author) / Tan, C.-W. (author) / Varaiya, P. (author)


    Publication date :

    2004-01-01


    Size :

    399588 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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