Motion is a critical indicator of human presence and activities. Recent developments in the field of indoor motion detection have the potential to enhance various aspects of our daily experiences like intrusion detection and sleep monitoring. Existing indoor motion detection solutions either are obstructive to use or fail to provide adequate coverage. To overcome these shortages, a noninvasive and cost-effective motion detection system (MoSense) is proposed for periodically detecting motions by exploring channel response in the commodity WiFi devices. The central idea is that signals in a ``silence'' environment serve well as a ``golden'' benchmark for recognizing motions that lead to signal fluctuations. A prototype of MoSense is realized and evaluated in real environments. By comparing MoSense with another state-of-the-art method, i.e., FIMD, we have shown that MoSense outperforms FIMD in terms of computational complexity, detection accuracy and false alarm rate. Considering that MoSense is compatible with existing WiFi infrastructure, it constitutes a low-cost yet promising solution for motion detection.


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    Title :

    "Silence Is Golden": Exploring Ambient Signals for Detecting Motions in a Real-Time Manner


    Contributors:
    Gu, Yu (author) / Zhan, Jinhai (author) / Ren, Fuji (author) / Wang, Xiaoyan (author)


    Publication date :

    2017-09-01


    Size :

    655867 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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