RFID MOTION DETECTION FOR DENSE RFID TAG ENVIRONMENTS

    公开(公告)号:US20210342560A1

    公开(公告)日:2021-11-04

    申请号:US17093418

    申请日:2020-11-09

    Abstract: In one embodiment, an apparatus comprises processing circuitry to: receive wireless signal data corresponding to an RFID tag, wherein the wireless signal data comprises signal strength data and signal phase data corresponding to wireless signals transmitted by the RFID tag and received by an RFID reader; generate decomposed signal strength data based on a seasonal decomposition of the signal strength data; generate a frequency-phase curve based on the signal phase data; extract a set of signal strength features based on the decomposed signal strength data; extract a set of signal phase features based on the frequency-phase curve; and detect a motion state of the RFID tag using a machine learning classifier, wherein the machine learning classifier is trained to detect the motion state based on the set of signal strength features and the set of signal phase features.

    Asynchronous representation of alternate reality characters

    公开(公告)号:US10319145B2

    公开(公告)日:2019-06-11

    申请号:US13997773

    申请日:2013-03-14

    Abstract: Technologies for representing alternate reality characters in a real-world environment include receiving sensor data from sensors of a sensor network of a home location of an alternate reality character, determining available response to the stimuli represented by the sensor data, and determining an activity of the alternate reality character for a time period based on the available responses. The technologies may also include generating a video of the alternate reality character performing the determined activity superimposed on an image map of a real-world environment of the home location during the time period. Users may view the video in real time or during a time period subsequent to the time period represented in the video. Additionally, the alternate reality character may be transferred to remote computing devices in some embodiments.

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