SYSTEM AND METHOD FOR A SECURITY CHECKPOINT USING RADIO SIGNALS

    公开(公告)号:US20180308331A1

    公开(公告)日:2018-10-25

    申请号:US15492008

    申请日:2017-04-20

    CPC classification number: G08B13/22 G01S5/0284 G07C9/00111 G08B27/005

    Abstract: A security device for monitoring the radio frequency signals generated by mobile phones and similar mobile computing and communication devices. The security device employs an antennae array and computer process that are configured to detect and provide a “fingerprint” for a mobile device based on the unique identifiers contained with the radio and other wireless signals utilized by such mobile device. The “fingerprint” that is obtained can be used to keep track of mobile devices as those devices enter and leave the area of the security device. Moreover, the security device can provide an alert when any new, foreign, or otherwise unrecognized device is within range of the security device and share “fingerprints” and alerts with other security devices in its network.

    SYSTEM AND METHOD FOR A SECURITY CHECKPOINT USING RADIO SIGNALS

    公开(公告)号:US20190035243A1

    公开(公告)日:2019-01-31

    申请号:US16151654

    申请日:2018-10-04

    Abstract: A security device for monitoring the radio frequency signals generated by mobile phones and similar mobile computing and communication devices. The security device employs an antennae array and computer process that are configured to detect and provide a “fingerprint” for a mobile device based on the unique identifiers contained with the radio and other wireless signals utilized by such mobile device. The “fingerprint” that is obtained can be used to keep track of mobile devices as those devices enter and leave the area of the security device. Moreover, the security device can provide an alert when any new, foreign, or otherwise unrecognized device is within range of the security device and share “fingerprints” and alerts with other security devices in its network.

    System and method for a security checkpoint using radio signals

    公开(公告)号:US10109166B1

    公开(公告)日:2018-10-23

    申请号:US15492008

    申请日:2017-04-20

    CPC classification number: G08B13/22 G01S5/0284 G07C9/00111 G08B27/005

    Abstract: A security device for monitoring the radio frequency signals generated by mobile phones and similar mobile computing and communication devices. The security device employs an antennae array and computer process that are configured to detect and provide a “fingerprint” for a mobile device based on the unique identifiers contained with the radio and other wireless signals utilized by such mobile device. The “fingerprint” that is obtained can be used to keep track of mobile devices as those devices enter and leave the area of the security device. Moreover, the security device can provide an alert when any new, foreign, or otherwise unrecognized device is within range of the security device and share “fingerprints” and alerts with other security devices in its network.

    DISTRIBUTED DEEP LEARNING USING A DISTRIBUTED DEEP NEURAL NETWORK

    公开(公告)号:US20180307979A1

    公开(公告)日:2018-10-25

    申请号:US15491950

    申请日:2017-04-19

    CPC classification number: G06N3/08 G06N5/04 H04N7/183

    Abstract: Apparatus and associated methods relate to training a neural network on a first host system, sending the neural network to a second host system, training the neural network by the second host system based on data private to the second host system, and employing the neural network to filter events sent to the first host system. In an illustrative example, the first host system may be a server having a central repository including trained neural networks and historical data, and the second host system may be a remote server having a data source private to the remote server. The private remote data source may be a camera. In some examples, events may be filtered as a function of a prediction of error in the neural network. Various examples may advantageously provide remote intelligent filtering. For example, remote data may remain private while adaptively filtering events to the central server.

    Automatic threat detection based on video frame delta information in compressed video streams

    公开(公告)号:US11074791B2

    公开(公告)日:2021-07-27

    申请号:US16529907

    申请日:2019-08-02

    Abstract: Apparatus and associated methods relate to identifying objects of interest and detecting motion to automatically detect a security threat as a function of video frame delta information received from a video encoder. In an illustrative example, the video encoder may be an H.264 encoder onboard a video camera. A cloud server may receive the video frame delta information in a compressed video stream from the camera. Threats may be detected by the cloud server processing the video frame delta information in the compressed video stream, without decompression, to identify objects and detect motion. The cloud server may employ artificial intelligence techniques to enhance threat detection by the cloud server. Various examples may advantageously provide increased capacity of a computer tasked with detecting security breaches, due to the significant reduction in the amount of data to be processed, relative to threat detection based on processing uncompressed video streams.

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