Wallet with Accommodating Pocket for Anti-Lost Tag

    公开(公告)号:US20240398079A1

    公开(公告)日:2024-12-05

    申请号:US18204960

    申请日:2023-06-02

    Applicant: Yusheng Liang

    Inventor: Yusheng Liang

    Abstract: A wallet includes a wallet body and an accommodating pocket which is coupled on the wallet body for accommodating the anti-lost tag. The accommodating pocket has a pocket opening, the wallet includes a switch control mechanism which is disposed at the pocket opening to allow the pocket opening to be switched between a first state to allow the anti-lost tag to enter and exit the accommodating pocket and a second state in which the anti-lost tag is blocked from entering and exiting the accommodating pocket through the pocket opening.

    System, software application and method of advanced interaction with transportable containers

    公开(公告)号:US11956696B2

    公开(公告)日:2024-04-09

    申请号:US18310948

    申请日:2023-05-02

    Inventor: Massimo Tonelli

    CPC classification number: H04W4/029 A45C13/18 A45C13/42 H04W4/80

    Abstract: A system of advanced interaction with transportable containers, such as suitcases, trolleys, trunks, backpacks, crates, or the like, includes



    transportable containers, each of which is equipped with a respective transponder which carries at least one corresponding identification code. Each transponder allow polling by a contactless information transmission technology, such as RFID or NFC, for communication at least of the corresponding identification code.




    The system also includes a remote processing unit, suitable for the management of a central data bank, which contains information related to the transportable containers and to their association with the corresponding identification codes.

    System, software application and method of advanced interaction with transportable containers

    公开(公告)号:US11665506B2

    公开(公告)日:2023-05-30

    申请号:US16971401

    申请日:2018-03-02

    Inventor: Massimo Tonelli

    CPC classification number: H04W4/029 A45C13/18 A45C13/42 H04W4/80

    Abstract: A system of advanced interaction with transportable containers, such as suitcases, trolleys, trunks, backpacks, crates, or the like, includes transportable containers, each of which is equipped with a respective transponder which carries at least one corresponding identification code. Each transponder allows polling by a contactless information transmission technology, such as RFID or NFC, for communication at least of the corresponding identification code.
    The system also includes a remote processing unit, suitable for the management of a central data bank, which contains information related to the transportable containers and to their association with the corresponding identification codes.

    Securement for zippered luggage
    8.
    发明授权

    公开(公告)号:US11350706B2

    公开(公告)日:2022-06-07

    申请号:US16305271

    申请日:2017-05-31

    Inventor: Ross Park

    Abstract: A securement for zippered luggage, including a housing to substantially cover a pair of sliders of a zipper of the luggage and to prevent movement of the sliders along a tape of the zipper, the housing being formed of a first part which receives the sliders and a second part which engages the first part to substantially encapsulate and prevent movement of the sliders, wherein the first and second parts are secured together in the inoperative securing condition by an element which requires breaking or permanent deformation to permit displacement of the second part to allow movement of the sliders.

    METHOD AND SYSTEM FOR ACTIVITY CLASSIFICATION

    公开(公告)号:US20210161266A1

    公开(公告)日:2021-06-03

    申请号:US17173978

    申请日:2021-02-11

    Applicant: WRNCH INC.

    Abstract: An activity classifier system and method that classifies human activities using 2D skeleton data. The system includes a skeleton preprocessor that transforms the 2D skeleton data into transformed skeleton data, the transformed skeleton data comprising scaled, relative joint positions and relative joint velocities. The system also includes a gesture classifier comprising a first recurrent neural network that receives the transformed skeleton data, and is trained to identify the most probable of a plurality of gestures. The system also has an action classifier comprising a second recurrent neural network that receives information from the first recurrent neural networks and is trained to identify the most probable of a plurality of actions.

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