AUTOMATED HANDLING AND MANIPULATION OF PACKAGES AND PACKAGES SPECIALLY ADAPTED THEREFOR

    公开(公告)号:US20240262553A1

    公开(公告)日:2024-08-08

    申请号:US18627049

    申请日:2024-04-04

    CPC classification number: B65B43/28 B65B7/02 B65B57/00

    Abstract: Systems, methods, and apparatuses for handling and manipulating packages in automated or semi-automated fashion and packages adapted for the same. The systems may include package-holding devices, package-manipulating devices, and package-detection components for locating packages or portions thereof in a three-dimensional space. The packages may include features that enable automated or semi-automated handling and manipulation thereof, such as different types of opening/closing mechanisms with different geometric structures that allow for holding, shifting, and manipulating the packages and/or portions thereof with the package-manipulating devices. The packages additionally or alternatively may include mechanical fasteners, magnets, and/or spring-biased opening/closing mechanisms for keeping the packages closed prior to manipulation thereof. Such packages and systems may be used in a logistics network to the increase speed, accuracy, and efficiency of processing packages having, at least in part, a non-fixed geometry.

    SYSTEMS AND METHODS FOR PROVIDING DELIVERY TIME ESTIMATES

    公开(公告)号:US20240249234A1

    公开(公告)日:2024-07-25

    申请号:US18603058

    申请日:2024-03-12

    CPC classification number: G06Q10/0833 G06F16/29 G06Q10/0838

    Abstract: Embodiments are disclosed for determining delivery confidence intervals. An example method for determining a confidence interval includes the following operations. Delivery information is received from one or more sources, wherein the delivery information comprises data associated with at least one predefined location perimeter. The data associated with the at least one predefined location perimeter is normalized. The normalized data is categorized into training data used to perform a deep neural network regression analysis. A predicted delivery confidence interval is determined by constructing a predictive learning model by conducting a regression of the data using deep neural network regression. The predicted delivery confidence interval is stored in a results table in association with the predefined location perimeter. And, upon receiving a request from a visibility management system, accessing the results table to provide predicted delivery windows to consignees.

    Asset return technology
    215.
    发明授权

    公开(公告)号:US12045771B2

    公开(公告)日:2024-07-23

    申请号:US17235127

    申请日:2021-04-20

    Inventor: Juan Perez

    Abstract: One or more identifiers are received based on an electronic scan of computer-readable indicia. The computer-readable indicia being coupled to an asset. The asset is associated with one or more shipping operations. Based at least in part on the one or more identifiers, it is determined that the asset is requested for return. Based at least in part on the one or more identifiers, a shipping label corresponding to a destination location for the asset to be returned to is automatically generated or a location for the asset to be delivered to is automatically changed.

Patent Agency Ranking