TECHNICAL SUPPORT SERVICE LOCATION RECOMMENDATION USING MACHINE LEARNING

    公开(公告)号:US20240095750A1

    公开(公告)日:2024-03-21

    申请号:US17946223

    申请日:2022-09-16

    IPC分类号: G06Q30/00 G06Q10/00

    CPC分类号: G06Q30/016 G06Q10/20

    摘要: A method comprises receiving work order data, wherein the work order data identifies at least one technical support issue requiring resolution. The work order data is analyzed using one or more machine learning algorithms. The method further comprises predicting, based at least in part on the analyzing, whether the at least one technical support issue will be resolved at one or more respective service locations of a plurality of service locations. Based at least in part on the predicting, a recommendation to respond to the at least one technical support issue at a given service location of the plurality of service locations is generated.

    AUTOMATICALLY PREDICTING DEVICE RECYCLING OPPORTUNITIES USING ARTIFICIAL INTELLIGENCE TECHNIQUES

    公开(公告)号:US20240232724A9

    公开(公告)日:2024-07-11

    申请号:US17969793

    申请日:2022-10-20

    IPC分类号: G06N20/20

    CPC分类号: G06N20/20

    摘要: Methods, apparatus, and processor-readable storage media for automatically predicting device recycling opportunities using artificial intelligence techniques are provided herein. An example computer-implemented method includes obtaining data associated with one or more devices; determining end of life-related information for the one or more devices by processing at least a portion of the obtained data; predicting at least one device recycling opportunity for at least one of the one or more devices by processing at least a portion of the determined end of life-related information using one or more artificial intelligence techniques; and performing one or more automated actions based at least in part on the at least one predicted device recycling opportunity.

    GENERATING AND PROCESSING DIGITAL ASSET INFORMATION CHAINS USING MACHINE LEARNING TECHNIQUES

    公开(公告)号:US20240193138A1

    公开(公告)日:2024-06-13

    申请号:US18078380

    申请日:2022-12-09

    IPC分类号: G06F16/215 G06F16/23 H04L9/00

    摘要: Methods, apparatus, and processor-readable storage media for generating and processing digital asset information chains using machine learning techniques are provided herein. An example computer-implemented method includes obtaining data, from one or more data sources, pertaining to one or more events involving a digital asset; generating a digital asset information chain associated with the digital asset by processing at least a portion of the obtained data using at least one cryptographic function and linking that at least a portion of the obtained data in accordance with at least one temporal parameter; performing anomaly detection by processing at least a portion of the digital asset information chain associated with the digital asset using one or more machine learning techniques; and performing one or more automated actions based at least in part on one or more of the digital asset information chain and results from the anomaly detection.

    AUTOMATICALLY PREDICTING DEVICE RECYCLING OPPORTUNITIES USING ARTIFICIAL INTELLIGENCE TECHNIQUES

    公开(公告)号:US20240135262A1

    公开(公告)日:2024-04-25

    申请号:US17969793

    申请日:2022-10-19

    IPC分类号: G06N20/20

    CPC分类号: G06N20/20

    摘要: Methods, apparatus, and processor-readable storage media for automatically predicting device recycling opportunities using artificial intelligence techniques are provided herein. An example computer-implemented method includes obtaining data associated with one or more devices; determining end of life-related information for the one or more devices by processing at least a portion of the obtained data; predicting at least one device recycling opportunity for at least one of the one or more devices by processing at least a portion of the determined end of life-related information using one or more artificial intelligence techniques; and performing one or more automated actions based at least in part on the at least one predicted device recycling opportunity.

    GENERATING AND PROCESSING PERSONAL INFORMATION CHAINS USING MACHINE LEARNING TECHNIQUES

    公开(公告)号:US20230342488A1

    公开(公告)日:2023-10-26

    申请号:US17726657

    申请日:2022-04-22

    IPC分类号: G06F21/62 G06F21/60

    CPC分类号: G06F21/6245 G06F21/602

    摘要: Methods, apparatus, and processor-readable storage media for generating and processing personal information chains using machine learning techniques are provided herein. An example computer-implemented method includes processing data, from one or more data sources, pertaining to one or more events involving an individual; generating a personal information chain associated with the individual by processing at least a portion of the processed data using at least one cryptographic function and linking that at least a portion of the processed data in accordance with at least one temporal parameter; performing anomaly detection by processing at least a portion of the personal information chain associated with the individual using one or more machine learning techniques; and performing one or more automated actions based at least in part on one or more of the personal information chain and results from the anomaly detection.

    COMPONENT REPLACEMENT FRAMEWORK
    7.
    发明公开

    公开(公告)号:US20240095683A1

    公开(公告)日:2024-03-21

    申请号:US17946212

    申请日:2022-09-16

    IPC分类号: G06Q10/00 G06Q10/08

    摘要: A method comprises collecting operational data corresponding to one or more components of at least one device and analyzing the operational data against one or more thresholds for component replacement. In the method, one or more alerts for at least one user are generated responsive to meeting the one or more thresholds. One or more communications are received from the at least one user in response to the one or more alerts. One or more replacement components for the one or more components are dispatched to the at least one user based at least in part on the received one or more communications. In analyzing the operational data, one or more databases are accessed to identify a support entitlement of the at least one user for the at least one device, and at least one threshold of the one or more thresholds corresponding to the identified support entitlement is identified.

    RESOURCE PREDICTION FOR MICROSERVICES
    9.
    发明公开

    公开(公告)号:US20240012667A1

    公开(公告)日:2024-01-11

    申请号:US17861553

    申请日:2022-07-11

    IPC分类号: G06F9/455 G06F9/50

    摘要: A method comprises receiving a request to predict an amount of at least one resource for at least one hosting instance of one or more microservices. Using one or more machine learning models, the amount of the at least one resource is predicted in response to the request. The at least one hosting instance is generated based, at least in part, on the predicted amount. In some embodiments, the at least one resource comprises, for example, a memory and/or a CPU, and the amount of the at least one resource comprises a size of the memory and/or a number of CPU core units.

    Microservices mediation layer for canonical message alignment in complex microservices environments

    公开(公告)号:US11327819B1

    公开(公告)日:2022-05-10

    申请号:US17246859

    申请日:2021-05-03

    IPC分类号: G06F9/54

    摘要: An apparatus comprises at least one processing device comprising a processor coupled to a memory, with the processing device being configured to receive in a microservices mediation layer a plurality of event notifications for respective internal events generated within an application, to extract information comprising at least a subset of an entity type, a key and an action from each of the event notifications, to issue at least one corresponding request to one or more microservices based at least in part on the extracted information, to prepare at least one message based at least in part on one or more responses received from the one or more microservices, and to publish the at least one message to one or more message consumers. The microservices mediation layer is illustratively configured to permit seamless switching between synchronous and asynchronous canonical message formats.