Systems, methods and devices for public announcements

    公开(公告)号:US09705618B1

    公开(公告)日:2017-07-11

    申请号:US14975074

    申请日:2015-12-18

    申请人: INTEL CORPORATION

    摘要: A public addressing system can identify user preferences including language, volume, and method of delivery to provide improved content in a given geographical area using perceptual computing techniques. The system can also support the use of personal devices including wearables in order to deliver private personalized messages discreetly. For example, one embodiment of a public announcement system gathers and aggregates demographic data of a population in a public place. The public announcement system creates inferences from this data to predict content delivery preferences, such as a sequence of languages or delivery characteristics (e.g., speech rate, content and volume). The delivery preferences can be ranked and then a recommendation for a public announcement provided.

    SYSTEMS, METHODS AND DEVICES FOR PUBLIC ANNOUNCEMENTS

    公开(公告)号:US20170180067A1

    公开(公告)日:2017-06-22

    申请号:US14975074

    申请日:2015-12-18

    申请人: INTEL CORPORATION

    IPC分类号: H04H20/71 H04H60/46 H04H60/70

    摘要: A public addressing system can identify user preferences including language, volume, and method of delivery to provide improved content in a given geographical area using perceptual computing techniques. The system can also support the use of personal devices including wearables in order to deliver private personalized messages discreetly. For example, one embodiment of a public announcement system gathers and aggregates demographic data of a population in a public place. The public announcement system creates inferences from this data to predict content delivery preferences, such as a sequence of languages or delivery characteristics (e.g., speech rate, content and volume). The delivery preferences can be ranked and then a recommendation for a public announcement provided.

    APPARATUS, ARTICLES OF MANUFACTURE, AND METHODS FOR CLUSTERED FEDERATED LEARNING USING CONTEXT DATA

    公开(公告)号:US20220222583A1

    公开(公告)日:2022-07-14

    申请号:US17709237

    申请日:2022-03-30

    申请人: INTEL CORPORATION

    发明人: Rita Wouhaybi

    IPC分类号: G06N20/00 G06K9/62 H04L67/10

    摘要: Methods, apparatus, systems, and articles of manufacture are disclosed for clustered federated learning. An example apparatus includes at least one memory, instructions, and processor circuitry to at least one of instantiate or execute the instructions to retrain a portion of a machine learning model based on context data from a first node, and cause deployment of the portion of the machine learning model to at least one of the first node or a second node to execute a workload, the second node associated with the context data.

    SYSTEMS, APPARATUS, AND METHODS FOR EDGE DATA PRIORITIZATION

    公开(公告)号:US20210328934A1

    公开(公告)日:2021-10-21

    申请号:US17359204

    申请日:2021-06-25

    申请人: Intel Corporation

    IPC分类号: H04L12/851 H04L29/06

    摘要: Methods, apparatus, systems and articles of manufacture are disclosed for edge data prioritization. An example apparatus includes at least one memory, instructions, and processor circuitry to at least one of execute or instantiate the instructions to identify an association of a data packet with a data stream based on one or more data stream parameters included in the data packet corresponding to the data stream, the data packet associated with a first priority, execute a model based on the one or more data stream parameters to generate a model output, determine a second priority of at least one of the data packet or the data stream based on the model output, the model output indicative of an adjustment of the first priority to the second priority, and cause transmission of at least one of the data packet or the data stream based on the second priority.

    Technologies for scene reconstruction

    公开(公告)号:US10154233B2

    公开(公告)日:2018-12-11

    申请号:US14998307

    申请日:2015-12-26

    申请人: Intel Corporation

    摘要: Technologies for scene reconstruction include a compute system to determine a context of at least one image of a scene captured by a camera of the compute system and generate metadata for the at least one image based on the determined context such that the metadata identifies the determined context of the compute system. The compute system further anonymizes the metadata to generate anonymized data that maintains privacy of the compute system and transmits the anonymized data to a cloud server for multi-dimensional reconstruction of the scene.

    SYSTEMS, METHODS AND APPARATUS FOR DATA QUALITY ASSESSMENT AND LEARNING FOR AUTOMATED DEVICES

    公开(公告)号:US20230244191A1

    公开(公告)日:2023-08-03

    申请号:US18148362

    申请日:2022-12-29

    申请人: Intel Corporation

    IPC分类号: G05B13/02

    CPC分类号: G05B13/0265

    摘要: Methods, apparatus, systems and articles of manufacture (e.g., physical storage media) to perform data quality assessment and learning for automated agents are disclosed. An example apparatus disclosed herein includes processor circuitry to calculate a data quality score for data generated by sensors of an autonomous agent. The processor circuitry also generates a reputation score based on the data quality score and the data generated by the sensors. The reputation score indicates a level of confidence in an accuracy of the data quality score. Usage of the data by an action circuitry of the autonomous agent is controlled based on the data quality score and the reputation score. The data quality score and the reputation score are a first value and a second value, respectively.

    SYSTEMS, APPARATUS, ARTICLES OF MANUFACTURE, AND METHODS FOR PROACTIVE DATA ROUTING

    公开(公告)号:US20230016946A1

    公开(公告)日:2023-01-19

    申请号:US17947009

    申请日:2022-09-16

    申请人: Intel Corporation

    IPC分类号: H04L45/00 H04L45/16

    摘要: Methods, apparatus, systems, and articles of manufacture are disclosed for proactive data routing. An example apparatus includes at least one memory, machine-readable instructions, and processor circuitry to execute the machine-readable instructions to at least execute a machine-learning model to output a first data routing path in a network environment based on metadata associated with an event in the network environment. The processor circuitry is further to, after a detection of a change of the first data routing path to a second data routing path, retrain the machine-learning model to output a third data routing path based on the second data routing path. The processor circuitry is additionally to cause transmission of a second message to a first node based on the third data routing path after an identification of the event.