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    TECHNOLOGIES FOR ADAPTIVE COLLABORATIVE OPTIMIZATION OF INTERNET-OF-THINGS SYSTEMS
    2.
    发明申请
    TECHNOLOGIES FOR ADAPTIVE COLLABORATIVE OPTIMIZATION OF INTERNET-OF-THINGS SYSTEMS 审中-公开

    公开(公告)号：US20200034205A1

    公开(公告)日：2020-01-30

    申请号：US16291235

    申请日：2019-03-04

    申请人： Intel Corporation

    发明人： Damian Kelly ,  Keith A. Ellis

    IPC分类号： G06F9/50

    摘要： Technologies for collaborative optimization include multiple Internet-of-Things (IoT) devices in communication over a network with an optimization server. Each IoT device selects an optimization strategy based on device context and user preferences. The optimization strategy may be full-local, full-global, or hybrid. Each IoT device receives raw device data from one or more sensors/actuators. If the full-local strategy is selected, the IoT device generates processed data based on the raw device data, generates optimization results based on the processed data, and generates device controls/settings for the sensors/actuators based on the optimization results. If the full-global strategy is selected, the optimization server performs those operations. If the hybrid strategy is selected, the IoT device generates the processed data and the device controls/settings, and the optimization server generates the optimization results. The optimization server may provision plugins to the IoT devices to perform those operations. Other embodiments are described and claimed.

    TECHNOLOGIES FOR ADAPTIVE COLLABORATIVE OPTIMIZATION OF INTERNET-OF-THINGS SYSTEMS
    3.
    发明申请
    TECHNOLOGIES FOR ADAPTIVE COLLABORATIVE OPTIMIZATION OF INTERNET-OF-THINGS SYSTEMS 审中-公开

    公开(公告)号：US20180181088A1

    公开(公告)日：2018-06-28

    申请号：US15392855

    申请日：2016-12-28

    申请人： Intel Corporation

    发明人： Damian Kelly ,  Keith A. Ellis

    IPC分类号： G05B13/04 ,  G05B13/02

    CPC分类号： G06F9/5072

    摘要： Technologies for collaborative optimization include multiple Internet-of-Things (IoT) devices in communication over a network with an optimization server. Each IoT device selects an optimization strategy based on device context and user preferences. The optimization strategy may be full-local, full-global, or hybrid. Each IoT device receives raw device data from one or more sensors/actuators. If the full-local strategy is selected, the IoT device generates processed data based on the raw device data, generates optimization results based on the processed data, and generates device controls/settings for the sensors/actuators based on the optimization results. If the full-global strategy is selected, the optimization server performs those operations. If the hybrid strategy is selected, the IoT device generates the processed data and the device controls/settings, and the optimization server generates the optimization results. The optimization server may provision plugins to the IoT devices to perform those operations. Other embodiments are described and claimed.

    MONITORING ELECTRICAL SUBSTATION NETWORKS
    5.
    发明申请
    MONITORING ELECTRICAL SUBSTATION NETWORKS 审中-公开

    公开(公告)号：US20190296547A1

    公开(公告)日：2019-09-26

    申请号：US16307369

    申请日：2016-07-01

    申请人： Intel Corporation

    发明人： Damian Kelly ,  David Boundy

    IPC分类号： H02J3/00 ,  G06F16/2455 ,  G06N20/00 ,  G06F17/50

    摘要： Systems and a method for forecasting data at noninstrumented substations from data collected at instrumented substations is provided. An example method includes determining a cluster id for a noninstrumented substation, creating a model from data for instrumented substations having the cluster id, and forecasting the data for the noninstrumented station from the model.

    Technologies for adaptive collaborative optimization of internet-of-things systems
    6.
    发明授权
    Technologies for adaptive collaborative optimization of internet-of-things systems 有权

    公开(公告)号：US10223169B2

    公开(公告)日：2019-03-05

    申请号：US15392855

    申请日：2016-12-28

    申请人： Intel Corporation

    发明人： Damian Kelly ,  Keith A. Ellis

    IPC分类号： G05B13/04 ,  G05B13/02 ,  G06F9/50

    摘要： Technologies for collaborative optimization include multiple Internet-of-Things (IoT) devices in communication over a network with an optimization server. Each IoT device selects an optimization strategy based on device context and user preferences. The optimization strategy may be full-local, full-global, or hybrid. Each IoT device receives raw device data from one or more sensors/actuators. If the full-local strategy is selected, the IoT device generates processed data based on the raw device data, generates optimization results based on the processed data, and generates device controls/settings for the sensors/actuators based on the optimization results. If the full-global strategy is selected, the optimization server performs those operations. If the hybrid strategy is selected, the IoT device generates the processed data and the device controls/settings, and the optimization server generates the optimization results. The optimization server may provision plugins to the IoT devices to perform those operations. Other embodiments are described and claimed.

    Sensor data search platform
    8.
    发明授权
    Sensor data search platform 有权

    公开(公告)号：US11665239B2

    公开(公告)日：2023-05-30

    申请号：US17113849

    申请日：2020-12-07

    申请人： Intel Corporation

    发明人： Ralf Graefe ,  Damian Kelly

    IPC分类号： H04L67/12 ,  H04L67/02 ,  H04L67/10

    CPC分类号： H04L67/12 ,  H04L67/02 ,  H04L67/10

    摘要： Disclosed in some examples are methods, systems, and machine readable mediums which automatically generate standardized interfaces to sensor data consumers, provide sensor data search functionality, automatically determine data quality, and cache previously used sensor data to minimize the burden on application developers and minimize API call costs.