Artificial intelligence device for guiding furniture placement and method of operating the same

    公开(公告)号:US11625508B2

    公开(公告)日:2023-04-11

    申请号:US16944034

    申请日:2020-07-30

    Abstract: The present invention includes an artificial intelligence device and a method for operating the same. The artificial intelligence device includes a communication unit that receives indoor area map data and indoor area image data from at least one external device, and a processor that generates first furniture placement map data in which a placement position of at least one piece of furniture is mapped, provides the first furniture placement map data to a furniture placement model, and obtains second furniture placement map data in which a placement position of at least one piece of furniture is changed, based on indoor area map data and indoor area image data.

    Device including battery
    14.
    发明授权

    公开(公告)号:US10803385B2

    公开(公告)日:2020-10-13

    申请号:US16181271

    申请日:2018-11-05

    Abstract: A method of controlling a battery is disclosed. The method includes training an artificial neural network to calculate an internal characteristic parameter value of the battery corresponding to a sensed input/output parameter value using training data, sensing the input/output parameter value of the battery, acquiring the characteristic parameter value corresponding to the sensed input/output parameter value using the trained artificial neural network, and controlling charging or discharging of the battery based on the acquired characteristic parameter value.

    DEVICE INCLUDING BATTERY
    15.
    发明申请

    公开(公告)号:US20200074297A1

    公开(公告)日:2020-03-05

    申请号:US16181271

    申请日:2018-11-05

    Abstract: A method of controlling a battery is disclosed. The method includes training an artificial neural network to calculate an internal characteristic parameter value of the battery corresponding to a sensed input/output parameter value using training data, sensing the input/output parameter value of the battery, acquiring the characteristic parameter value corresponding to the sensed input/output parameter value using the trained artificial neural network, and controlling charging or discharging of the battery based on the acquired characteristic parameter value.

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