Patents by Inventor Qinpeng Wang

Qinpeng Wang has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 11480935
    Abstract: There is described a building management system and a method for auto-tagging points. Data associated with multiple points of a site are received, and each point is associated with a point name and a point descriptor. A building name is identified based on the point name for each point by extracting a first part detected frequently among the data associated with the points. A point equipment is determined from a second part of each point name and a point function is determined from a third part of each point name. A set of point tags is generated based on the point equipment, the point function, and the point descriptor. Confidence scores are created for the set of point tags based on matching characteristics to a common tag set.
    Type: Grant
    Filed: October 30, 2020
    Date of Patent: October 25, 2022
    Assignee: Siemens Industry, Inc.
    Inventors: Qinpeng Wang, Gregory Conte
  • Patent number: 11347213
    Abstract: Methods, mediums, and systems include use of a system manger application in a data processing system for fault detection a building automation system using deep learning, to receive point data for a hardware being analyzed, where the received point data is contaminated data, train a deep learning model for the hardware being analyzed, generate predicted data based on the deep learning model, analyze the predicted data and the received point data, identify a fault in the hardware being analyzed according to the received point data and the predicted data, and produce a fault report according to the identified fault.
    Type: Grant
    Filed: June 22, 2018
    Date of Patent: May 31, 2022
    Assignee: Siemens Industry, Inc.
    Inventor: Qinpeng Wang
  • Publication number: 20220137577
    Abstract: There is described a building management system and a method for auto-tagging points. Data associated with multiple points of a site are received, and each point is associated with a point name and a point descriptor. A building name is identified based on the point name for each point by extracting a first part detected frequently among the data associated with the points. A point equipment is determined from a second part of each point name and a point function is determined from a third part of each point name. A set of point tags is generated based on the point equipment, the point function, and the point descriptor. Confidence scores are created for the set of point tags based on matching characteristics to a common tag set.
    Type: Application
    Filed: October 30, 2020
    Publication date: May 5, 2022
    Inventors: Qinpeng Wang, Gregory Conte
  • Patent number: 11009246
    Abstract: An approach that collects sensor data associated with a building automation system having filters and determining the optimal timing of the replacement of filters that includes replacement dates based upon use, utility, and labor costs.
    Type: Grant
    Filed: August 29, 2019
    Date of Patent: May 18, 2021
    Assignee: Siemens Industry, Inc.
    Inventors: Zhen Song, Gregory Conte, Qinpeng Wang
  • Publication number: 20210063038
    Abstract: An approach that collects sensor data associated with a building automation system having filters and determining the optimal timing of the replacement of filters that includes replacement dates based upon use, utility, and labor costs.
    Type: Application
    Filed: August 29, 2019
    Publication date: March 4, 2021
    Inventors: Zhen Song, Gregory Conte, Qinpeng Wang
  • Publication number: 20190391573
    Abstract: Methods, mediums, and systems include use of a system manger application in a data processing system for fault detection a building automation system using deep learning, to receive point data for a hardware being analyzed, where the received point data is contaminated data, train a deep learning model for the hardware being analyzed, generate predicted data based on the deep learning model, analyze the predicted data and the received point data, identify a fault in the hardware being analyzed according to the received point data and the predicted data, and produce a fault report according to the identified fault.
    Type: Application
    Filed: June 22, 2018
    Publication date: December 26, 2019
    Inventor: Qinpeng Wang
  • Patent number: D931571
    Type: Grant
    Filed: September 24, 2020
    Date of Patent: September 28, 2021
    Assignee: ARKSUN INC
    Inventor: Qinpeng Wang
  • Patent number: D951868
    Type: Grant
    Filed: October 29, 2020
    Date of Patent: May 17, 2022
    Inventor: Qinpeng Wang