Patents by Inventor Matthew Scharpf

Matthew Scharpf 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).

  • Publication number: 20250238881
    Abstract: A method for cross-bore risk management involves receiving at least one dataset comprising a plurality of assets and cross-bore data. A risk probability value is calculated, using a processor, based on the cross-bore data for each asset of the plurality of assets using machine learning techniques. The risk probability values are spatially distributed around each respective asset. A graphical output is produced that illustrates the risk probability for a specified geographical area based on the spatially distributed risk probability values.
    Type: Application
    Filed: April 15, 2025
    Publication date: July 24, 2025
    Applicant: Hydromax USA, LLC
    Inventor: Matthew Scharpf
  • Patent number: 12271962
    Abstract: A method for cross-bore risk management involves receiving at least one dataset comprising a plurality of assets and cross-bore data. A risk probability value is calculated, using a processor, based on the cross-bore data for each asset of the plurality of assets using machine learning techniques. The risk probability values are spatially distributed around each respective asset. A graphical output is produced that illustrates the risk probability for a specified geographical area based on the spatially distributed risk probability values.
    Type: Grant
    Filed: February 2, 2023
    Date of Patent: April 8, 2025
    Assignee: HYDOMAX USA, LLC
    Inventor: Matthew Scharpf
  • Patent number: 12229841
    Abstract: A method for cross-bore risk management involves receiving at least one dataset comprising a plurality of assets and cross-bore data. A risk probability value is calculated, using a processor, based on the cross-bore data for each asset of the plurality of assets using machine learning techniques. The risk probability values are spatially distributed around each respective asset. A graphical output is produced that illustrates the risk probability for a specified geographical area based on the spatially distributed risk probability values.
    Type: Grant
    Filed: June 26, 2019
    Date of Patent: February 18, 2025
    Assignee: HYDROMAX USA, LLC
    Inventor: Matthew Scharpf
  • Publication number: 20230186410
    Abstract: A method for cross-bore risk management involves receiving at least one dataset comprising a plurality of assets and cross-bore data. A risk probability value is calculated, using a processor, based on the cross-bore data for each asset of the plurality of assets using machine learning techniques. The risk probability values are spatially distributed around each respective asset. A graphical output is produced that illustrates the risk probability for a specified geographical area based on the spatially distributed risk probability values.
    Type: Application
    Filed: February 2, 2023
    Publication date: June 15, 2023
    Applicant: Hydromax USA, LLC
    Inventor: Matthew Scharpf
  • Publication number: 20230177623
    Abstract: A method for cross-bore risk management involves receiving at least one dataset comprising a plurality of assets and cross-bore data. A risk probability value is calculated, using a processor, based on the cross-bore data for each asset of the plurality of assets using machine learning techniques. The risk probability values are spatially distributed around each respective asset. A graphical output is produced that illustrates the risk probability for a specified geographical area based on the spatially distributed risk probability values.
    Type: Application
    Filed: February 2, 2023
    Publication date: June 8, 2023
    Applicant: Hydromax USA, LLC
    Inventor: Matthew Scharpf
  • Publication number: 20200005406
    Abstract: A method for cross-bore risk management involves receiving at least one dataset comprising a plurality of assets and cross-bore data. A risk probability value is calculated, using a processor, based on the cross-bore data for each asset of the plurality of assets using machine learning techniques. The risk probability values are spatially distributed around each respective asset. A graphical output is produced that illustrates the risk probability for a specified geographical area based on the spatially distributed risk probability values.
    Type: Application
    Filed: June 26, 2019
    Publication date: January 2, 2020
    Inventor: Matthew Scharpf