Patents by Inventor John Geddes

John Geddes 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: 20240110893
    Abstract: A pathogen detection method. A sample that potentially contains a pathogen is collected. A triangle wave form output is produced. A signal associated with the triangle wave form is transmitted from a voltage-controlled oscillator over a plurality of frequencies. The signal is transmitted through the sample to cause the pathogen in the sample to vibrate at a frequency. The vibrations from the sample are detected. A resonance profile of a pathogen in the sample is calculated based upon the vibrations. A database that includes a resonance profile signature of at least one pathogens is provided. The calculated resonance profile is compared to the resonance profile signature database to determine if the sample includes the pathogen.
    Type: Application
    Filed: October 4, 2023
    Publication date: April 4, 2024
    Inventors: Timothy Childs, John Geddes, Daniel C. Eller, Jerry W. Cole, Kalyani Mantha, Manish Saka
  • Publication number: 20240094344
    Abstract: A method of detecting threats. A threat detection system is provided that includes a controller, a millimeter wave radar with transceiver, a signature database, and a camera. The signature database or machine learning includes time and frequency domain characteristic data for a threat. A signal is emitted by the millimeter wave radar. A return signal is received when the signal bounces off an object. Time and frequency domain characteristic data of the return signal is compared to the signature database, or the machine learned characteristics to determine the threat, anomaly, foreign object, material characteristics, and threat speech recognition.
    Type: Application
    Filed: September 6, 2023
    Publication date: March 21, 2024
    Inventors: Timothy T. Childs, Daniel C. Eller, Kalyani Mantha, John Geddes, Manish Saka
  • Publication number: 20230174047
    Abstract: An engine control unit (400) for a full hybrid engine (100, 101) is provided. The full hybrid engine (100, 101) comprises an internal combustion engine (110) and an electric motor (120). The internal combustion engine (110) is coupled to the drivetrain via a clutch (130). The engine control unit (400) is configured to operate the internal combustion engine (110) in a lean-burn mode, to determine a current load level of the full hybrid engine (100, 101), and to compare the current load level to a lean-burn load threshold (210). The lean-burn load threshold (210) defines a load level below which stable operation of the internal combustion engine (110) in the lean-burn mode is impossible and/or undesirable. If the current load level of the full hybrid engine (100, 101) is below the lean-burn load threshold (210), the internal combustion engine (110) is decoupled from the drivetrain and the full hybrid engine (100, 101) is operated in an electric mode.
    Type: Application
    Filed: March 26, 2021
    Publication date: June 8, 2023
    Inventors: Jack JOHNSON, Lyn MCWILLIAM, John GEDDES, Bryn LITTLEFAIR, Thomas JOHNSON
  • Publication number: 20220026560
    Abstract: A method of detecting threats. A threat detection system is provided that includes a controller, a millimeter wave radar, a signature database and a camera. The signature database or machine learning includes time and frequency domain characteristic data for a threat. A signal is emitted by the millimeter wave radar. A return signal is received when the signal bounces off an object. Time and frequency domain characteristic data of the return signal is compared to the signature database or the machine learned characteristics to determine the threat, anomaly, foreign object and material characteristics.
    Type: Application
    Filed: May 13, 2021
    Publication date: January 27, 2022
    Inventors: Timothy T. Childs, Daniel C. Eller, Kalyani Mantha, John Geddes, Manish Saka
  • Publication number: 20190195989
    Abstract: A method of detecting threats. A threat detection system is provided that includes a controller, a millimeter wave radar, a signature database and a camera. The signature database or machine learning includes time and frequency domain characteristic data for a threat. A signal is emitted by the millimeter wave radar. A return signal is received when the signal bounces off an object. Time and frequency domain characteristic data of the return signal is compared to the signature database or the machine learned characteristics to determine the threat, anomaly, foreign object and material characteristics.
    Type: Application
    Filed: April 23, 2018
    Publication date: June 27, 2019
    Inventors: Timothy T. Childs, Daniel C. Eller, Kalyani Mantha, John Geddes, Manish Saka