Patents by Inventor Connor Liam McFadden

Connor Liam McFadden 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: 20240036650
    Abstract: Disclosed herein are systems and methods for methods of developing a database of controllable objects in an environment. For example, a method includes a mobile device having a camera to capture images of objects in an environment. For each object, the method includes, in response to receiving a user selection of the object, training a machine-learning model to recognize the object. The method includes receiving a command associated with the object and receiving a plurality of images of the object and training the machine-learning model to recognize the object based on the plurality of images. The method further includes transmitting the trained model and the command to a wearable electronic device causing the wearable electronic device to save the trained machine-learning model to a data store and to associate the command with the trained machine-learning model.
    Type: Application
    Filed: October 6, 2023
    Publication date: February 1, 2024
    Inventors: Ian Davies Troisi, Justin Henry Deegan, Connor Liam McFadden, Nicholas Albert Silenzi
  • Patent number: 11816266
    Abstract: Disclosed herein are systems and methods for methods of developing a database of controllable objects in an environment. For example, a method includes a mobile device having a camera to capture images of objects in an environment. For each object, the method includes, in response to receiving a user selection of the object, training a machine-learning model to recognize the object. The method includes receiving a command associated with the object and receiving a plurality of images of the object and training the machine-learning model to recognize the object based on the plurality of images. The method further includes transmitting the trained model and the command to a wearable electronic device causing the wearable electronic device to save the trained machine-learning model to a data store and to associate the command with the trained machine-learning model.
    Type: Grant
    Filed: September 23, 2022
    Date of Patent: November 14, 2023
    Inventors: Ian Davies Troisi, Justin Henry Deegan, Connor Liam McFadden, Nicholas Albert Silenzi
  • Publication number: 20230018742
    Abstract: Disclosed herein are systems and methods for methods of developing a database of controllable objects in an environment. For example, a method includes a mobile device having a camera to capture images of objects in an environment. For each object, the method includes, in response to receiving a user selection of the object, training a machine-learning model to recognize the object. The method includes receiving a command associated with the object and receiving a plurality of images of the object and training the machine-learning model to recognize the object based on the plurality of images. The method further includes transmitting the trained model and the command to a wearable electronic device causing the wearable electronic device to save the trained machine-learning model to a data store and to associate the command with the trained machine-learning model.
    Type: Application
    Filed: September 23, 2022
    Publication date: January 19, 2023
    Inventors: Ian Davies Troisi, Justin Henry Deegan, Connor Liam McFadden, Nicholas Albert Silenzi
  • Patent number: 11500463
    Abstract: Disclosed herein are systems and methods for controlling electronic devices based on detected brain activity. For example, a system includes a wearable over-the-ear electronic device has a set of dry EEG sensors, a camera, a processor, and programming instructions. The programming instructions cause the processor to receive images from the camera, process the images to identify features corresponding to a known device, and receive brain-wave signals from the EEG sensors. The system compares the brain-wave signals to measure a level of brain activity. Upon detection of both (a) a feature corresponding to the known device and (b) a level of brain activity that deviates from a baseline by at least a threshold level, the system generates a command signal configured to cause the known device to actuate and transmits the command signal to a controller for the known device.
    Type: Grant
    Filed: November 5, 2021
    Date of Patent: November 15, 2022
    Assignee: Imagine Technologies, Inc.
    Inventors: Ian Davies Troisi, Justin Henry Deegan, Connor Liam McFadden, Nicholas Albert Silenzi
  • Patent number: 11461991
    Abstract: Disclosed herein are systems and methods for methods of developing a database of controllable objects in an environment. For example, a method includes a mobile device having a camera to capture images of objects in an environment. For each object, the method includes, in response to receiving a user selection of the object, training a machine-learning model to recognize the object. The method includes receiving a command associated with the object and receiving a plurality of images of the object and training the machine-learning model to recognize the object based on the plurality of images. The method further includes transmitting the trained model and the command to a wearable electronic device causing the wearable electronic device to save the trained machine-learning model to a data store and to associate the command with the trained machine-learning model.
    Type: Grant
    Filed: November 5, 2021
    Date of Patent: October 4, 2022
    Assignee: Imagine Technologies, Inc.
    Inventors: Ian Davies Troisi, Justin Henry Deegan, Connor Liam McFadden, Nicholas Albert Silenzi
  • Publication number: 20220207281
    Abstract: Disclosed herein are systems and methods for methods of developing a database of controllable objects in an environment. For example, a method includes a mobile device having a camera to capture images of objects in an environment. For each object, the method includes, in response to receiving a user selection of the object, training a machine-learning model to recognize the object. The method includes receiving a command associated with the object and receiving a plurality of images of the object and training the machine-learning model to recognize the object based on the plurality of images. The method further includes transmitting the trained model and the command to a wearable electronic device causing the wearable electronic device to save the trained machine-learning model to a data store and to associate the command with the trained machine-learning model.
    Type: Application
    Filed: November 5, 2021
    Publication date: June 30, 2022
    Inventors: Ian Davies Troisi, Justin Henry Deegan, Connor Liam McFadden, Nicholas Albert Silenzi
  • Publication number: 20220206576
    Abstract: Disclosed herein are systems and methods for controlling electronic devices based on detected brain activity. For example, a system includes a wearable over-the-ear electronic device has a set of dry EEG sensors, a camera, a processor, and programming instructions. The programming instructions cause the processor to receive images from the camera, process the images to identify features corresponding to a known device, and receive brain-wave signals from the EEG sensors. The system compares the brain-wave signals to measure a level of brain activity. Upon detection of both (a) a feature corresponding to the known device and (b) a level of brain activity that deviates from a baseline by at least a threshold level, the system generates a command signal configured to cause the known device to actuate and transmits the command signal to a controller for the known device.
    Type: Application
    Filed: November 5, 2021
    Publication date: June 30, 2022
    Inventors: Ian Davies Troisi, Justin Henry Deegan, Connor Liam McFadden, Nicholas Albert Silenzi