Patents by Inventor Sentibaleng M. NCUBE

Sentibaleng M. NCUBE 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).

  • Adaptive alarm and dispatch system using incremental regressive model development
    Patent number: 11256244
    Abstract: Systems and methods for monitoring an operational system. An initial set of sensor data is accumulated from a system over a substantially shorter time than is required to collect data to characterize a regression model for an operating parameter of the system. An initial regression model is created based on the initial set of sensor data. A subsequent set of sensor data is received from the at least one sensor after creating the initial regression model. An expected dependent value for the subsequent independent value is determined using the initial regression model. An operator is prompted to update the initial regression model based on a difference between a subsequent dependent value and the expected dependent value. The initial regression model is updated to incorporate the subsequent set of sensor data. A notification is provided based on a difference between presently received sensor data and the updated regression model.
    Type: Grant
    Filed: February 5, 2018
    Date of Patent: February 22, 2022
    Assignee: Inventus Holdings, LLC
    Inventors: Boris A. Zarate, Sentibaleng M. Ncube, Hooman Yousefizadeh, Yi Li, Donville Smith
  • ADAPTIVE SYSTEM MONITORING USING INCREMENTAL REGRESSIVE MODEL DEVELOPMENT
    Publication number: 20190243350
    Abstract: Systems and methods for monitoring an operational system. An initial set of sensor data is accumulated from a system over a substantially shorter time than is required to collect data to characterize a regression model for an operating parameter of the system. An initial regression model is created based on the initial set of sensor data. A subsequent set of sensor data is received from the at least one sensor after creating the initial regression model. An expected dependent value for the subsequent independent value is determined using the initial regression model. An operator is prompted to update the initial regression model based on a difference between a subsequent dependent value and the expected dependent value. The initial regression model is updated to incorporate the subsequent set of sensor data. A notification is provided based on a difference between presently received sensor data and the updated regression model.
    Type: Application
    Filed: February 5, 2018
    Publication date: August 8, 2019
    Inventors: Boris A. ZARATE, Sentibaleng M. NCUBE, Hooman YOUSEFIZADEH, Yi LI, Donville SMITH