Patents by Inventor Aravindakshan BABU

Aravindakshan BABU 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: 20220058099
    Abstract: A device monitoring system comprising a computation engine to obtain, for each of a plurality of devices, an actual failure condition indicating actual device failure and a probable failure condition predicted by a health monitoring device. The health monitoring device to monitor health of the plurality of devices, the probable failure condition indicating when the device is predicted to stop functioning. The computation engine is to compute a failure prediction gap for each of the plurality of devices. The failure prediction gap indicating a difference between the probable failure condition and the actual failure condition. A performance evaluation engine to compute a saving factor based at least on cost parameters and an average of the failure prediction gap computed for the plurality of devices and initiate discontinuance of usage of the health monitoring device based on a comparison of the saving factor with a threshold.
    Type: Application
    Filed: May 13, 2020
    Publication date: February 24, 2022
    Applicant: Hewlett-Packard Development Company, L.P.
    Inventors: Niranjan Damera Venkata, Aravindakshan Babu, Darrel D Cherry, Anton Wiranata, Prasad Hegde, Mithra Vankipuram
  • Patent number: 10846311
    Abstract: An optimized and efficient method of identifying one or more points within a dataset that are close to the centers of clumps similar records in a large, multi-element dataset uses Monte Carlo techniques to compute approximate clustering costs at significantly reduced computational expense. The inaccuracy caused by the approximate methods is also estimated, and if it is too high, the method may be repeated with a larger Monte Carlo sample size to improve accuracy. Portions of the algorithm that are independent are distributed among a number of cooperating computing nodes so that the full algorithm can be completed in less time.
    Type: Grant
    Filed: October 9, 2018
    Date of Patent: November 24, 2020
    Assignee: Mad Street Den, Inc.
    Inventors: Saurabh Agarwal, Aravindakshan Babu, Sudarshan Babu, Hariharan Chandrasekaran
  • Publication number: 20190130018
    Abstract: An optimized and efficient method of identifying one or more points within a dataset that are close to the centers of clumps similar records in a large, multi-element dataset uses Monte Carlo techniques to compute approximate clustering costs at significantly reduced computational expense. The inaccuracy caused by the approximate methods is also estimated, and if it is too high, the method may be repeated with a larger Monte Carlo sample size to improve accuracy. Portions of the algorithm that are independent are distributed among a number of cooperating computing nodes so that the full algorithm can be completed in less time.
    Type: Application
    Filed: October 9, 2018
    Publication date: May 2, 2019
    Applicant: Mad Street Den, Inc.
    Inventors: Saurabh AGARWAL, Aravindakshan BABU, Sudarshan BABU, Hariharan CHANDRASEKARAN