Patents by Inventor Deepalakshmi Ranganathan

Deepalakshmi Ranganathan 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).

  • Method and system for analyzing internet of things (IoT) data in real-time and providing predictions
    Patent number: 11321624
    Abstract: This disclosure relates to method and system for analyzing IoT data in real-time and predicting future events. In one embodiment, the method may include acquiring the real-time IoT data corresponding to one or more IoT devices, and building a predictive model based on the real-time IoT data. The predictive model may include a machine learning algorithm that generates an output parameter representing a future event based on a set of input parameters derived from the real-time IoT data. The predictive model may be built by training the predictive model for one or more explanatory input parameters and an expected output parameter. The method may further include predicting the future event based on the real-time IoT data using the predictive model, determining a deviation between the future event and an actual event, and tuning the predictive model based on the deviation.
    Type: Grant
    Filed: November 5, 2018
    Date of Patent: May 3, 2022
    Assignee: Wipro Limited
    Inventors: Sandipan Bhattacharyya, Deepalakshmi Ranganathan
  • METHOD AND SYSTEM FOR ANALYZING INTERNET OF THINGS (IoT) DATA IN REAL-TIME AND PROVIDING PREDICTIONS
    Publication number: 20200090070
    Abstract: This disclosure relates to method and system for analyzing IoT data in real-time and predicting future events. In one embodiment, the method may include acquiring the real-time IoT data corresponding to one or more IoT devices, and building a predictive model based on the real-time IoT data. The predictive model may include a machine learning algorithm that generates an output parameter representing a future event based on a set of input parameters derived from the real-time IoT data. The predictive model may be built by training the predictive model for one or more explanatory input parameters and an expected output parameter. The method may further include predicting the future event based on the real-time IoT data using the predictive model, determining a deviation between the future event and an actual event, and tuning the predictive model based on the deviation.
    Type: Application
    Filed: November 5, 2018
    Publication date: March 19, 2020
    Inventors: Sandipan Bhattacharyya, Deepalakshmi Ranganathan