Patents by Inventor Harikumar Venkatesan

Harikumar Venkatesan 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).

  • Patent number: 11361247
    Abstract: Historical device positioning data captured from one or more devices over a period of time is received. The historical device positioning data includes historical latitude, longitude, and elevation data of the one or more devices. Building boundaries for a give building are identified based upon the historical latitude and longitude data. The historical device positioning data corresponding to locations within the building boundaries of the building is clustered using a machine learning-based clustering algorithm, resulting in clusters with corresponding cluster centroids. The cluster centroids are associated with respective floors within the building. A current floor of the building on which a specific device is located is determined by mapping current device positioning data of the specific device to the closest cluster centroid.
    Type: Grant
    Filed: October 1, 2018
    Date of Patent: June 14, 2022
    Assignee: International Business Machines Corporation
    Inventors: Charles D. Wolfson, Otis Smart, Harikumar Venkatesan, Sushain Pandit, David A. Selby, Brent Gross, Corey A. Stubbs
  • Patent number: 10771920
    Abstract: Known geospatial device coordinates are clustered using a clustering algorithm into device clusters with cluster centroids. Each device cluster corresponds to a geographical location. Each cluster centroid is annotated with a regional floor-height value of the respective geographical location. Current device data of a device, including geographic location and elevation, are received. An approximate current floor upon which the first device is located is determined using the elevation of the first device and the annotated regional floor-height value of a closest cluster centroid, the closest cluster centroid determined based, at least in part, on the geographic location of the first device. An individual is directed to the device's geographic location and approximate current floor. The device clusters are re-computed based upon feedback from the individual regarding the device's actual floor.
    Type: Grant
    Filed: November 13, 2019
    Date of Patent: September 8, 2020
    Assignee: International Business Machines Corporation
    Inventors: Sushain Pandit, Charles D. Wolfson, Brent Gross, Otis Smart, Harikumar Venkatesan, David A. Selby
  • Patent number: 10631129
    Abstract: Known geospatial device coordinates are clustered using a machine learning-based clustering algorithm into device clusters with cluster centroids. Each device cluster corresponds to a geographical location. Each cluster centroid is annotated with a regional floor-height value of the respective geographical location. Current device data of a device, including latitude, longitude, and elevation, are received, and a geographic location of the device is determined using the latitude and longitude. An approximate current floor upon which the first device is located is determined by mapping the current device data of the first device to a closest cluster centroid, and calculating the approximate current floor using the elevation of the first device and the annotated regional floor-height value of the closest cluster centroid. An individual is directed to the device's geographic location and approximate current floor.
    Type: Grant
    Filed: October 1, 2018
    Date of Patent: April 21, 2020
    Assignee: International Business Machines Corporation
    Inventors: Sushain Pandit, Charles D. Wolfson, Brent Gross, Otis Smart, Harikumar Venkatesan, David A. Selby
  • Publication number: 20200107159
    Abstract: Known geospatial device coordinates are clustered using a machine learning-based clustering algorithm into device clusters with cluster centroids. Each device cluster corresponds to a geographical location. Each cluster centroid is annotated with a regional floor-height value of the respective geographical location. Current device data of a device, including latitude, longitude, and elevation, are received, and a geographic location of the device is determined using the latitude and longitude. An approximate current floor upon which the first device is located is determined by mapping the current device data of the first device to a closest cluster centroid, and calculating the approximate current floor using the elevation of the first device and the annotated regional floor-height value of the closest cluster centroid. An individual is directed to the device's geographic location and approximate current floor.
    Type: Application
    Filed: October 1, 2018
    Publication date: April 2, 2020
    Inventors: Sushain Pandit, Charles D. Wolfson, Brent Gross, Otis Smart, Harikumar Venkatesan, David A. Selby
  • Publication number: 20200107160
    Abstract: Known geospatial device coordinates are clustered using a clustering algorithm into device clusters with cluster centroids. Each device cluster corresponds to a geographical location. Each cluster centroid is annotated with a regional floor-height value of the respective geographical location. Current device data of a device, including geographic location and elevation, are received. An approximate current floor upon which the first device is located is determined using the elevation of the first device and the annotated regional floor-height value of a closest cluster centroid, the closest cluster centroid determined based, at least in part, on the geographic location of the first device. An individual is directed to the device's geographic location and approximate current floor. The device clusters are re-computed based upon feedback from the individual regarding the device's actual floor.
    Type: Application
    Filed: November 13, 2019
    Publication date: April 2, 2020
    Inventors: Sushain Pandit, Charles D. Wolfson, Brent Gross, Otis Smart, Harikumar Venkatesan, David A. Selby
  • Publication number: 20200104755
    Abstract: Historical device positioning data captured from one or more devices over a period of time is received. The historical device positioning data includes historical latitude, longitude, and elevation data of the one or more devices. Building boundaries for a give building are identified based upon the historical latitude and longitude data. The historical device positioning data corresponding to locations within the building boundaries of the building is clustered using a machine learning-based clustering algorithm, resulting in clusters with corresponding cluster centroids. The cluster centroids are associated with respective floors within the building. A current floor of the building on which a specific device is located is determined by mapping current device positioning data of the specific device to the closest cluster centroid.
    Type: Application
    Filed: October 1, 2018
    Publication date: April 2, 2020
    Inventors: Charles D. Wolfson, Otis Smart, Harikumar Venkatesan, Sushain Pandit, David A. Selby, Brent Gross, Corey A. Stubbs