Patents by Inventor Jeremy Deram

Jeremy Deram 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).

  • Collision analysis platform using machine learning to reduce generation of false collision outputs
    Patent number: 11961339
    Abstract: Aspects of the disclosure relate to computing platforms that utilize machine learning to reduce false positive/negative collision output generation. A computing platform may apply machine learning algorithms on received data to generate a collision output. In response to generating the collision output indicating a collision, the computing platform may identify a data collection location. If the data collection location is within a predetermined radius of a false positive collection location, the computing platform may modify the collision output to indicate a non-collision. If the data collection location is not within the predetermined radius, the computing platform may compute a score using telematics data and compare the score to a predetermined threshold. If the score does not exceed the predetermined threshold, the computing platform may modify the collision output to indicate a non-collision.
    Type: Grant
    Filed: January 10, 2023
    Date of Patent: April 16, 2024
    Assignee: ALLSTATE INSURANCE COMPANY
    Inventors: Venu Madhav Tammali, Kyle Patrick Schmitt, Jeremy Deram
  • Collision analysis platform using machine learning to reduce generation of false collision outputs
    Patent number: 11562603
    Abstract: Aspects of the disclosure relate to computing platforms that utilize machine learning to reduce false positive/negative collision output generation. A computing platform may apply machine learning algorithms on received data to generate a collision output. In response to generating the collision output indicating a collision, the computing platform may identify a data collection location. If the data collection location is within a predetermined radius of a false positive collection location, the computing platform may modify the collision output to indicate a non-collision. If the data collection location is not within the predetermined radius, the computing platform may compute a score using telematics data and compare the score to a predetermined threshold. If the score does not exceed the predetermined threshold, the computing platform may modify the collision output to indicate a non-collision.
    Type: Grant
    Filed: June 26, 2020
    Date of Patent: January 24, 2023
    Assignee: ALLSTATE INSURANCE COMPANY
    Inventors: Venu Madhav Tammali, Kyle Patrick Schmitt, Jeremy Deram
  • Collision Analysis Platform Using Machine Learning to Reduce Generation of False Collision Outputs
    Publication number: 20210407219
    Abstract: Aspects of the disclosure relate to computing platforms that utilize machine learning to reduce false positive/negative collision output generation. A computing platform may apply machine learning algorithms on received data to generate a collision output. In response to generating the collision output indicating a collision, the computing platform may identify a data collection location. If the data collection location is within a predetermined radius of a false positive collection location, the computing platform may modify the collision output to indicate a non-collision. If the data collection location is not within the predetermined radius, the computing platform may compute a score using telematics data and compare the score to a predetermined threshold. If the score does not exceed the predetermined threshold, the computing platform may modify the collision output to indicate a non-collision.
    Type: Application
    Filed: June 26, 2020
    Publication date: December 30, 2021
    Inventors: Venu Madhav Tammali, Kyle Patrick Schmitt, Jeremy Deram