Patents by Inventor Cassandra PALLAI

Cassandra PALLAI 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).

  • Systems and methods for predicting pest pressure using geospatial features and machine learning
    Patent number: 12161103
    Abstract: System and methods for predicting future pest pressures are provided. A pest pressure prediction computing device includes a memory and a processor communicatively coupled to the memory. The processor is programmed to receive trap data for a plurality of pest traps in a geographic location, receive weather data for the geographic location, receive image data for the geographic location, identify at least one geospatial feature within or proximate to the geographic location, apply a machine learning algorithm to the trap data, the weather data, the image data, and the at least one identified geospatial feature to identify a correlation between pest pressure and the at least one geospatial feature, and generate predicted future pest pressures for the geographic location based at least on the identified correlation between pest pressure and the at least one geospatial feature.
    Type: Grant
    Filed: October 27, 2020
    Date of Patent: December 10, 2024
    Assignee: FMC Corporation
    Inventors: Sukhvinder Singh, Sara Catherine Sterling, Simon Bridge Barratt, Ruixue Gong, Wandi Lin, Sai Anirudh Mandagondi, Cassandra Pallai, Ross Joseph Putterman
  • SYSTEMS AND METHODS FOR PREDICTING PEST PRESSURE USING GEOSPATIAL FEATURES AND MACHINE LEARNING
    Publication number: 20210279639
    Abstract: System and methods for predicting future pest pressures are provided. A pest pressure prediction computing device includes a memory and a processor communicatively coupled to the memory. The processor is programmed to receive trap data for a plurality of pest traps in a geographic location, receive weather data for the geographic location, receive image data for the geographic location, identify at least one geospatial feature within or proximate to the geographic location, apply a machine learning algorithm to the trap data, the weather data, the image data, and the at least one identified geospatial feature to identify a correlation between pest pressure and the at least one geospatial feature, and generate predicted future pest pressures for the geographic location based at least on the identified correlation between pest pressure and the at least one geospatial feature.
    Type: Application
    Filed: October 27, 2020
    Publication date: September 9, 2021
    Inventors: Sukhvinder SINGH, Sara Catherine STERLING, Simon Bridge BARRATT, Ruixue GONG, Wandi LIN, Sai Anirudh MANDAGONDI, Cassandra PALLAI, Ross Joseph PUTTERMAN