Patents by Inventor ANKUR PANDIT

ANKUR PANDIT 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: 20240028957
    Abstract: This disclosure relates to methods and systems for high resolution and scalable crop yield forecasting by first developing a first crop yield forecasting model to generate coarse resolution yield maps and further dynamically selecting a set of pixels from the coarse resolution yield maps. The coarse resolution yield maps, satellite, weather and soil related data are fed as input to a second crop yield forecasting to generate high resolution crop yield forecasting maps. Further, domain knowledge about crop growth stages, economically important crop growth stages and weather based triggers are identified to quantify extent of change in crop yield. This helps in crop yield forecasting during real time adverse weather conditions. Finally, an adjusted crop yield model is obtained after adjusting losses incurred due to the real time adverse weather conditions to obtain accurate high resolution crop yield forecasting maps. The method of present disclosure is inexpensive, light-weight, and scalable.
    Type: Application
    Filed: June 13, 2023
    Publication date: January 25, 2024
    Applicant: Tata Consultancy Services Limited
    Inventors: Jayantrao MOHITE, Suryakant Ashok SAWANT, Rishabh AGARWAL, Ankur PANDIT, Srinivasu PAPPULA
  • Publication number: 20230298183
    Abstract: Coarse resolution satellite data has limited information content of land captured in the images and small area field boundary detection is technically challenging. Embodiments of the present disclosure provide a method and system for detection of field boundaries using coarse resolution satellite data and GIS. Multi-layer crop segmentation approach is used over RoI, wherein agricultural land related segments are derived from a soil layer, a temporal stack for a current season and a temporal change layer from the coarse resolution satellite data of the RoI. Segmentation based on different aspects captures various details at each segmentation layer. The segments are then combined, which aggregates all information related to the land to accurately detect the field boundaries in the RoI. The field boundaries are further refined using GIS topology operations. Baseline cadastral maps are updated using information from maps generated using refined field boundaries identified in real time for each season.
    Type: Application
    Filed: February 27, 2023
    Publication date: September 21, 2023
    Applicant: Tata Consultancy Services Limited
    Inventors: JAYANTRAO MOHITE, SURYAKANT ASHOK SAWANT, RISHABH AGARWAL, ANKUR PANDIT, SRINIVASU PAPPULA
  • Publication number: 20230090921
    Abstract: Agriculture is impacted due to various parameters that results into heavy losses to the crops. Existing methods rely on manual inventories from fields and statistical results are prone to errors thus classification of crops may not be accurate. Present disclosure provides systems and methods for detection and prediction of disguised and potential non-performing assets (NPAs) in agriculture. Disguised NPAs detection involves, obtaining satellite data from sources and natural calamity, detecting of crop for past years, crop growth, estimating yields, market prices for individual years, AC zones, etc. wherein a generate performance score is generated for each field for classifying crop as disguised NPA.
    Type: Application
    Filed: July 19, 2022
    Publication date: March 23, 2023
    Applicant: Tata Consultancy Services Limited
    Inventors: JAYANTRAO MOHITE, SRINIVASU PAPPULA, SURYAKANT ASHOK SAWANT, VAIBHAV SADASHIV LONKAR, MARIAPPAN SAKKAN, ANKUR PANDIT
  • Publication number: 20220343099
    Abstract: The disclosure herein relates to identification of agro-phenological zones. Further the disclosed method and system also shares techniques for updating of the identified/existing agro-phenological zones. In a diverse geographical domain (like India), in order to maximize the crop production (avoid crop failures) from the available resources and prevailing diverse climatic conditions it necessary to use the resources and technology to infer the best agriculture approach on an individual location. The invention enables identification of the agro-phenological zones based on satellite image, weather data, soil data and cloud free historical satellite data using several techniques that includes machine learning, time series analysis, heuristic time series analysis technique and clustering. Further the invention also discloses techniques to update the identified/existing agro-phenological zones using historic data of agro-phenological zones of satellite image.
    Type: Application
    Filed: October 21, 2021
    Publication date: October 27, 2022
    Applicant: Tata Consultancy Services Limited
    Inventors: JAYANTRAO MOHITE, SURYAKANT ASHOK SAWANT, ANKUR PANDIT, SRINIVASU PAPPULA, MARIAPPAN SAKKAN
  • Publication number: 20220312699
    Abstract: This disclosure relates generally to root zone moisture estimation for vegetation cover using remote sensing. Conventionally, it is challenging to estimate root zone soil moisture using only satellite data. Moreover, estimation of soil moisture under vegetation cover based on bare surface soil moisture and vegetation parameters is not available. The disclosed method and system facilitate estimation of an ensemble of soil moisture under vegetation cover and root zone soil moisture using process based soil water balance for spatial estimation of root zone soil moisture. The system estimates bare surface soil moisture for different soil types/textures using the baseline bare surface model and soil properties derived from satellite data and in-situ sensors. The method further provides temporal spatially distributed soil moisture inputs to an intelligent irrigation management/information system which is very important to reduce and regulate water consumption.
    Type: Application
    Filed: January 3, 2022
    Publication date: October 6, 2022
    Applicant: Tata Consultancy Services Limited
    Inventors: ANKUR PANDIT, JAYANTRAO MOHITE, SURYAKANT ASHOK SAWANT, SRINIVASU PAPPULA
  • Publication number: 20220237888
    Abstract: Machine Learning models to be created for crop mapping for any region, require huge volumes of ground truth data requiring manual effort in generating region specific training dataset. Method and system for providing generalized approach for crop mapping across regions with varying characteristics is disclosed. The method provides automatic generation of a labelled pixel dataset representing cropping pattern of a Region of Interest (ROI) for building a ML crop mapping model for the ROI. The generated labelled pixel dataset captures regional dependency and localized phenological indicators for the ROI. ML crop mapping model is updated using a database, regularly updated for the set of crops and the plurality of features associated with each of the set of crops and corresponding the set of crops.
    Type: Application
    Filed: January 26, 2022
    Publication date: July 28, 2022
    Applicant: Tata Consultancy Services Limited
    Inventors: JAYANTRAO MOHITE, SURYAKANT ASHOK SAWANT, ANKUR PANDIT, SRINIVASU PAPPULA