公开(公告)号：US11963488B2

公开(公告)日：2024-04-23

申请号：US17646731

申请日：2022-01-03

Applicant: Tata Consultancy Services Limited

Inventor： Ankur Pandit ,  Jayantrao Mohite ,  Suryakant Ashok Sawant ,  Srinivasu Pappula

IPC: A01G25/16 ,  G01N33/24 ,  G01S19/14 ,  G01S19/25 ,  G01S19/26

CPC classification number: A01G25/167 ,  G01N33/246 ,  G01S19/14 ,  G01S19/256 ,  G01S19/26

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.

公开(公告)号：US10555461B2

公开(公告)日：2020-02-11

申请号：US15066891

申请日：2016-03-10

Applicant: Tata Consultancy Services Limited

Inventor： Bhushan Gurmukhdas Jagyasi ,  Jayantrao Mohite ,  Srinivasu Pappula

IPC: A01G22/00 ,  G06Q50/02 ,  G06Q10/04 ,  G06Q10/06 ,  A01C14/00 ,  A01M17/00 ,  A01M99/00 ,  G01W1/00

Abstract: Presence of natural enemies has a considerable impact on pest severity in a given geo-location. However, manually estimating pest severity or population of natural enemies is cumbersome, inaccurate and not scalable. Systems and methods of the present disclosure enable estimating effective pest severity index by receiving a first set of inputs pertaining to weather associated with a geo-location under consideration; receiving a second set of inputs pertaining to agronomic information; generating a pest forecasting model and a natural enemies forecasting model based on the received first set and the second set of inputs for each pest; and estimating the effective pest severity index based on the generated models. The timing and quantity of pesticide application can be optimized based on the estimated pest severity index. The generated models can be further enhanced continually based on one or more of historical data, participatory sensing inputs, crowdsourcing inputs and management practices.

公开(公告)号：US11645596B2

公开(公告)日：2023-05-09

申请号：US17449841

申请日：2021-10-04

Applicant: Tata Consultancy Services Limited

Inventor： Pankaj Doke ,  Karan Bhavsar ,  Sujit Shinde ,  Sanjay Kimbahune ,  Manash Paul ,  Srinivasu Pappula ,  Sylvan Lobo ,  Akhilesh Srivastava

IPC: G06Q10/06 ,  G06Q10/0631

CPC classification number: G06Q10/06313

Abstract: State-of-the-art techniques hardly attempt to address controlled resource access problem in context of Basic Emergent Users (BEUs). Embodiments of the present disclosure provide a method and system for Proof of Work (POW) based protection of resources. The method includes using the POW for work done by BEUs in physical world and mapping it to digital world to generate crypto currency in terms of credit score, wherein an end user is eligible or authorized to use a resource of an entity to get a desired service if accumulated credit score is above a credit threshold. Gaining points to improve the credit score is challenging as it is based on percentage of compliance achieved by the BEU through actual work in accordance with a compliance protocol. Further, the method includes authenticating the authorized user based on a set of questions with increasing difficulty, derived based on a culture graph.

公开(公告)号：US11425628B2

公开(公告)日：2022-08-23

申请号：US16099936

申请日：2017-05-08

Applicant: Tata Consultancy Services Limited

Inventor： Sanat Sarangi ,  Srinivasu Pappula

IPC: H04W40/32 ,  H04W52/02 ,  H04W84/18

Abstract: A system and method for achieving auto-adaptive clustering in a sensor network has been explained. The system performs a hierarchical clustering in sensor networks to maximize the lifetime of the network. The system includes a set of sensor nodes and a sink node. The clusters in sensor networks are formed automatically from a large number of deployed nodes where the cluster characteristics are driven by the measurement requirements defined by the end-user. The system also employs a clustering algorithm to achieve adaptive clustering. The processor further includes a first level clustering module for grouping the set of sensor nodes into data level clusters based on the measurements. The processor further includes a second level clustering module for grouping the set of sensor nodes in the data level clusters into the location level clusters based on location. In another embodiment, that clustering can go on to more than two levels.

公开(公告)号：US20210303770A1

公开(公告)日：2021-09-30

申请号：US17136593

申请日：2020-12-29

Applicant: Tata Consultancy Services Limited

Inventor： Pankaj Doke ,  Karan Bhavsar ,  Sujit Shinde ,  Sanjay Kimbahune ,  Srinivasu Pappula ,  Harsh Vishwakarma ,  Sylvan Lobo ,  Akhilesh Srivastava

IPC: G06F40/109 ,  G06F3/0481 ,  G06F3/0485 ,  G06F40/284

Abstract: State of the art viewport design approach faces challenge in addressing customization of view port design. A method and device for dynamic view port generation providing enhanced viewport usability of text messages to be displayed on screen by considering type of user and customized typeface is provided. Determining of a customized typeface is based on user's reading capability tested during initial type face set up by the device. The customization of typeface includes applying kerning spacing and glyphs adjustment to squeeze area of the displayed text, still maintaining less ambiguity during reading. For received messages to be displayed, maximum size of window for a viewport is obtained on-the-fly with a constraint of maximum or optimal number of viewports displayed at a time on device screen. NLP is applied to each message to condense text in the message such that maximum information is conveyed while displaying minimum words.

公开(公告)号：US12182751B2

公开(公告)日：2024-12-31

申请号：US17813371

申请日：2022-07-19

Applicant: Tata Consultancy Services Limited

Inventor： Jayantrao Mohite ,  Srinivasu Pappula ,  Suryakant Ashok Sawant ,  Vaibhav Sadashiv Lonkar ,  Mariappan Sakkan ,  Ankur Pandit

IPC: G06Q10/0639 ,  A01B79/00 ,  G06F16/29 ,  G06Q50/02 ,  G06T7/11 ,  G06V10/75 ,  G06V20/00 ,  G06V20/10 ,  G06V20/13

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. Predicting potential NPAs includes obtaining current season satellite data, data received from the fields via sensors, determining crop protocol being followed, forecast weather, estimating cumulative growth, feedback received from fields, projected yield, estimating crop losses, and then performance score is generated for predicting crops as potential NPA.

公开(公告)号：US12130906B2

公开(公告)日：2024-10-29

申请号：US18051200

申请日：2022-10-31

Applicant: Tata Consultancy Services Limited

Inventor： Pankaj Doke ,  Karan Rajesh Bhavsar ,  Srinivasu Pappula ,  Akhilesh Srivastava ,  Sujit Shinde ,  Sanjay Kimbahune

IPC: G06F21/36 ,  G06F21/46 ,  G06F21/62 ,  H04L9/40

CPC classification number: G06F21/46 ,  G06F21/6218

Abstract: State of the art authentication mechanisms have limitations when used by Basic Emergent User (BEU). Embodiments herein provide method and system for recognition based multi-skill-multi-sensory passwords with dynamic identification of sensor combination based on end user skill, specifically for the BEU. The method disclosed generates user profile using a task-based technique to determine skill and capability of the user associated with each of a plurality of sensory categories used for generating a multi-skill-multi-sensory password. Each of the plurality of sensory categories are graded is descending order based on user's skill and capability and user is offered to select each password entry from a particular sensor category in accordance with the identified grade in each iteration. Thus, the entropy of password generation in the context of user is split among the sensor categories. Furthermore, recognition-based out of sequence approach is used during user authentication instead of more challenging memorizing-based approach.

公开(公告)号：US12039730B2

公开(公告)日：2024-07-16

申请号：US17372725

申请日：2020-01-15

Applicant: Tata Consultancy Services Limited

Inventor： Jayantrao Mohite ,  Sanjay Kimbahune ,  Srinivasu Pappula ,  Dineshkumar Singh ,  Sanat Sarangi

IPC: G06K9/00 ,  G01N33/00 ,  G06T7/00 ,  G06V10/762 ,  G06V20/10 ,  G06V20/13 ,  G06V20/90

CPC classification number: G06T7/0014 ,  G01N33/0098 ,  G06V10/762 ,  G06V20/13 ,  G06V20/188 ,  G06V20/90 ,  G06T2207/10032 ,  G06T2207/30188

Abstract: Plant health estimation is required to be performed so as to detect any health issues in early stages, so as to take counter measures. Existing systems for the plant health estimation perform the health estimation by considering data obtained from satellite images of the plants being monitored. However this alone may not be much effective as the satellite images fail to provide information on many parameters which have direct or indirect impact on health of the plants. Disclosed herein are a method and a system for plant health estimation, wherein the system performs health estimation at a macro level and a micro level. The macro level health estimation is done using satellite images of the plants as inputs, whereas the micro level health estimation is done by collecting and processing sensor data with respect to various parameters that affect health of a plant.

公开(公告)号：US11989886B2

公开(公告)日：2024-05-21

申请号：US17371650

申请日：2020-02-07

Applicant: Tata Consultancy Services Limited

Inventor： Prakruti Vinodchandra Bhatt ,  Sanat Sarangi ,  Srinivasu Pappula

IPC: G06T7/136 ,  G06T7/00 ,  G06T7/11 ,  G06T7/174 ,  G06V10/26 ,  G06V10/764 ,  G06V10/77 ,  G06V10/776 ,  G06V10/82 ,  G06V10/94 ,  G06V20/68

CPC classification number: G06T7/136 ,  G06T7/0012 ,  G06T7/11 ,  G06T7/174 ,  G06V10/26 ,  G06V10/764 ,  G06V10/7715 ,  G06V10/776 ,  G06V10/82 ,  G06V10/95 ,  G06V20/68 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30188 ,  G06T2207/30242

Abstract: Existing techniques in precision farming comprise supervised event detection and need labeled training data which is tedious considering the large number of crops, differences therein and even larger number of diseases and pests. The present disclosure provides an unsupervised method and uses images of any size captured in an uncontrolled environment. The methods and systems disclosed find application in automatically localizing and classifying events, including health state and growth stage and also estimating an extent of manifestation of the event. Information of spatial continuity in pixels and boundaries in a given image is used to update the feature representation and label assignment to every pixel using a fully convolutional network. Back propagation of the pixel labels modified according to the output of a graph based method helps the neural network to converge and provide a time efficient solution.

公开(公告)号：US11880981B2

公开(公告)日：2024-01-23

申请号：US17446725

申请日：2021-09-02

Applicant: Tata Consultancy Services Limited

Inventor： Prakruti Vinodchandra Bhatt ,  Sanat Sarangi ,  Srinivasu Pappula ,  Avil Saunshi

IPC: G06T7/13 ,  G06T7/187 ,  G06V10/56 ,  G06V10/26 ,  G06T5/00 ,  G06F18/2413

CPC classification number: G06T7/13 ,  G06F18/24147 ,  G06T5/002 ,  G06T5/009 ,  G06T7/187 ,  G06V10/267 ,  G06V10/56 ,  G06T2207/30188

Abstract: This disclosure relates generally to estimating age of a leaf using morphological features extracted from segmented leaves. Traditionally, leaf age estimation requires a single leaf to be plucked from the plant and its image to be captured in a controlled environment. The method and system of the present disclosure obviates these needs and enables obtaining one or more full leaves from images captured in an uncontrolled environment. The method comprises segmenting the image to identify veins of the leaves that further enable obtaining the full leaves. The obtained leaves further enable identifying an associated plant species. The method also discloses some morphological features which are fed to a pre-trained multivariable linear regression model to estimate age of every leaf. The estimated leaf age finds application in estimation of multiple plant characteristics like photosynthetic rate, transpiration, nitrogen content and health of the plants.