公开(公告)号：US20250166042A1

公开(公告)日：2025-05-22

申请号：US18901093

申请日：2024-09-30

Applicant: Tata Consultancy Services Limited

Inventor： Jayantrao MOHITE ,  Dineshkumar Jang Bahadur SINGH ,  Suryakant Ashok SAWANT ,  Jay Prakash KUMAR ,  Siddhesh Deepak NAR ,  Jayshree Dnyaneshwar KAKAD ,  Srinivasu PAPPULA ,  Vaibhav Sadashiv LONKAR

IPC: G06Q30/0601

Abstract: The present disclosure provide a system and method for personalized recommendation and transaction of non-fungible tokens of livestock embryos. There is a challenge in uniquely identifying livestock embryos and tracking them authentically for their ownership and all the associated details about the donor male, female, their lineage and/or the like. The present disclosure leverages blockchain technology to create unique digital assets representing the physical livestock embryos and identified by a unique token. By utilizing smart contracts on a blockchain platform, secure creation, transfer, and ownership tracking of livestock embryo NFTs is enabled. Further, a machine learning based approach for personalized recommendation of the livestock embryos with associated costs to the user based on the available NFT data, domain knowledge about the breeding policy and needs of the user is provided. A marketplace transaction system for fair trading of the livestock embryo NFTs is disclosed.

公开(公告)号：US20190141604A1

公开(公告)日：2019-05-09

申请号：US16099936

申请日：2017-05-08

Applicant: Tata Consultancy Services Limited

Inventor： Sanat SARANGI ,  Srinivasu PAPPULA

IPC: H04W40/32

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：US20250069155A1

公开(公告)日：2025-02-27

申请号：US18785568

申请日：2024-07-26

Applicant: Tata Consultancy Services Limited

Inventor： Jayantrao MOHITE ,  Dineshkumar SINGH ,  Suryakant Ashok SAWANT ,  Sanat SARANGI ,  Vaibhav Sadashiv LONKAR ,  Mariappan SAKKAN ,  Srinivasu PAPPULA ,  Ajay MITTAL

IPC: G06Q40/12 ,  G06Q40/04 ,  G06Q50/02

Abstract: A method and system for dynamic value determination and performance based royalty calculation of non-fungible tokens (NFTs) created for agricultural assets is disclosed. The method enables reliable and authentic ownership tracking and the removal of frauds/biases affecting the valuation of the said asset(s), as all the transactions are recorded and visible to everybody on the platform. Various biases, such as location (or spatial), temporal or human judgment-based biases in the existing valuation systems are removed by having dynamic and performance-based valuation approach proposed in this invention. NFT valuations of farm diary and farm art have hardly been proposed in earlier works. Royalty or reward computations from agricultural NFTs has not been attempted. Thus, the method provides performance or creation-based (creation of IP, Knowledge base, Geographical Indication IP) royalties/rewards for the NFT owner or entities involved in the process.

公开(公告)号：US20220122347A1

公开(公告)日：2022-04-21

申请号：US17371650

申请日：2020-02-07

Applicant: Tata Consultancy Services Limited

Inventor： Prakruti Vinodchandra BHATT ,  Sanat SARANGI ,  Srinivasu PAPPULA

IPC: G06V10/70 ,  G06V20/68 ,  G06T7/11 ,  G06T7/174 ,  G06V10/25 ,  G06V10/22 ,  G06V10/77 ,  G06V10/82 ,  G06V10/776 ,  G06T7/00 ,  G06V10/94

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：US20240028957A1

公开(公告)日：2024-01-25

申请号：US18209080

申请日：2023-06-13

Applicant: Tata Consultancy Services Limited

Inventor： Jayantrao MOHITE ,  Suryakant Ashok SAWANT ,  Rishabh AGARWAL ,  Ankur PANDIT ,  Srinivasu PAPPULA

IPC: G06N20/00 ,  G06Q10/04

CPC classification number: G06N20/00 ,  G06Q10/04

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.

公开(公告)号：US20240013108A1

公开(公告)日：2024-01-11

申请号：US18216056

申请日：2023-06-29

Applicant: Tata Consultancy Services Limited

Inventor： Pankaj DOKE ,  Sujit Raghunath SHINDE ,  Akhilesh Chandra SRIVASTAVA ,  Karan Rajesh BHAVSAR ,  Srinivasu PAPPULA ,  Sanjay KIMBAHUNE

IPC: G06Q10/0631

CPC classification number: G06Q10/0631

Abstract: A method and system for synthesizing smartphone cue-cards representing socio-technical system (STS) service design prototyping based on a plurality of constraints has been provided. The system creates just in time, a dynamic visual design for senior and junior designers for displaying of patterns as digital Cue Cards based on human configured time constraint and novelty constraints all the while avoiding repeatability for the designer. Smartphone is utilized as a mechanism to host multiple cue cards and an interaction model which allows multiple cue-card-connectedness to jump across constraints of local-maxima/minima towards a global-maxima/minima. The method allows young designers get access to better long term memory (LTM) and senior designer getting access to faster LTM. The present disclosure helps senior designer get faster access to new patterns to reduce time for novel new interventions.

公开(公告)号：US20240029254A1

公开(公告)日：2024-01-25

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

CPC classification number: G06T7/0014 ,  G01N33/0098 ,  G06V20/90 ,  G06V20/188 ,  G06V10/762 ,  G06V20/13 ,  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：US20190220967A1

公开(公告)日：2019-07-18

申请号：US16022239

申请日：2018-06-28

Applicant: TATA CONSULTANCY SERVICES LIMITED

Inventor： Prakruti Vinodchandra BHATT ,  Sanat SARANGI ,  Srinivasu PAPPULA

IPC: G06T7/00

Abstract: The present disclosure addresses the technical problem of enabling automated inferencing of changes in spatio-temporal images by leveraging the high level robust features extracted from a Convolutional Neural Network (CNN) trained on varied contexts instead of data dependent feature methods. Unsupervised clustering on the high level features eliminates the cumbersome requirement of labeling the images. Since models are not trained on any specific context, any image may be accepted. Real time inferencing is enabled by a certain combination of unsupervised clustering and supervised classification. A cloud-edge topology ensures real time inferencing even when connectivity is not available by ensuring updated classification models are deployed on the edge. Creating a knowledge ontology based on adaptive learning enables inferencing of an incoming image with varying levels of precision. Precision farming may be an application of the present disclosure.

公开(公告)号：US20180018414A1

公开(公告)日：2018-01-18

申请号：US15648209

申请日：2017-07-12

Applicant: Tata Consultancy Services Limited

Inventor： Sandika BISWAS ,  Jayantrao MOHITE ,  Srinivasu PAPPULA

IPC: G06F17/50 ,  G06F17/11 ,  G06F17/18 ,  G06N99/00

CPC classification number: G06F17/5009 ,  A01N25/00 ,  G06F17/11 ,  G06F17/18 ,  G06N20/00 ,  G06Q10/04 ,  G06Q50/02

Abstract: Traditionally, forecasting models were developed using pest or disease instances collected through pest or disease surveillance. The present disclosure relates to pest forecasting using historical pesticide usage information thereby obviating need for voluminous and time consuming effort of collecting site specific data. Firstly forecasting models for different pests or diseases of different crops are generated based on historical data on pesticide usage and historical weather data collected for a geo-location under consideration. The model is validated and adapted with the current scenario of pests. Current scenario is captured using image samples sent from the field or farm through participatory sensing platform. The images are then analyzed to extract information like actual pest infestation in the field, severity, if there was infestation and the like. This analyses helps to derive the actual pest infestation instances in the field.

公开(公告)号：US20250069142A1

公开(公告)日：2025-02-27

申请号：US18787259

申请日：2024-07-29

Applicant: Tata Consultancy Services Limited

Inventor： Pankaj Harish DOKE ,  Karan Rajesh BHAVSAR ,  Sanjay Madhukar KIMBAHUNE ,  Srinivasu PAPPULA ,  Sujit Raghunath SHINDE

IPC: G06Q40/06 ,  G06F3/04815

Abstract: Unaddressed technical problem is how to make the window manager select and update the appropriate visual design given the Just-In-Time constraint to optimize Profit/Economic Goal for a Basic Emergent User and not have a locking/permanent binding on a particular Socio Economic Cohort (SEC) or Contract Management System Companies (CMSCs). A method and system is disclosed that provides interface layout to discover and optimize economics of information exchange of digitally virtualized physical space for a Basic Emergent User (BEU). A correlation score is determined based on correlation between i) the expected profit range provided by the BEU indicating the tolerance around the SP(selling price) and ii) the buying price(BP) and the tolerance specified by the SEC or the CMSC to identify a best match for the BEU based on goal provided by the BEU in terms of expected profit range and corresponding time range within which it is to be achieved.