Patents Assigned to Tata Consultancy Services Limited
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Patent number: 11977608Abstract: Traditional food quality monitoring systems fail to monitor the variation of food quality in real-time scenarios. Existing machine learning approaches require dedicated data models for different classes of food items due to differences in characteristics of different food items. Also, to generate such data models, a lot of annotated data is required per food item, which are expensive. The disclosure herein generally relates to monitoring and shelf-life prediction of food items, and, more particularly, to system and method for real-time monitoring and shelf-life prediction of food items. The system generates a data model using a knowledge graph indicative of a hierarchical taxonomy for a plurality of categories of the plurality of food items, which in turn contains metadata representing similarities in physio-chemical degradation pattern of different classes of the food items. This data model serves as a generic data model for real-time shelf-life prediction of different food items.Type: GrantFiled: November 1, 2021Date of Patent: May 7, 2024Assignee: TATA CONSULTANCY SERVICES LIMITEDInventors: Jayita Dutta, Parijat Deshpande, Manasi Samarth Patwardhan, Shirish Subhash Karande, Shankar Kausley, Priya Kedia, Shrikant Arjunrao Kapse, Beena Rai
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Patent number: 11977200Abstract: It is important to know the flow rates of oil and gas from individual wells in connected oil and gas wells. The existing methods for multiphase flow measurement are prohibitively expensive and used infrequently. The system is configured to ingest real-time and non-real-time data from a plurality of well data sources. Utilizing this data, a plurality of physics-guided data-driven well surveillance models run in real-time for forecasting a plurality of parameters including the flow rates of oil, gas and brine from individual wells, computing the health of well assets and performing fault detection and localization in well assets. The system is also configured to automatically compose a well performance optimization problem based on the current performance of the wells and health of well assets and solve the problem to identify optimal process settings for improving the operation of connected oil and gas wells.Type: GrantFiled: January 6, 2022Date of Patent: May 7, 2024Assignee: Tata Consultancy Services LimitedInventors: Sri Harsha Nistala, Tanmaya Singhal, Venkataramana Runkana
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Patent number: 11978537Abstract: Pathogens invade and infect humans. Understanding the infection mechanism is essential for determining targets for new therapeutics. Existing methods provide too many false positive results. A method and system for predicting protein-protein interaction between a host and a pathogen has been provided. The disclosure provides a pipeline for predicting HPIs, which is a combination of biological knowledge-based filters, domain-based filter and sequence-based predictions. Biologically feasible interactions are only possible when both the proteins share common localization and overlapping expression profiles. This observation was used as the first filter to remove biologically irrelevant HPIs. Proteins interact with each other through domains. Both interacting and non-interacting protein pairs provide valuable information about the probability of protein-protein interactions and hence both were used to derive statistical inferences to remove improbable HPIs.Type: GrantFiled: November 17, 2020Date of Patent: May 7, 2024Assignee: Tata Consultancy Services LimitedInventors: Arijit Roy, Dibyajyoti Das, Gopalakrishnan Bulusu
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Publication number: 20240143299Abstract: This disclosure relates generally to method and system for incremental functional approach-based dataflow analysis. Static dataflow analysis can take hours to days depending on size and complexity of the code. In today's agile development environment faster analysis is required which can handle incremental changes to the code in an efficient manner. The method includes by performing a static dataflow analysis over a set of functions of a source code. Further, obtains a set of impacted functions from the source code and executes a dataflow analysis over the set of impacted functions of the source code. The method performs an incremental functional approach-based dataflow analysis over the set of impacted functions including an incremental bottom-up analysis and an incremental top-down analysis. The method efficiently updates results of dataflow analysis in response to incremental changes which is fast and scalable and minimizes the number of procedures by comparing summaries across the versions.Type: ApplicationFiled: September 8, 2023Publication date: May 2, 2024Applicant: Tata Consultancy Services LimitedInventors: Anushri JANA, Bharti CHIMDYALWAR, Ramanathan VENKATESH, Shrawan KUMAR
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Publication number: 20240142962Abstract: Conventionally, root cause analysis and process documentation in process industries has been manually performed resulting in time consuming effort, cost, and human resources. Moreover, in the event of failure, looking at such document and searching for possible root causes is practically impossible in the interest of time and cost associated. Systems and methods of the present disclosure systematically curate knowledge of industrial process(es) from various sources and generate process ontology via meta model(s). Root cause graph (RCG) is created wherein the RCG corresponds to process and root cause and failure modes in the process. The RCG is then transformed to machine instructions which are executed for root cause analysis in real time. The created graphs/knowledge also help in identifying conflicting knowledge or redundant knowledge. Present disclosure enables root cause analysis as soon as a failure occurs or as the systems show or indicate a tendency towards failure.Type: ApplicationFiled: October 19, 2020Publication date: May 2, 2024Applicant: Tata Consultancy Services LimitedInventors: DILSHAD AHMAD, PURUSHOTTHAM GAUTHAM BASAVARSU, HRISHIKESH NILKANTH KULKARNI, CHETAN PREMKUMAR MALHOTRA, THANGA JAWAHAR KALIDOSS, SWAMY DOSS KOLAPPAN
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Publication number: 20240143980Abstract: Conventional transport mode detection relies either on GPS data or uses supervised learning for transport mode detection, requiring labelled data with hand crafted features. Embodiments of the present disclosure provide a method and system for identification of transport modes of commuters via unsupervised learning implemented using a multistage learner. Unlabeled time series data received from accelerometer of commuters mobiles from a diversified population is processed using a unique journey segment detection technique to eliminate redundant data corresponding to stationary segments of commuter or user. The non-stationary journey segments are represented using domain generalizable Invariant Auto-Encoded Compact Sequence (I-AECS), which is a learned compact representation encompassing the encoded best diversity and commonality of latent feature representation across diverse users and cities.Type: ApplicationFiled: September 25, 2023Publication date: May 2, 2024Applicant: Tata Consultancy Services LimitedInventors: SOMA BANDYOPADHYAY, ARPAN PAL, RAMESH KUMAR RAMAKRISHNAN, ANISH DATTA
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Publication number: 20240140244Abstract: Disadvantage of state-of-the-art scheduling mechanisms for Electric Vehicle (EV) charging is that they fail to accommodate dynamic requirements in terms of charging needs. The disclosure herein generally relates to EV fleet charging, and, more particularly, to a method and system for Electric Vehicle (EV) fleet charging by accommodating one or more dynamic requirements. The system initially generates a base charging plan for a fleet of EVs. Further, the system checks if the base charging plan is to be modified to accommodate one or more dynamic charging requirements obtained. Upon determining that the base charging plan is to be modified, the system modifies the base charging plan till a) no more vehicles are left to charge, or b) all of a plurality of chargers have an assignment.Type: ApplicationFiled: September 28, 2023Publication date: May 2, 2024Applicant: Tata Consultancy Services LimitedInventors: Kshitij GARG, Ajay Narayanan, Prasant Kumar Misra, Arunchandar Vasan, Vivek Bandhu, Debarupa Das
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Publication number: 20240143979Abstract: Synthetic data is an annotated information that computer simulations or algorithms generate as an alternative to real-world data. synthetic data is created in digital worlds rather than collected from or measured in the real world. Embodiments herein provide a method and system for generating synthetic data with domain adaptable features using a neural network. The system is configured to receive seed data from a source domain as an input data. The seed data is considered as a normal state of a machine. The normal state, which is an initial stage of the source domain, consists of a set of features with a certain range of values. Further, a neural network based model is used to generate high quality data with adaptation of the domain specific features. To obtain large amount data for training robust deep learning models to adapt domains emphasizing set of features/providing higher importance selectively.Type: ApplicationFiled: September 11, 2023Publication date: May 2, 2024Applicant: Tata Consultancy Services LimitedInventors: SOMA BANDYOPADHYAY, ANISH DATTA, CHIRABRATA BHAUMIK, TAPAS CHAKRAVARTY, ARPAN PAL, RIDDHI PANSE, MUDASSIR ALI SABIR
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Publication number: 20240145037Abstract: This disclosure relates generally to identifying candidate genome sequences. Next generation sequencing (NGS) is a massively parallel sequencing technique for identifying candidate genome sequences. The current state-of-the-art techniques for identifying candidate genome sequences does not efficiently address the problem of distributing abundance values across several related strains that are present in the reference under the same species. The disclosed technique proposes a technique for identifying candidate genome sequences by estimating coverage. The disclosed technique includes a local search-based optimization to compute maximum likelihood-based estimates using constrains on coverage/cardinality thresholds for identifying candidate genome sequences.Type: ApplicationFiled: September 20, 2023Publication date: May 2, 2024Applicant: Tata Consultancy Services LimitedInventors: VIDUSHI WALIA, SAIPRADEEP VANGALA GOVINDAKRISHNAN, NAVEEN SIVADASAN, RAJGOPAL SRINIVASAN
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Publication number: 20240133042Abstract: Metal corrosion is a ubiquitous phenomenon costing the global economy, trillions of dollars annually. Conventional corrosion inhibitor compounds are either not so effective or require huge amount of inhibitor for adequate protection. The present disclosure addresses the problem of acid corrosion of iron and iron alloys which is relevant for a wide variety of industries such as oil and gas production and acid pickling etc. The technical solution provided in the present disclosure is a new corrosion inhibitor composition including Naphthalene-1-thiocarboxamide for iron and iron alloys in HCl media. This is specifically relevant for acid well stimulation in the oil and gas industries.Type: ApplicationFiled: July 7, 2023Publication date: April 25, 2024Applicant: Tata Consultancy Services LimitedInventors: DHARMENDR KUMAR, VENKATA MURALIDHAR KANAMARLAPUDI, VINAY JAIN, BEENA RAI
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Patent number: 11966498Abstract: This disclosure relates to a system and method for at source data masking and discovery of unique identifier for at-source masking. The method reads a table of production database comprising sensitive column from a source database for at source data masking. A unique identifier column is identified, and a temporary table is created which has three or more columns. Columns of temporary table comprises a sensitive column from the table of production database, a column for masked data of sensitive column and a unique identifier column. Sensitive column of the temporary table is masked using a known masking technique and the original data of the sensitive column and the masked data of the sensitive column is inserted into the temporary table. Finally, the production database is updated with the masked data of the sensitive column.Type: GrantFiled: September 2, 2021Date of Patent: April 23, 2024Assignee: TATA CONSULTANCY SERVICES LIMITEDInventors: Nandita Babu, Ashim Roy, Shirish Damle, Rupali Kulkarni
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Patent number: 11963488Abstract: 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: GrantFiled: January 3, 2022Date of Patent: April 23, 2024Assignee: TATA CONSULTANCY SERVICES LIMITEDInventors: Ankur Pandit, Jayantrao Mohite, Suryakant Ashok Sawant, Srinivasu Pappula
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Patent number: 11966674Abstract: Artificially structured materials are created artificially and offer customizable properties. They are being used in various fields. A system and method for designing artificially structured materials have been provided. The system and method is based on neural networks for approximating the electromagnetic (EM) responses of the artificially structured materials. By treating the EM spectral data as time-varying sequences and the inverse problem as a single-input, multi-output model, the architecture is forced to learn the geometry of the designs from the training data as opposed to abstract features thereby addressing both the forward and the inverse design problems.Type: GrantFiled: March 31, 2021Date of Patent: April 23, 2024Assignee: TATA CONSULTANCY SERVICES LIMITEDInventors: Parama Pal, Prajith Pillai, Rinu Chacko, Deepak Shyamsunder Jain, Beena Rai
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Patent number: 11967133Abstract: Embodiments of the present disclosure provide a method and system for co-operative and cascaded inference on the edge device using an integrated Deep Learning (DL) model for object detection and localization, which comprises a strong classifier trained on largely available datasets and a weak localizer trained on scarcely available datasets, and work in coordination to first detect object (fire) in every input frame using the classifier, and then trigger a localizer only for the frames that are classified as fire frames. The classifier and the localizer of the integrated DL model are jointly trained using Multitask Learning approach. Works in literature hardly address the technical challenge of embedding such integrated DL model to be deployed on edge devices. The method provides an optimal hardware software partitioning approach for components or segments of the integrated DL model which achieves a tradeoff between latency and accuracy in object classification and localization.Type: GrantFiled: October 12, 2021Date of Patent: April 23, 2024Assignee: TATA CONSULTANCY SERVICES LIMITEDInventors: Swarnava Dey, Jayeeta Mondal, Jeet Dutta, Arpan Pal, Arijit Mukherjee, Balamuralidhar Purushothaman
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Publication number: 20240126830Abstract: Machine Learning approaches in literature for determining optimal solver-preconditioner-smoother for solving matrix equations in computer modelling of any systems are directly dependent on matrix property calculation as an intermediate step. However, in CFD domain, this matrix system is generated from simulation input parameters. Also, part of simulation parameter's relation with the matrix equations can be derived from the theory. Embodiments of the present disclosure provide a method and system for prediction of fastest solver combination for solution of matrix equations during CFD simulations. The system trains a Machine Learning (ML) model using a set of relevant input parameters, based on domain knowledge of a CFD problem of interest, as a plurality of input features. The ML model is a multi-class classification model for the prediction of solver combination taking the CFD simulation parameters as an input.Type: ApplicationFiled: August 29, 2023Publication date: April 18, 2024Applicant: Tata Consultancy Services LimitedInventors: HRISHIKESH NILKANTH KULKARNI, DILSHAD AHMAD
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Publication number: 20240126943Abstract: Simulation of dynamic physical systems is done using iterative solvers. However, this iterative process is a time consuming and compute intensive process and, for a given set of simulation parameters, the solution does not always converge to a physically meaningful solution, resulting in huge waste of man hours and computation resource. Embodiments herein provide a method and system for stabilizing a diverged numerical simulation and accelerating a converged numerical simulation by changing one or more control parameters. An automatic monitoring mechanism of residue history (to interpret convergence or divergence) and a subsequent control logic to auto-tune the under-relaxation factor would help in stabilizing a diverging simulation and reaching faster convergence by accelerating converging simulation.Type: ApplicationFiled: September 1, 2023Publication date: April 18, 2024Applicant: Tata Consultancy Services LimitedInventors: Mithilesh Kumar MAURYA, Dighanchal BANERJEE, Dilshad AHMAD, Sounak DEY
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Publication number: 20240127158Abstract: This disclosure relates generally to method and system for generating key performance indicator prediction model for multi-cloud applications. The disclosed method determines an optimized resource model and a predictive cost structure for one or more multi-cloud applications. The method receives a composite usage request to obtain a current resource consumption metrics and a cost structure for each cloud application identifier (ID). Further, a set of cloud provider API endpoints are invoked to obtain a plurality of usage tracking metrics. Further, a plurality of views are generated for each cloud application ID by processing every record associated with each API response file with allocated resource data. Then, a KPI prediction model is generated by leveraging autoregressive integrated moving average on the KPI time series data to determine an optimized resource model and a cost structure.Type: ApplicationFiled: October 16, 2023Publication date: April 18, 2024Applicant: Tata Consultancy Services LimitedInventors: Sujoy BANERJEE, Tanmoy BANERJEE
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Publication number: 20240129028Abstract: The present disclosure addresses unresolved problems of task scheduling by adding redundancy in a collection task schedule generated by a ground control station. Embodiments of the present disclosure provide a randomization based redundant collection task scheduling for mitigating occlusions in sensing by small satellite constellations. The randomization based redundant collection task scheduling algorithm receives as input a set of region of observations tessellated into sub-regions, and then collection opportunities for each sub-region is computed based on satellite tracks data. Further, a sub-set of collection opportunities is determined from all the possible collection tasks for each sub-region to further generate the collection task schedule for each of the region of observation.Type: ApplicationFiled: October 3, 2023Publication date: April 18, 2024Applicant: Tata Consultancy Services LimitedInventors: HIMADRI SHEKHAR PAUL, SWAGATA BISWAS
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Publication number: 20240127309Abstract: E-commerce industry is currently expanding rapidly, worldwide. A process of generating product copy for grocery items, which is very challenging as food items, do not have features in common, unlike fashion products. A data associated with one or more grocery products is received as an input. The data is processed to obtain one or more sorted similar grocery products. One or more relevant attributes and allergen information associated with the one or more sorted similar grocery products are extracted. A vocabulary model is created based the one or more relevant attributes and the allergen information associated with the one or more sorted similar grocery products. The vocabulary model is validated based on one or more assigned weights on training data. The one or more descriptive copies associated with grocery products are generated by mapping the validated vocabulary model with the training data.Type: ApplicationFiled: January 30, 2023Publication date: April 18, 2024Applicant: Tata Consultancy Service LimitedInventors: Bagya Lakshmi VASUDEVAN, Sudesna BARUAH, Mayur PATIDAR, Meghna Kishor MAHAJAN
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Publication number: 20240127925Abstract: This is a method and a system for designing a personalized therapeutic intervention for an individual. Each individual has a unique composition of microbiome in the gut, one probiotic or dietary regimen may not have same efficacy in different individuals. The disclosure recommends a personalized therapeutic intervention for improving gut health of an individual by designing personalized therapeutics and diet based on functions of microbiome. The personalized therapeutic intervention is recommended based on several steps including generating a set of knowledge bases, identifying a change in the gut health of an individual by monitoring the gut samples and recommending a personalized therapeutic intervention. The personalized therapeutic intervention comprises at least one of a prebiotic, a probiotic and an optimized diet, wherein the optimized diet is estimated based on optimizing a gut food score, where the gut food score is computed based on the change in the gut health of an individual.Type: ApplicationFiled: February 3, 2022Publication date: April 18, 2024Applicant: Tata Consultancy Services LimitedInventors: SWADHA ANAND, SHARMILA SHEKHAR MANDE, RASHMI SINGH, HARRISHAM KAUR, CHANDRANI BOSE, KUNTAL KUMAR BHUSAN, KRISHANU DAS BAKSI