Patents by Inventor Manasi Samarth PATWARDHAN
Manasi Samarth PATWARDHAN 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).
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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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Publication number: 20240119046Abstract: This disclosure relates generally to program synthesis for weakly-supervised multimodal question answering using filtered iterative back-translation (FIBT). Existing approaches for chart question answering mainly address structural, visual, relational, or simple data retrieval queries with fixed-vocabulary answers. The present disclosure implements a two-stage approach where, in first stage, a computer vision pipeline is employed to extract data from chart images and store in a generic schema. In second stage, SQL programs for Natural Language (NL) queries are generated in dataset by using FIBT. To adapt forward and backward models to required NL queries, a Probabilistic Context-Free Grammar is defined, whose probabilities are set to be inversely proportional to SQL programs in training data and sample programs from it.Type: ApplicationFiled: August 22, 2023Publication date: April 11, 2024Applicant: Tata Consultancy Services LimitedInventors: Shabbirhussain Hamid BHAISAHEB, Shubham Singh Paliwal, Manasi Samarth Patwardhan, Rajaswa Ravindra Patil, Lovkesh Vig, Gautam Shroff
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Publication number: 20240095606Abstract: This disclosure relates generally to method and system for predicting shelf life of perishable food items. In supply chain management, current technology provides limited capability in providing relation between visual image of food item and a quality parameter value at different storage conditions. The system includes a quality parameter prediction module and a shelf life prediction module. The method obtains input data from user comprising a visual data and a storage data of each food item. The quality parameter prediction module determines a current quality parameter value of the food item from a look-up table. The shelf life prediction module predicts the shelf life of food item based on the current quality parameter value, a critical quality parameter value and the storage data. The look-up table comprising a plurality of weather zones are generated based on relationship dynamics between the visual image of food item and the quality parameter value.Type: ApplicationFiled: August 22, 2023Publication date: March 21, 2024Applicant: Tata Consultancy Services LimitedInventors: PRIYA KEDIA, SHANKAR KAUSLEY, MANASI SAMARTH PATWARDHAN, SHIRISH SUBHASH KARANDE, BEENA RAI, JAYITA DUTTA, PARIJAT DESHPANDE, ANAND SRIRAMAN, SHRIKANT ARJUNRAO KAPSE
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Patent number: 11488017Abstract: This disclosure relates generally to a system and method for monitoring and quality evaluation of perishable food items in quantitative terms. Current technology provides limited capability for controlling environmental conditions surrounding the food items in real-time or any quantitative measurement for the degree of freshness of the perishable food items. The disclosed systems and methods facilitate in quantitative determination of freshness of food items by utilizing sensor data and visual data obtained by monitoring the food item. In an embodiment, the system utilizes a pre-trained CNN model and a RNN model, where the pertained CNN model is further fine-tined while training the RNN model to provide robust quality monitoring of the food items. In another embodiment, a rate kinetic based model is utilized for determining reaction rate order of the food item at a particular post-harvest stage of the food item so as to determine the remaining shelf life thereof.Type: GrantFiled: February 6, 2020Date of Patent: November 1, 2022Assignee: Tata Consultancy Services LimitedInventors: Beena Rai, Jayita Dutta, Parijat Deshpande, Shankar Balajirao Kausley, Shirish Subhash Karande, Manasi Samarth Patwardhan, Shashank Madhukar Deshmukh
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Patent number: 11430576Abstract: This disclosure relates generally to a system and method for monitoring and quality evaluation of perishable food items in quantitative terms. Current technology provides limited capability for controlling environmental conditions surrounding the food items in real-time or any quantitative measurement for the degree of freshness of the perishable food items. The disclosed systems and methods facilitate in quantitative determination of freshness of food items by utilizing sensor data and visual data obtained by monitoring the food item. In an embodiment, the system utilizes a pre-trained CNN model and a RNN model, where the pertained CNN model is further fine-tined while training the RNN model to provide robust quality monitoring of the food items. In another embodiment, a rate kinetic based model is utilized for determining reaction rate order of the food item at a particular post-harvest stage of the food item so as to determine the remaining shelf life thereof.Type: GrantFiled: February 6, 2020Date of Patent: August 30, 2022Assignee: TATA CONSULTANCY SERVICES LIMITEDInventors: Beena Rai, Jayita Dutta, Parijat Deshpande, Shankar Balajirao Kausley, Shirish Subhash Karande, Manasi Samarth Patwardhan, Shashank Madhukar Deshmukh
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Publication number: 20220147755Abstract: 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: ApplicationFiled: November 1, 2021Publication date: May 12, 2022Applicant: 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: 11120228Abstract: This disclosure relates generally to data processing, and more particularly to a method and system for generating ground truth labels for ambiguous domain specific tasks. The system generates reference data corresponding to a regulation statement being processed, using a crowd sourcing mechanism and then processes the reference data using an Expectation Maximization (EM) model. The EM model determines consensus with respect to ambiguity of terms/phrases, validity of questions, and validity of answers, and then based on the determined consensus, provides questions and answers to disambiguate the regulation statement.Type: GrantFiled: July 3, 2019Date of Patent: September 14, 2021Assignee: Tata Consultancy Services LimitedInventors: Manasi Samarth Patwardhan, Abhishek Sainani, Shirish Karande, Smita Ghaisas, Richa Sharma
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Publication number: 20200250531Abstract: This disclosure relates generally to a system and method for monitoring and quality evaluation of perishable food items in quantitative terms. Current technology provides limited capability for controlling environmental conditions surrounding the food items in real-time or any quantitative measurement for the degree of freshness of the perishable food items. The disclosed systems and methods facilitate in quantitative determination of freshness of food items by utilizing sensor data and visual data obtained by monitoring the food item. In an embodiment, the system utilizes a pre-trained CNN model and a RNN model, where the pertained CNN model is further fine-tined while training the RNN model to provide robust quality monitoring of the food items. In another embodiment, a rate kinetic based model is utilized for determining reaction rate order of the food item at a particular post-harvest stage of the food item so as to determine the remaining shelf life thereof.Type: ApplicationFiled: February 6, 2020Publication date: August 6, 2020Applicant: Tata Consultancy Services LimitedInventors: Beena RAI, Jayita DUTTA, Parijat DESHPANDE, Shankar Balajirao KAUSLEY, Shirish Subhash KARANDE, Manasi Samarth PATWARDHAN, Shashank Madhukar DESHMUKH
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Publication number: 20200251229Abstract: This disclosure relates generally to a system and method for monitoring and quality evaluation of perishable food items in quantitative terms. Current technology provides limited capability for controlling environmental conditions surrounding the food items in real-time or any quantitative measurement for the degree of freshness of the perishable food items. The disclosed systems and methods facilitate in quantitative determination of freshness of food items by utilizing sensor data and visual data obtained by monitoring the food item. In an embodiment, the system utilizes a pre-trained CNN model and a RNN model, where the pertained CNN model is further fine-tined while training the RNN model to provide robust quality monitoring of the food items. In another embodiment, a rate kinetic based model is utilized for determining reaction rate order of the food item at a particular post-harvest stage of the food item so as to determine the remaining shelf life thereof.Type: ApplicationFiled: February 6, 2020Publication date: August 6, 2020Applicant: Tata Consultancy Services LimitedInventors: Beena RAI, Jayita DUTTA, Parijat DESHPANDE, Shankar Balajirao KAUSLEY, Shirish Subhash KARANDE, Manasi Samarth PATWARDHAN, Shashank Madhukar DESHMUKH
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Publication number: 20200104545Abstract: This disclosure relates generally to data processing, and more particularly to a method and system for generating ground truth labels for ambiguous domain specific tasks. The system generates reference data corresponding to a regulation statement being processed, using a crowd sourcing mechanism and then processes the reference data using an Expectation Maximization (EM) model. The EM model determines consensus with respect to ambiguity of terms/phrases, validity of questions, and validity of answers, and then based on the determined consensus, provides questions and answers to disambiguate the regulation statement.Type: ApplicationFiled: July 3, 2019Publication date: April 2, 2020Applicant: Tata Consultancy Services LimitedInventors: Manasi Samarth PATWARDHAN, Abhishek SAINANI, Shirish KARANDE, Smita GHAISAS, Richa SHARMA