公开(公告)号：US20210405009A1

公开(公告)日：2021-12-30

申请号：US17296967

申请日：2019-10-25

Applicant: Tata Consultancy Services Limited

Inventor： Jayita DUTTA ,  Parijat DESHPANDE ,  Beena RAI

IPC: G01N33/02 ,  G06Q10/08 ,  G05B13/02 ,  G06T7/00

Abstract: Health of perishable commodities such as eatables deteriorate over time. State of art systems for health monitoring of perishable commodities rely on measurement of limited parameters and also fail to consider effect of environment on the health of the perishable commodities. Disclosed herein is an apparatus and method for multimodal sensing and monitoring of perishable commodities. The apparatus allows to change environment within a closed chamber in which the perishable commodity being monitored is kept, and in turn allows to generate health data in different environment settings. This data is used to generate a health model. Data collected in real-time are processed with the health model to establish a correlation with at least one image, wherein each of such images in the health model represents certain health state. Based on the established correlation, health of the perishable commodity is determined.

公开(公告)号：US20220120693A1

公开(公告)日：2022-04-21

申请号：US17504823

申请日：2021-10-19

Applicant: Tata Consultancy Services Limited

Inventor： Jayita DUTTA ,  Parijat DESHPANDE ,  Beena RAI

IPC: G01N21/78 ,  G06Q10/08 ,  G01N33/02

Abstract: State of the art food quality measurement techniques fail to determine quality of the food item once it is packed and sealed in a container. The disclosure herein generally relates to food quality prediction, and, more particularly, to a system and method for predicting food quality in a non-invasive manner. A Color Changing Indicator (CCI) in a biosensor strip forming a component of the enclosed package in which the liquid food item is packed, changes color when came in contact with the liquid food item. For different quality of the liquid food item the CCI has different color. Based on the color of the CCI, and ambient temperature and relative humidity at the time the color of the CCI is determined, a machine learning model determines rate of deterioration of the liquid food item, and then predicts remaining shelf life, which in turn provided as output to a user.

公开(公告)号：US20200281220A1

公开(公告)日：2020-09-10

申请号：US16809260

申请日：2020-03-04

Applicant: Tata Consultancy Services Limited

Inventor： Jayita DUTTA ,  Parijat DESHPANDE ,  Beena RAI

IPC: A23B7/152 ,  G05B13/02

Abstract: This disclosure relates generally to managing ripening conditions of climacteric fruits and more particularly to a system and method for managing ripening conditions of climacteric fruits using Artificial neural network (ANN) model. The method includes obtaining levels of environment condition parameters associated with ripening of the climacteric fruit over time at periodic intervals by using an enclosure enclosing the climacteric fruit. A respiration rate of the climacteric fruit is computed based at least on the levels of the environment condition parameters using Michaelis Menten kinetics model. A level of ethylene is monitored to determine a climacteric peak of Ethylene for the climacteric fruit. The climacteric peak is indicative of complete natural ripening of the climacteric fruit. An ANN model predicts optimal ripening condition of the climacteric fruit based on the respiration rate of the climacteric fruit and the climacteric peak of ethylene.

公开(公告)号：US20200250531A1

公开(公告)日：2020-08-06

申请号：US16783755

申请日：2020-02-06

Applicant: Tata Consultancy Services Limited

Inventor： Beena RAI ,  Jayita DUTTA ,  Parijat DESHPANDE ,  Shankar Balajirao KAUSLEY ,  Shirish Subhash KARANDE ,  Manasi Samarth PATWARDHAN ,  Shashank Madhukar DESHMUKH

IPC: G06N3/08 ,  G06N3/04

Abstract: 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.

公开(公告)号：US20220205905A1

公开(公告)日：2022-06-30

申请号：US17562133

申请日：2021-12-27

Applicant: Tata Consultancy Services Limited

Inventor： Beena RAI ,  Jayita DUTTA ,  Parijat DESHPANDE

IPC: G01N21/359 ,  G01N33/04

Abstract: State of the art food quality measurement techniques fail to determine quality of the food item once it is packed and sealed in an enclosed package. The disclosure herein generally relates to food quality prediction, and, more particularly, to a system and method for predicting liquid food quality in a non-invasive manner. A near infra-red (NIR) radiation is transmitted through a semi-transparent opening configured on an enclosed package containing a liquid food item and the resulting NIR reflection spectra is collected. The quality of the liquid food item is estimated by correlating a plurality of features derived from the NIR reflection spectra with the concentration of the biomarker contained in the liquid food item, using a trained machine learning model and the remaining shelf life of the liquid food item is estimated based on the concentration of the biomarker.

公开(公告)号：US20200251229A1

公开(公告)日：2020-08-06

申请号：US16783897

申请日：2020-02-06

Applicant: Tata Consultancy Services Limited

Inventor： Beena RAI ,  Jayita DUTTA ,  Parijat DESHPANDE ,  Shankar Balajirao KAUSLEY ,  Shirish Subhash KARANDE ,  Manasi Samarth PATWARDHAN ,  Shashank Madhukar DESHMUKH

IPC: G16Y40/10 ,  G16Y20/20 ,  G16Y10/05 ,  G06K9/62 ,  G06N3/08 ,  G06N3/04 ,  G06N20/20 ,  G06N20/10

Abstract: 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.

公开(公告)号：US20190008475A1

公开(公告)日：2019-01-10

申请号：US15912234

申请日：2018-03-05

Applicant: Tata Consultancy Services Limited

Inventor： Shreyasi DATTA ,  Anirban DUTTA CHOUDHURY ,  Parijat DESHPANDE ,  Sakyajit BHATTACHARYA ,  Arpan PAL

IPC: A61B7/00 ,  A61B7/04 ,  A61B5/00

Abstract: Identification of pulmonary diseases involves accurate auscultation as well as elaborate and expensive pulmonary function tests. Also, there is a dependency on a reference signal from a flowmeter or need for labelled respiratory phases. The present disclosure provides extraction of frequency and time-frequency domain lung sound features such as spectral and spectrogram features respectively that enable classification of healthy and abnormal lung sounds without the dependencies of prior art. Furthermore extraction of wavelet and cepstral features improves accuracy of classification. The lung sound signals are pre-processed prior to feature extraction to eliminate heart sounds and reduce computational requirements while ensuring that information providing adequate discrimination between healthy and abnormal lung sounds is not lost.

公开(公告)号：US20180038954A1

公开(公告)日：2018-02-08

申请号：US15552225

申请日：2016-02-16

Applicant: Tata Consultancy Services Limited

Inventor： Parijat DESHPANDE ,  Ramu VEMPADA ,  Ranjan DASGUPTA ,  Arpan PAL ,  Dibyendu ROY

IPC: G01S15/52 ,  G08B29/18 ,  G08B13/16

CPC classification number: G08B13/1672 ,  G01N2291/045 ,  G01N2291/26 ,  G01S15/523 ,  G08B13/1636 ,  G08B13/1681 ,  G08B29/186

Abstract: An acoustic array system for anomaly detection is provided. The acoustic array system (100) performs a scan (or a progressive scan of frequencies) of a given volume by transmitting one or more signals, and receives one or more reflected signals from objects within the volume. The reflected signals are then amplified and converted to a set of digital signals. Features of the set of digital signals are extracted both in time and frequency domains. The acoustic array system (100) further performs a comparison of these set of digital extracted features with the reflected signals via machine learning techniques. Based on the comparison, the acoustic array system detects one or more anomalies.