公开(公告)号：US20140046144A1

公开(公告)日：2014-02-13

申请号：US13965523

申请日：2013-08-13

Applicant: Tata Consultancy Services Limited

Inventor： Srinivasan Jayaraman ,  Kriti Kumar ,  Balamuralidhar Purushothaman

IPC: A61B5/16

CPC classification number: A61B5/165 ,  A61B5/0006 ,  A61B5/0077 ,  A61B5/0205 ,  A61B5/02405 ,  A61B5/0245 ,  A61B5/0456 ,  A61B5/1116 ,  A61B5/486 ,  A61B5/7253 ,  A61B5/7264 ,  A61B2503/24 ,  A61B2576/00 ,  G06K9/0053 ,  G06K2009/00939

Abstract: The present subject matter relates to a computer implemented method for real time determination of stress levels of an individual. The method includes receiving at least one stream of physiological data from at least one primary sensor for a predetermined duration, and preprocessing the at least one stream of physiological data to extract physiological parameters, where the preprocessing includes performing a preliminary analysis on the at least one stream of physiological data. The method further includes determining a stress level of the individual based on at least the physiological parameters, wherein the determining comprises performing a statistical analysis on the physiological parameters.

Abstract translation: 本主题涉及一种用于实时确定个人的压力水平的计算机实现方法。 该方法包括从至少一个主传感器接收至少一个生理数据流预定的持续时间，以及预处理所述至少一个生理数据流以提取生理参数，其中所述预处理包括对所述至少一个 生理数据流。 该方法还包括基于至少生理参数来确定个体的压力水平，其中确定包括对生理参数进行统计分析。

公开(公告)号：US10467533B2

公开(公告)日：2019-11-05

申请号：US15272025

申请日：2016-09-21

Applicant: Tata Consultancy Services Limited

Inventor： Kriti Kumar ,  Naveen Kumar Thokala ,  Ravikumar Karumanchi ,  Mariswamy Girish Chandra ,  Kalyan Prathap Kamakolanu Guru ,  Suresh Upparapalli ,  Madhusudhan Kamma Chavala Chowdary ,  Prasanna Madhavrao Kulkarni ,  Pareshkumar Bhawanishankar Sharda

IPC: G06K9/62 ,  G06N5/02 ,  G05B23/02 ,  G06N20/00 ,  G06Q10/04 ,  G06N99/00

Abstract: System and method for predicting enterprise system response time is disclosed. System pre-processes causal variables of historical output time series data to select subset of causal variables by applying regression techniques to obtain significant causal variables. Historical output time series data shows response time of enterprise system. System derives dummy variables from historical output time series data using threshold based method. Dummy variables are specific to peak detection and trough detection in historic output time series data. System trains predictive model using historical output time series data, significant causal variables, and dummy variables to generate trained predictive model and predictive model designed using machine learning technique selected based on forecast methodology used for forecasting input time series data. System predicts enterprise system response time by using trained predictive model, input time series data or lag between input time series data and historical output time series data.

公开(公告)号：US11270429B2

公开(公告)日：2022-03-08

申请号：US16900106

申请日：2020-06-12

Applicant: Tata Consultancy Services Limited

Inventor： Achanna Anil Kumar ,  Rishab Khawad ,  Riddhi Panse ,  Andrew Gigie ,  Tapas Chakravarty ,  Kriti Kumar ,  Saurabh Sahu ,  Mariswamy Girish Chandra

IPC: G06T7/00 ,  G01N21/88

Abstract: The disclosure herein generally relates to image processing, and, more particularly, to a method and system for impurity detection using multi-modal image processing. This system uses a combination of polarization data, and at least one of a depth data and an RGB image data to perform the impurity material detection. The system uses a graph fusion based approach while processing the captured images to detect presence of the impurity material, and accordingly alert the user.

公开(公告)号：US20210011062A1

公开(公告)日：2021-01-14

申请号：US16813794

申请日：2020-03-10

Applicant: Tata Consultancy Services Limited

Inventor： Kriti Kumar ,  Mariswamy Girish CHANDRA ,  Achanna Anil KUMAR ,  Naveen Kumar THOKALA

IPC: G01R21/133 ,  G06N20/00 ,  G06N7/00

Abstract: This disclosure relates generally to method and system for low sampling rate electrical load disaggregation. At low sampling rates, disaggregation of energy load is challenging due to unavailability of events and signatures of the constituent loads. The disclosed energy disaggregation technique receives aggregated load data from a utility meter and sequentially obtains training data for determining disaggregated energy load at low sampling rate. Dictionaries are used to characterize the different loads in terms of power values and time of operation. The obtained dictionary coefficients are treated as graph signals and graph smoothness is used for propagating the coefficients from the training phase to the test phase by formulating an optimization model. The derivation of the optimization model identifies the load of interest and estimate their power consumption based on optimization model constraints. This method achieves accuracy greater than 70% for the loads of interest at low sampling rates.

公开(公告)号：US11119132B2

公开(公告)日：2021-09-14

申请号：US16813794

申请日：2020-03-10

Applicant: Tata Consultancy Services Limited

Inventor： Kriti Kumar ,  Mariswamy Girish Chandra ,  Achanna Anil Kumar ,  Naveen Kumar Thokala

IPC: G01R21/133 ,  G06N20/00 ,  G06N7/00

Abstract: This disclosure relates generally to method and system for low sampling rate electrical load disaggregation. At low sampling rates, disaggregation of energy load is challenging due to unavailability of events and signatures of the constituent loads. The disclosed energy disaggregation technique receives aggregated load data from a utility meter and sequentially obtains training data for determining disaggregated energy load at low sampling rate. Dictionaries are used to characterize the different loads in terms of power values and time of operation. The obtained dictionary coefficients are treated as graph signals and graph smoothness is used for propagating the coefficients from the training phase to the test phase by formulating an optimization model. The derivation of the optimization model identifies the load of interest and estimate their power consumption based on optimization model constraints. This method achieves accuracy greater than 70% for the loads of interest at low sampling rates.

公开(公告)号：US11006874B2

公开(公告)日：2021-05-18

申请号：US13965523

申请日：2013-08-13

Applicant: Tata Consultancy Services Limited

Inventor： Srinivasan Jayaraman ,  Kriti Kumar ,  Balamuralidhar Purushothaman

IPC: A61B5/16 ,  A61B5/0245 ,  A61B5/00 ,  A61B5/11 ,  A61B5/024 ,  G06K9/00 ,  A61B5/0205 ,  A61B5/0456 ,  A61B5/352

Abstract: The present subject matter relates to a computer implemented method for real time determination of stress levels of an individual. The method includes receiving at least one stream of physiological data from at least one primary sensor for a predetermined duration, and preprocessing the at least one stream of physiological data to extract physiological parameters, where the preprocessing includes performing a preliminary analysis on the at least one stream of physiological data. The method further includes determining a stress level of the individual based on at least the physiological parameters, wherein the determining comprises performing a statistical analysis on the physiological parameters.