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1.发明授权公开(公告)号：US10678886B2
公开(公告)日：2020-06-09
申请号：US15395439
申请日：2016-12-30
Applicant: Tata Consultancy Services Limited
Inventor： Debnath Mukherjee , Suman Datta , Prateep Misra
Abstract: This disclosure relates to systems and methods for analyzing sensor data using incremental autoregression techniques for generating a vector of autoregression coefficients is provided. The system processes a time series data to obtain blocks of observation values, reads the observation values, updates pre-stored convolution values with the observation values, updates a partial sum by adding each observation value to the partial sum, increments a count each time an observation value is read, repeats the steps of updates and increments until a last observation value from a last block is read to obtain an updated set of convolution values, partial sum, and count. The system further computes a first matrix and a second matrix using the updated set of convolutions values, or summation of observation values computed from the updated partial sum, or the updated count, and generates a vector of autoregression coefficients based on the first and the second matrix.
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2.发明授权公开(公告)号：US10180807B2
公开(公告)日：2019-01-15
申请号：US14345934
申请日：2012-10-11
Applicant: Tata Consultancy Services Limited
Inventor： Prateep Misra , Soumitra Naskar , Sumanta Ghosh , Ankur Chakraborty , Nilanjan Roy
Abstract: A system and method for consolidating a plurality of heterogeneous storage systems in a data center comprising collecting data from a plurality of heterogeneous storage devices using data collection tools, using Data Preparation Tool for extracting and translating the collected data, populating a Data Model stored in source storage configuration unit suitable for analysis, analyzing and classifying the collected data by an analysis unit based upon a plurality of attributes, comprising of a Consolidation Advisor that uses the analyzed data and candidate Target System Configurations, Preferences & Constraints for generating optimum number, specification & configuration of the Consolidate Target State infrastructure and mappings of logical units from as-is data center storage infrastructure to the target state, and iteratively validating the same in a Validation task till the final desired consolidation and objectives are met.
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公开(公告)号：US10031973B2
公开(公告)日：2018-07-24
申请号：US14492807
申请日：2014-09-22
Applicant: Tata Consultancy Services Limited
Inventor： Sounak Dey , Ranjan Dasgupta , Arpan Pal , Prateep Misra , Anupam Basu
IPC: G06F17/30
Abstract: Disclosed is a method and system for identifying a sensor to be deployed in a physical environment. The method may comprise storing sensor data and metadata of the plurality of sensors in a data store. Further, the method may comprise deriving sensor information comprising at least one of thematic information, temporal information, and spatial information. The method may further comprise creating sensor ontology to define a relationship between the sensor data, the metadata, and the sensor information. The sensor ontology may be stored in a knowledge repository of the data store. The method may further comprise receiving and decomposing the search query into at least one of a basic query component and an inferred query component. Finally, the method may comprise executing the basic query component or the inferred query component on the data store and the knowledge repository respectively in order to identify the sensor.
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公开(公告)号：US11586596B2
公开(公告)日：2023-02-21
申请号：US16596986
申请日：2019-10-09
Applicant: Tata Consultancy Services Limited
Inventor： Satanik Panda , Dibyendu Biswas , Hemanta Dutta , Tanushyam Chattopadhyay , Prateep Misra
Abstract: Data cataloging has become a necessity for empowering organizations with analytical ability. Conventional cataloging systems may fail to provide proper visualization of data to the different stakeholders of an organization. The present disclosure provides a hierarchical dynamic cataloging system so that visualization of data at different levels would be possible for different stake holders. In the present disclosure, a hierarchical structure of algorithms and multiple stake holders along with relevant metadata is generated. Further, a catalog is generated by performing a mapping across components comprised in the hierarchical structure and identifying relationship across the components based on mapping. The catalog gets dynamically updated and provides a dynamic view of the algorithms and associated metadata to the multiple stakeholders of an organization. Further, the disclosure supports reuse of already developed algorithms across multiple applications and domains resulting in optimization of resources and time.
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公开(公告)号：US10074052B2
公开(公告)日：2018-09-11
申请号：US14761463
申请日：2013-12-05
Applicant: Tata Consultancy Services Limited
Inventor： Snehasis Banerjee , Debnath Mukherjee , Prateep Misra
Abstract: Disclosed is a method and system for dynamically generating a customized, personalized and contextual alert for a user based upon personalized, contextual and background knowledge associated with the profile of the user. The system comprises a profile updater module configured to update the profile data of the user extracted either from the social web or from the user. Further, a reasoning module is configured to derive refined background knowledge in context with the updated profile data of the user. A monitoring module is configured to monitor the events sensed by a sensing module. A context extractor module is configured for extracting the context of the events and the context of the user. A knowledge converter module is configured to convert the extracted context into structured format. Finally, the refined background knowledge is steam reasoned to determine whether the events received are relevant to the user and accordingly transmitted.
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Patent Agency Ranking
公开(公告)号：US09990182B2
公开(公告)日：2018-06-05
申请号：US14345545
申请日：2012-09-18
Applicant: Tata Consultancy Services Limited
Inventor： Prateep Misra , Arpan Pal , Balamuralidhar Purushothaman , Chirabrata Bhaumik , Deepak Swamy , Venkatramanan Siva Subrahmanian , Avik Ghose , Aniruddha Sinha
CPC classification number: G06F8/00 , G06F8/36 , G06F8/60 , G06F11/3668 , H04L41/00 , H04L41/04 , H04L41/5096 , H04L43/00 , H04L67/10 , H04L67/12
Abstract: A computing platform for intelligent development, deployment and management of vehicle telemetry applications is disclosed herein. Further, the present disclosure provides a method and system that enables provision of Intelligent Transportation Service on the Cloud-based Platform that facilitates creation and deployment of vehicle telemetry applications configured for enabling traffic measurements, traffic shaping, vehicle surveillance and other vehicle related services.
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7.发明申请公开(公告)号：US20170208081A1
公开(公告)日：2017-07-20
申请号：US15395439
申请日：2016-12-30
Applicant: Tata Consultancy Services Limited
Inventor： Debnath Mukherjee , Suman Datta , Prateep Misra
Abstract: This disclosure relates generally to data analysis systems, and more particularly to systems and methods for analyzing sensor data using incremental autoregression techniques. In one embodiment, a Systems and methods for generating a vector of autoregression coefficients is provided. The system processes a time series data to obtain blocks of observation values, reads the observation values, updates pre-stored convolution values with the observation values, updates a partial sum by adding each observation value to the partial sum, increments a count each time an observation value is read, repeats the steps of updates and increments until a last observation value from a last block is read to obtain an updated set of convolution values, partial sum, and count. The system further computes a first matrix using the updated set of convolutions values, or summation of observation values computed from the updated partial sum, or the updated count, and a second matrix using the updated set of convolutions values, or summation of observation values, and generates a vector of autoregression coefficients based on the first and the second matrix.
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8.发明申请公开(公告)号：US20140351337A1
公开(公告)日：2014-11-27
申请号：US14376536
申请日：2013-01-22
Applicant: Tata Consultancy Services Limited
Inventor： Arpan Pal , Balamuralidhar Purushothaman , Prateep Misra , Sunil Kumar Kopparapu , Aniruddha Sinha , Chirabrata Bhaumik , Priyanka Sinha , Avik Ghose
IPC: H04L29/06
CPC classification number: H04L65/403 , G01S5/0257 , G06Q30/02 , G09B19/06 , H04L67/306 , H04M1/72569 , H04M1/72572 , H04W4/02 , H04W4/08
Abstract: A method and system for identifying personal context of a user having a portable mobile communication device at a particular location for deriving social interaction information of the user, wherein the user within a predefined range is identified using personal context of the user at the particular location and the identified personal context of the user is assigned with the confidence value. Further the current location information of the user within the particular location is obtained by fusing assigned confidence value. Further the proximity of the user in the current location is estimated by finding the accurate straight line distance between users. Further the two users having similar current location information at the particular location are grouped together with the predefined density criteria. Finally the social interaction information of the user is derived by multimodal sensor data fusion at the fusion engine and represented using a human network graph.
Abstract translation: 一种用于识别具有在特定位置处的便携式移动通信设备的用户的个人情境的方法和系统，用于导出用户的社交交互信息，其中使用在特定位置处的用户的个人情境来识别预定范围内的用户，以及 所识别的用户的个人上下文被分配有置信度值。 此外，通过融合分配的置信度值来获得特定位置内用户的当前位置信息。 此外，通过找到用户之间的准确的直线距离来估计用户在当前位置的接近度。 此外，在特定位置处具有相似的当前位置信息的两个用户与预定义的密度标准一起被分组在一起。 最后，用户的社交交互信息是通过融合引擎的多模态传感器数据融合得出的，并使用人类网络图表示。
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9.发明授权公开(公告)号：US11906958B2
公开(公告)日：2024-02-20
申请号：US17366777
申请日：2021-07-02
Applicant: Tata Consultancy Services Limited
Inventor： Tanushyam Chattopadhyay , Abhisek Das , Suvra Dutta , Shubhrangshu Ghosh , Prateep Misra
IPC: G05B23/02 , G06F18/20 , G06F18/2415
CPC classification number: G05B23/0227 , G06F18/2415 , G06F18/285
Abstract: State-of-the-art approaches have concentrated on building solution(s) to match the amplitude of a time series with a user given one. However, these have failed to implement solution(s) which enables searching for pattern(s) that can depict human vision psychology. Embodiments of the present disclosure determine occurrence of pattern of interest in time series data for anomaly detection, wherein time series data is obtained, and first order derivative is computed. Further an angle of change in direction is derived based on a gradient of change in value of the time series data. This angle is further converted to a measurement unit. The time series data is quantized into bins and a weighted finite state transducers diagram (WFSTD) is obtained based on domain knowledge which is then converted to specific pattern. The specific pattern is searched in the bins to determine occurrence/count of the specific pattern for anomaly detection.
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10.发明授权公开(公告)号：US11449522B2
公开(公告)日：2022-09-20
申请号：US17359818
申请日：2021-06-28
Applicant: Tata Consultancy Services Limited
Inventor： Tanushyam Chattopadhyay , Arindam Halder , Sangram Dasharath Gaikwad , Tania Ghosh , Abhisek Das , Shubhrangshu Ghosh , Suvra Dutta , Prateep Misra
IPC: G06F17/00 , G06F16/25 , G06F16/2455
Abstract: Sensor data (or IoT) analytics plays a critical role in taking business decisions for various entities (e.g., organizations, project owners, and the like). However, scaling of such analytical solutions beyond certain point requires adopting to various computing environments which seems to be challenging with the constrained resources available. Embodiments of the present disclosure provide system and method for analysing and executing sensor observational data in computing environments, wherein extract, transform, load (ETL) workflow pipeline created by users in the cloud, can be seamlessly deployed to job execution service available in cloud/edge without any changes in the code/config by end user. The configuration changes are internally handled by the system based on the selected computing environment and queries are executed either in distributed or non-distributed environments to output data frames. The data frames are further pre-processed in a desired computing environment and thereafter visualized accordingly.
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