公开(公告)号：US20150257014A1

公开(公告)日：2015-09-10

申请号：US14560741

申请日：2014-12-04

Applicant: TATA CONSULTANCY SERVICES LIMITED

Inventor： Nasimuddin Ahmed ,  Chirabrata Bhaumik ,  Avik Ghose ,  Arpan Pal ,  Amit Agrawal ,  Tapas Chakravarty

IPC: H04W16/20 ,  H04W4/04 ,  H04W24/10

CPC classification number: H04W16/20 ,  G01S5/0252 ,  H04W4/04 ,  H04W24/10

Abstract: The present disclosure envisages a computer implemented system and method for Wi-Fi based indoor localization. The system includes a repository for storing attributes of the floor plan of an indoor area with respect to the zones on the floor plan. A communicating module receives a threshold number of data points from user devices located in the area. These data points include a plurality of Received Signal Strength Indicators (RSSI) captured from the access points positioned in the area. A k-means clustering is then performed on the data points for grouping the data points into ‘k’ number of clusters and a decision tree is built by following a condition based approach. Distance values are then calculated pertaining to the RSSIs stored at the decision tree, and zone circles are plotted. Zone of user presence is then determined by correlating the plotted zone circles upon the floor plan using maximum overlap property.

Abstract translation: 本公开设计了用于基于Wi-Fi的室内定位的计算机实现的系统和方法。 该系统包括用于存储关于平面图上的区域的室内平面图的属性的存储库。 通信模块从位于该区域中的用户设备接收阈值数量的数据点。 这些数据点包括从位于该区域中的接入点捕获的多个接收信号强度指示符（RSSI）。 然后对数据点执行k均值聚类，以将数据点分组为“k”个簇，并通过遵循基于条件的方法构建决策树。 然后计算与决定树上存储的RSSI相关的距离值，并绘制区域圆。 然后通过使用最大重叠属性将平面图上绘制的区域圆相关联来确定用户存在区域。

公开(公告)号：US20150193686A1

公开(公告)日：2015-07-09

申请号：US14588595

申请日：2015-01-02

Applicant: Tata Consultancy Services Limited

Inventor： Kingshuk Chakravarty ,  Ramu Reddy Vempada ,  Tanushyam Chattopadhyay ,  Aniruddha Sinha ,  Arpan Pal

IPC: G06N5/04 ,  G06N99/00 ,  G01J5/00

CPC classification number: G06N5/04 ,  G01J5/00 ,  G06F21/32 ,  G06K9/00369 ,  G06K2209/055 ,  G06N99/005

Abstract: A system and method for identifying an unknown person based on a static posture of the unknown person is described. The method includes receiving data of N skeleton joints of the unknown person from a skeleton recording device. The method further includes identifying the static posture of the unknown person. The method includes dividing a skeleton structure of the unknown person in a plurality of body parts based on joint types of the skeleton structure. In addition, the method includes extracting feature vectors for each of the joint type from each of the plurality of body parts. The method further includes identifying the unknown person based on comparison of the feature vectors for the unknown person with one of a constrained feature dataset and an unconstrained feature dataset for a plurality of known persons.

Abstract translation: 描述了基于未知人的静态姿势来识别未知人的系统和方法。 该方法包括从骨架记录装置接收未知人的N个骨架关节的数据。 该方法还包括识别未知人的静态姿势。 该方法包括基于骨骼结构的关节类型将未知人的骨架结构划分为多个身体部位。 此外，该方法包括从多个身体部分中的每一个提取每个关节类型的特征向量。 该方法还包括基于未知人的特征向量与多个已知人的约束特征数据集和无约束特征数据集之一的比较来识别未知人。

公开(公告)号：US20150067742A1

公开(公告)日：2015-03-05

申请号：US14387086

申请日：2013-03-19

Applicant: Tata Consultancy Services Limited

Inventor： Aniruddha Sinha ,  Tanushyam Chattopadhyay ,  Chirabrata Bhaumik ,  Arpan Pal

IPC: H04N21/454 ,  H04N7/10 ,  H04N21/45 ,  H04N21/41 ,  H04L29/06 ,  H04N21/436

CPC classification number: H04N21/454 ,  H04L65/60 ,  H04N7/106 ,  H04N21/4104 ,  H04N21/436 ,  H04N21/43615 ,  H04N21/4532

Abstract: A method and system is provided for context based splitting of a broadcast content stream and transmission of a relevant broadcast content out of said broadcast content stream to at least one edge device over a home area network for consumption. Particularly, the invention provides a method and system for obtaining context of the edge device and corresponding device owner; comparing the said obtained context with the broadcast content stream; finding and splitting relevant broadcast content out of the broadcast content stream according to the context of said edge device; and transmitting said relevant broadcast content to said edge device for future consumption.

Abstract translation: 提供了一种方法和系统，用于基于上下文的广播内容流的分割和从所述广播内容流中的相关广播内容的传输到家庭区域网络上的至少一个边缘设备以供消费。 特别地，本发明提供了一种用于获得边缘设备和相应设备所有者的上下文的方法和系统; 将所述获得的上下文与广播内容流进行比较; 根据所述边缘设备的上下文从广播内容流中发现和分解相关的广播内容; 以及将所述相关广播内容发送到所述边缘设备以供将来消费。

公开(公告)号：US20150049016A1

公开(公告)日：2015-02-19

申请号：US14387007

申请日：2013-03-08

Applicant: Tata Consultancy Services Limited

Inventor： Aniruddha Sinha ,  Kingshuk Chakravarty ,  Rohit Kumar Gupta ,  Arpan Pal ,  Anupam Basu

IPC: G06F3/01

CPC classification number: G06F3/017 ,  A63F13/213 ,  A63F13/215 ,  G06F3/011 ,  G06K9/00335 ,  G06K9/629 ,  G06K9/6293

Abstract: A device and a method facilitating generation of one or more intuitive gesture sets for the interpretation of a specific purpose are disclosed. Data is captured in a scalar and a vector form which is further fused and stored. The intuitive gesture sets generated after the fusion are further used by one or more components/devices/modules for one or more specific purpose. Also incorporated is a system for playing a game. The system receives one or more actions in a scalar and a vector from one or more user in order to map the action with at least one pre stored gesture to identify a user in control amongst a plurality of users and interpret the action of user for playing the game. In accordance with the interpretation, an act is generated by the one or more component of the system for playing the game.

Abstract translation: 公开了一种便于产生用于解释特定目的的一个或多个直观手势集的装置和方法。 以标量和向量形式捕获数据，进一步融合和存储。 一个或多个组件/设备/模块进一步使用融合之后生成的直觉手势集合用于一个或多个特定目的。 还包括玩游戏的系统。 系统从一个或多个用户接收标量和向量中的一个或多个动作，以便通过至少一个预先存储的手势来映射动作，以便在多个用户之间的控制中识别用户，并解释用户播放的动作 游戏。 根据解释，系统的一个或多个部件产生一个动作，用于玩游戏。

公开(公告)号：US20140362733A1

公开(公告)日：2014-12-11

申请号：US14363378

申请日：2012-12-14

Applicant: Tata Consultancy Services Limited

Inventor： Aniruddha Sinha ,  Arpan Pal ,  Dhiman Chattopadhyay

IPC: H04L29/08 ,  H04W4/00 ,  H04W48/10

CPC classification number: H04L67/12 ,  H04L63/0421 ,  H04W4/023 ,  H04W4/06 ,  H04W4/80 ,  H04W12/003 ,  H04W12/02 ,  H04W48/10 ,  H04W84/18

Abstract: A system and method for dynamically establishing an adhoc network amongst plurality of communication devices in a beyond audible frequency range is disclosed. The system comprises a first communication device to transmit a quantity of data to a second communication device. The first communication device comprises of an input capturing module to receive the quantity of data from a broadcaster in a format and converts the quantity of data received into a quantity of modulated data, an identity generating module to generate a temporary identity for a broadcasting user. The second communication device then receives the data broadcasted from the first communication device and determines a probabilistic confidence level of the quantity of modulated data. A transreceiver implemented in the first communication device and second communication device transmits and receives the quantity of data in conjugation with the temporary identity within a predefined proximity of each device.

Abstract translation: 公开了一种用于在超出可听频率范围内的多个通信设备之间动态建立自组网络的系统和方法。 该系统包括用于将数量的数据发送到第二通信设备的第一通信设备。 第一通信设备包括输入捕获模块，用于以格式接收来自广播者的数据量，并将所接收的数据量转换成调制数据量，身份生成模块，以产生广播用户的临时身份。 然后，第二通信设备接收从第一通信设备广播的数据，并确定调制数据量的概率置信水平。 在第一通信设备和第二通信设备中实现的收发器在每个设备的预定接近度内发送和接收与临时身份共轭的数据量。

公开(公告)号：US20140351790A1

公开(公告)日：2014-11-27

申请号：US14286068

申请日：2014-05-23

Applicant: TATA CONSULTANCY SERVICES LIMITED

Inventor： Avik Ghose ,  Arpan Pal ,  Anirban Dutta Choudhury ,  Tanushyam Chattopadhyay ,  Plaban Kumar Bhowmick ,  Dhiman Chattopadhyay

IPC: G06F9/44 ,  G06F17/30

CPC classification number: G06F8/70 ,  G06F8/36 ,  G06F16/2228

Abstract: An application development system for development of Internet of Things (IoT) application includes a cataloging module to obtain an input from an application developer. The input comprises data related to the IoT application to be developed. The cataloging module further retrieves a plurality of reusable artefacts from a knowledge database based on the input. A recommendation module in the application development system recommends, to the application developer, artefacts from amongst the plurality of reusable artefacts, based at least on one of a feedback associated with each of the plurality of reusable artefacts, an expert analysis, and a combination of the expert analysis and the feedback. An association module in the application development system associates artefacts selected by the application developer with each other for development of the IoT application.

Abstract translation: 物联网应用开发系统（IoT）应用程序包括编目模块，用于从应用程序开发人员获取输入。 该输入包括与要开发的IoT应用有关的数据。 编目模块基于输入进一步从知识数据库检索多个可重用的伪像。 所述应用开发系统中的推荐模块至少基于与所述多个可重复使用的人工制品中的每一个相关联的反馈中的一个，专家分析以及所述多个可重复使用的人工制品的组合中的至少一个，向所述应用开发者推荐所述多个可再利用人造物中的人造物 专家分析和反馈。 应用程序开发系统中的关联模块将由应用程序开发人员选择的伪装相互关联，以便开发IoT应用程序。

公开(公告)号：US12018989B2

公开(公告)日：2024-06-25

申请号：US17436062

申请日：2020-04-21

Applicant: Tata Consultancy Services Limited

Inventor： Arijit Sinharay ,  Rajat Kumar Das ,  Anwesha Khasnobish ,  Tapas Chakravarty ,  Arpan Pal

IPC: G01K11/24 ,  G01K3/06 ,  G01K13/02 ,  G01K11/26

CPC classification number: G01K11/24 ,  G01K3/06 ,  G01K13/026 ,  G01K11/26

Abstract: Temperature measurement is an important part of many potential applications in the fields of metallurgy. Conventional temperature measurement methods do not provide accurate and precise average temperature of fluid inside an enclosed chamber. The present disclosure provides multi-sensory techniques for measuring average temperature of mixed fluid inside a chamber. The average temperature is measured based on acoustic interferometry technique on standing wave and inputs received from one or more sensors and radar. The present disclosure utilizes radar to compensate the effect of fumes, noise based on Doppler effect. Further, the inputs received from the one or more sensors are used to determine the concentration of one or more fluids present in the chamber. The method of proposed disclosure depends on the principle of dependence of temperature on sound speed in fluid. So, measurement of sound speed can be mapped to report average temperature of mixed fluid inside the chamber.

公开(公告)号：US11967133B2

公开(公告)日：2024-04-23

申请号：US17450602

申请日：2021-10-12

Applicant: Tata Consultancy Services Limited

Inventor： Swarnava Dey ,  Jayeeta Mondal ,  Jeet Dutta ,  Arpan Pal ,  Arijit Mukherjee ,  Balamuralidhar Purushothaman

IPC: G06V10/00 ,  G06V10/44 ,  G06V10/764 ,  G06V10/82

CPC classification number: G06V10/764 ,  G06V10/454 ,  G06V10/82

Abstract: 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.

公开(公告)号：US11872040B2

公开(公告)日：2024-01-16

申请号：US17136899

申请日：2020-12-29

Applicant: Tata Consultancy Services Limited

Inventor： Debatri Chatterjee ,  Dibyanshu Jaiswal ,  Arpan Pal ,  Ramesh Kumar Ramakrishnan ,  Ratna Ghosh ,  Madhurima Moulick ,  Rajesh Ranjan

IPC: A61B5/16 ,  G16H10/60 ,  G16H50/70 ,  G06N20/00 ,  A61B5/0533 ,  A61B5/00 ,  G16H40/67

CPC classification number: A61B5/165 ,  A61B5/0533 ,  A61B5/7267 ,  A61B5/7278 ,  G06N20/00 ,  G16H10/60 ,  G16H40/67 ,  G16H50/70

Abstract: Direct usage of endosomatic EDA has multiple challenges for practical cognitive load assessment. Embodiments of the method and system disclosed provide a solution to the technical challenges in the art by directly using the bio-potential signals to implement endosomatic approach for assessment of cognitive load. The method utilizes a multichannel wearable endosomatic device capable of acquiring and combining multiple bio-potentials, which are biomarkers of cognitive load experienced by a subject performing a cognitive task. Further, extracts information for classification of the cognitive load, from the acquired bio-signals using a set of statistical and a set of spectral features. Furthermore, utilizes a feature selection approach to identify a set of optimum features to train a Machine Learning (ML) based task classifier to classify the cognitive load experienced by a subject into high load task and low load task.

公开(公告)号：US20230376781A1

公开(公告)日：2023-11-23

申请号：US18199708

申请日：2023-05-19

Applicant: Tata Consultancy Services Limited

Inventor： Abhishek Roy Choudhury ,  Vighnesh Vatsal ,  Mehesh Rangarajan ,  Naveen Kumar Basa Anitha ,  Aditya Kapoor ,  Jayavardhana Rama Gubbi Lakshminarasimha ,  Aravindhan Saravanan ,  Vartika Sengar ,  Balamuralidhar Purushothaman ,  Arpan Pal ,  Nijil George

IPC: G06N3/092

CPC classification number: G06N3/092

Abstract: This disclosure relates generally to systems and methods for autonomous task composition of vision pipelines using an algorithm selection framework. The framework leverages transformer architecture along with deep reinforcement learning techniques to search an algorithmic space for unseen solution templates. In an embodiment, the present disclosure describes a two stage process of identifying the vision pipeline for a particular task. At first stage, a high-level sequence of the vision pipeline is provided by a symbolic planner to create the vision workflow. At second stage, suitable algorithms for each high-level task are selected. This is achieved by performing a graph search using a transformer architecture over an algorithmic space on each component of generated workflow. In order to make the system more robust, weights of embedding, key and query networks of a visual transformer are updated with a Deep Reinforcement Learning framework that uses Proximal Policy Optimization (PPO) as underlying algorithm.