Tata Consultancy Services Limited

Rajat Kumar Das

Arijit Sinharay

Tapas Chakravarty

Arpan Pal

Aniruddha Sinha

Debatri Chatterjee

Rahul Dasharath Gavas

Anwesha Khasnobish

Arijit Chowdhury

Shreyasi Datta

Avik Ghose

Chirabrata Bhaumik

Kingshuk Chakravarty

Smriti Rani

Raj Kumar Rakshit

Andrew Gigie

Amit Swain

Abhijit Das

Pratyusha Das

Anagha Nikhil Mehrotra

Arpit Vishwakarma

Ratnamala Manna

Vedraj

Sayan Seth

Arijit Choudhury

Vedraj Vedraj

Rahul Dashrath Gavas

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.

Multi-sensory techniques for measuring average temperature of mixed fluid inside a chamber

Temperature measurement is an important part of many potential applications in process industry. Conventional temperature measurement methods require manual intervention for process monitoring and fail to provide accurate and precise measurement of temperature of an enclosed mixed fluid chamber. The present disclosure provides artificial intelligence based temperature measurement in mixed fluid chamber. A plurality of inputs pertaining to the mixed fluid chamber are received to build a fluid based model. The fluid based model is used to generate one or more fluid parameters. The one or more fluid parameters are used along with a ground truth temperature data and the received plurality of inputs for training an artificial intelligence (AI) based model. However, the AI based model is trained with and without knowledge of fluid flow. The trained AI based model is further used to accurately estimate temperature of the mixed fluid chamber for a plurality of test input data.

Artificial intelligence based temperature measurement in mixed fluid chamber

This disclosure relates to a system and method for measuring average temperature of mixed fluid in an enclosed chamber. Measurement is based on two independent principle as measuring variation in acoustic wave velocity and variation in resistivity that works on a single setup. First principle is based on measuring acoustic wave velocity in a known medium, which is isolated from the surrounding. The system comprises a primary pipe and a secondary pipe, wherein the ends of the pipes reside inside the enclosed chamber. The primary pipe is made out of good conductor of heat and filled with air. Ends of the primary pipe is fitted with a transducers have one transmitter at one end and one receiver at another end. Average temperature of the mixed fluid is measured based on the variations in sound velocity of acoustic wave passed through the primary pipe and resistivity variations of the primary pipe.

System and method for measuring temperature of mixed fluid in an enclosed chamber

Any sensing system is faced with triangle of dilemma between accuracy, latency and energy. High energy and high latency sensing systems are often very accurate but less useful. Embodiments herein provide a method and system for edge based sensor controlling in the IoT network for event monitoring. The system disclosed herein applies a hierarchical sensor selection process and adaptively chooses sensors among multiple sensors deployed in the IoT network. Further, on-the-fly changes operation modes of the sensors to automatically produce the best possible inference from the selected sensor data, in time, power and latency at the edge. Further, sensors of the system include a waveform and diversity control mechanism that enables controlling of an excitation signal of the sensor.

Edge based sensor actuation and control in IoT network for event monitoring

A method and system is provided for assessing the learning experience of the person by monitoring the mental state of the person. The method involves measuring the brain signal, skin conductance using GSR device, and heart rate variability using the pulse oximeter. These physiological signals are measured when the person is performing an activity such as the modified Stroop test. Once the activity is performed, an offline questionnaire is also filled by the person. Based on the comparison of the offline questionnaire and the physiological signals, a model is generated. This model is used to assess the learning experience of the person. According to another embodiment, a method is also provided for maintaining the steady flow state of a person while performing any activity.

Method and system for assessing learning experience of a person

This disclosure relates generally to tracking motion of target in indoor environment. The method includes estimating an initial position of the target in a mesh grid form based on radar data captured from radar devices installed in the indoor environment. For a subsequent target movement, a subsequent position of the target is estimated in the mesh grid form based on the initial position and a resultant velocity vector of the target. A number of outlier grid-points is computed with a threshold number, and based on comparison the outlier grid-points are either replaced with interpolated grid-points or the subsequent position of the target is repaired based on a probable position of the target obtained from at least one of a linear regression based analysis of prior positions of the target, prior knowledge of the target velocity and sampling interval, and a trilateration based technique.

System and method for tracking motion of target in indoor environment

Health signal monitoring using continuous wave microwave signals is often affected by phase wrapping and null point detection issues. The disclosure herein generally relates to health monitoring, and, more particularly, to a method and a monitoring system for health monitoring using Amplitude Modulated Continuous Wave (AMCW) microwave signals. In this design of the monitoring system, the AMCW microwave signal comprises of a carrier signal and a modulating signal. The modulating signal is used for measuring heart rate and breathing rate of a subject, while the carrier signal is used to tune antenna size in the monitoring system. As the probing wavelength and the antenna size are independent of each other in this design of the monitoring system, the probing wavelength can be adjusted such that effect of the phase wrapping can be minimized. The system addresses the null point measurement problem by quadrature modulating the modulating signal.

Method and system for health monitoring using amplitude modulated continuous wave microwave signal

A method and system is provided for pre-processing of an electroencephalography (EEG) signal for cognitive load measurement. The present application provides a method and system for pre-processing of electroencephalography signal for cognitive load measurement of a user, comprises of capturing the electroencephalography signal from the head of the user, detecting the plurality of system artifacts in the captured electroencephalography signal, detecting and removing noisy window from the captured electroencephalography signal, detecting an eye blink region and filtering out said detected eye blink region from the captured electroencephalography signal, utilizing the filtered electroencephalography signal for measuring the cognitive load of the user and subsequently computing different levels of mental workloads on the user using variation of spatial distribution of frontal scalp EEG electrodes for measured cognitive load.

Method and system for pre-processing of an EEG signal for cognitive load measurement

System and method for aiding communication for subjects suffering from paralysis of muscles controlled by peripheral nervous system are disclosed. A method for aiding communication for said subjects includes capturing, from a plurality of sensors, sensor data generated based on an interaction of a subject with an interactive UI. The plurality of sensors includes one or more body-parts movement tracking sensors for tracking motion of body-parts of the subject and one or more physiological signal sensors for monitoring physiological signals generated from the subject during the interaction. A plurality of model parameters indicative of characteristics of the subject related to the interaction are determined based on the sensor data. The navigation at the interactive UI is controlled on the plurality of model parameters.

System and method for aiding communication

A method and system for determining cognitive load of a person using a modified baseline is provided. The person is asked to perform a series of activities including staying in eye closed rest state and baseline state and performing a trial state. Simultaneously, EEG signal and GSR signal of the person are captured. The EEG signal and the GSR signal are preprocessed and segmented. The EEG and GSR signals are then used to determine a first set and a second set of inactive states from the baseline interval and the rest interval. The most inactive window is then identified out of the first set of inactive states. The most inactive window is determined from the rest interval of the person. The inactive window is used as the modified baseline to measure the cognitive load of the person.

Method and system for determining inactive state and its implication over cognitive load computation of a person

This disclosure relates to non-contact inspection of material for identifying and estimate composition of a material under inspection. Traditionally, material inspection is an invasive process involving contact based approaches. A radar-based approach requires placement of the radar at a specific location, which is a challenge since amplitude of the reflected signal, depends on the distance from the material under inspection. The present disclosure addresses this technical problem by providing a Continuous Wave radar-based approach that is based on absolute slope at extrema points on the reflected signal from the material under inspection.

Non-contact material inspection

The present disclosure envisages a computer implemented system and method to derive a relationship between Elementary Cognitive Tasks (ECTs) and the underlying cognitive skills of individuals through Electroencephalogram (EEG) analysis. The aim is to evaluate or improve the perceptual-cognitive traits of a subject that comprises disintegrating a given task into elementary task that are further mapped to identified cognitive categories of Bloom's Taxonomy, upon which a cluster analysis is performed. The separation index between the clusters thereafter establishes that individuals have different thinking process which is characteristics of that subject.

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Kolkata, India

Rajat Kumar Das