Abstract: 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.

Abstract: Radar based HR and BR measurements by simultaneous decoding is a technical problem due to presence of intermodulation of BR and HR harmonics, which degrades simultaneous decoding. Embodiments herein provide a method and system for unobtrusive liveliness detection and monitoring of a subject using a Dual Frequency Radar (DFR) in an IOT network. The system has the capability to completely process the captured raw signals onboard to by applying required signal conditioning and extraction of relevant information using unique signal processing techniques for determining the HR and the BR of the subject accurately. The intermodulation of BR and HR harmonics is eliminated by the system by performing frequency spectrum averaging of both radars signals, which improves the accuracy. Further, the system is configured with a light MQTT protocol and encoding modules for any data to be shared for off board processing, ensuring data security and privacy compliance.

Abstract: This disclosure relates to systems and methods for shapelet decomposition based recognition using radar. State-of-the-art solutions involve use of standard machine learning classification techniques for gesture recognition which suffer with problem of dependency on collected data. The present disclosure overcome the limitations faced by the state-of-the-art solutions by obtaining a plurality of time domain signal using a radar system comprising three vertically arranged radars and one or more sensors, identifying one or more gesture windows to obtain one or more shapelets corresponding to one or gestures which are further decomposed into a plurality of sub shapelets. Further, at least one of (i) a positive or (i) a negative time delay is applied to each of the plurality of sub shapelets to obtain a plurality of composite shapelets which are further mapped with a plurality of trained shapelets to recognize gestures comprised in one or more activities performed by a subject.

Abstract: Techniques for heart rate estimation are disclosed. In an embodiment, synchronized photoplethysmograph (PPG) and 3-axis acceleration signals are received. Further, the PPG and acceleration signals are partitioned into windows. Furthermore, it is determined whether motion is present in a window of the acceleration signal. Moreover, Fourier transform is performed on the signals to obtain power spectra of the signals in the window when there is motion. Also, it is determined whether a peak of the acceleration signal is present in a range around first highest PPG peak. Further, it is determined whether the peak of the acceleration signal affects heart rate of the user when the peak of the acceleration signal is in the range around the highest PPG peak. The heart rate of the user in the window is then estimated using second highest PPG peak when the peak of the acceleration signal affects heart rate of the user.

Abstract: This disclosure relates generally to radar based human activity detection, and, more particularly to, systems and methods from radar based human activity detection and three-dimensional (3D) reconstruction of human gestures using configurable panel radar system. Traditional systems and methods may not provide for a separate capturing of top and bottom parts of the human body. Embodiment of the present disclosure overcome the limitations faced by the traditional systems and methods by identifying a user that performed a gesture; detecting each gesture performed by the identified user; generating, by simulating a set of gesture labels, a sensor data and the generated metadata, a two-dimensional (2D) reference database of different speeds of the detected gestures; computing a displacement and a time of the detected gestures via a pattern matching technique; and reconstructing a video of the identified user performing the detected gestures in 3D.

Abstract: This disclosure relates to selection of optimum channel in twin radars for efficient detection of cardiopulmonary signal rates. State-of-the-art solutions involve use of IQ (In-phase and Quadrature) channel radar which need continuous calibration. Distance of the radar from a subject being monitored affects performance. The present disclosure enables enhanced cardiopulmonary signal rate monitoring using a time domain approach, wherein only the data from signal reflected off the radar is considered. The solution is also time window adaptive. Signal property and radar physics-based methods have been implemented for selecting an optimum channel in twin radars thereby enhancing detection of respiration rate and breath rate.

Abstract: This disclosure relates generally to field agnostic source localization. Conventional state-of-the-art methods perform source localization for near-field scenario by estimating carrier frequency and direction of arrival (DOA) at or above Nyquist sampling rate. Embodiments of the present disclosure provide a method for source localization at sub Nyquist sampling rate. The method estimates parameters such as range, carrier frequency and DOA of source signals from data sources in a mixed field scenario. i.e., the data sources may reside in far-field as well as near-field. The method considers a delay channel to a sensor receiver architecture for estimating the parameters. The disclosed method can be used in applications like cognitive radio to determine the carrier frequency, DOA and range of various source signals from data sources in mixed field.

Abstract: The present disclosure provides means for detecting and tracking a moving object using RADAR and ultrasonic sensors. A stationary RADAR detects the moving object and estimates speed and two rotating ultrasonic sensors determine distance of the detected object. An incrementally changing orientation of the ultrasound sensors is associated with an angular speed of rotation based on a last logged distance of the moving object from the ultrasound sensors. Once the moving object is detected, based on an adaptively changing sampling frequency, the moving object is continuously tracked in real time. Conventionally, multiple RADARs are needed for location estimation and motion tracking. Also, merely using a RADAR in combination with an ultrasound sensor also does not serve the purpose since both sensors are static. The present disclosure provides a simple cost effective alternative that can find application in say tracking of an elderly person living alone in an unobtrusive manner.

Abstract: This disclosure relates generally to driver profiling, and more particularly to system and method for driver profiling corresponding to automobile trip. In one embodiment, the method includes selectively computing, based on GPS data captured during a trip, features such that a first set of features are computed at a computation device and a second set of features are computed at a cloud server. The first and second set of features differs in computational complexity level. Said features include statistical data for attributes computed from the GPS data. The features corresponding to the trip are stored at repository associated with the cloud server. The repository includes previously precomputed features data associated with a set of driver profiles for previously completed trips. A driver profile corresponding to the trip is identified from amongst the set of driver profiles based on comparison of the plurality of features and the previously computed features data.

Abstract: This disclosure relates generally to methods and systems for unobtrusive and automated detection of frequencies of spatially located distinct parts of a machine. Location of vibration and detection of vibration frequency of each vibrating part in a machine is critical for routine monitoring and fault detection in the machine. Current solutions use either high frames per second (fps) industrial grade camera or stroboscopes tuned at one particular frequency. Manual stroboscopes require manual intervention for objects moving at different speeds with high convergence time. Point-lasers need prior knowledge of exact location of faults. Also Point-by-point scanning of a large machine body is time consuming. In the present disclosure, a movement detector such as RADAR enables detecting all vibration frequencies that also serve to reduce the search space of a stroboscope configured to start strobing at each detected vibration frequency to enable mapping of each vibration frequency to a corresponding vibrating part.

Abstract: This disclosure relates generally to bio-signal detection, and more particularly to method and system for non-contact bio-signal detection using ultrasound signals. In an embodiment, the method includes acquiring an in-phase I(t) baseband signal and a quadrature Q(t) baseband signal associated with an ultrasound signal directed from the sensor assembly towards the target. Magnitude and phase signals are calculated from the in-phase and quadrature baseband signals, and are filtered by passing through a band pass filter associated with a predefined frequency range to obtain filtered magnitude and phase signals. Fast Fourier Transformation (FFT) of the filtered magnitude and phase signals is performed to identify frequency of dominant peaks of spectrum of the magnitude and phase signals in the ultrasound signal. Value of the bio-signal associated with the target is determined based on weighted values of the frequency of the dominant peaks of the magnitude and phase signals.

Abstract: A pulmonary health monitoring system aims at assessing pulmonary health of subjects. Conventional techniques used for pulmonary health monitoring are not convenient to the subjects and needs considerable cooperation from the subjects. But, there is a challenge in utilizing the conventional devices to the subjects not capable of providing considerable cooperation. The present disclosure includes a blow device applicable to all kind of subjects and doesn't need cooperation from the subjects. Further, in the present disclosure, the blow device generates a phase shifted signal corresponding to a breathe signal and the phase shifted signal is further processed to extract a set of physiological features. Further, pulmonary health of a subject is analyzed by processing the set of physiological features based on a ridge regression based machine learning technique.

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.

Abstract: 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.

Abstract: Embodiments herein provide a system and method for screening and monitoring of cardiac diseases by analyzing acquired physiological signals. Unlike state of art approaches that consider only synchronized ECG and PPG signals for cardiac health analysis and do not consider PCG which is a critical signal for CAD analysis, the system synchronously captures physiological signals such as photo plethysmograph (PPG), phonocardiogram (PCG) and electrocardiogram (ECG) from subject(s) and builds an analytical model in the cloud for analyzing heart conditions from the captured physiological signals. The system and method provides a fusion based approach of combining the captured physiological signals such as PPG, PCG and ECG along with other details such as subject clinical information, demography information and so on. The analytical model is pretrained using ECG. PPG and PCG along with metadata associated with the subject such as demography and clinical information.

Abstract: Systems and methods for adaptive sensors calibration are provided. The traditional systems and methods provide for heart rate monitoring using PPG methods but do not focus on adaptive calibration with real-time feedback and dynamic signal quality validation. Embodiments of the present disclosure provide for obtaining an initial value pertaining to a set of calibration parameters of a first sensor and performing a comparison with a pre-defined threshold; incrementing value of the set of calibration parameters by a pre-defined value and performing a comparison; obtaining from the sensor configuration matrix, an initial value pertaining to a set of calibration parameters of a second sensor and performing a comparison; and repeating the steps performed above if the comparisons performed does not match pre-defined quality threshold and finally updating sensor configuration matrix whenever pre-defined quality threshold is matched.

Abstract: 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.

Abstract: This disclosure relates generally to radar based human activity detection, and, more particularly to, systems and methods from radar based human activity detection and three-dimensional (3D) reconstruction of human gestures using configurable panel radar system. Traditional systems and methods may not provide for a separate capturing of top and bottom parts of the human body. Embodiment of the present disclosure overcome the limitations faced by the traditional systems and methods by identifying a user that performed a gesture; detecting each gesture performed by the identified user; generating, by simulating a set of gesture labels, a sensor data and the generated metadata, a two-dimensional (2D) reference database of different speeds of the detected gestures; computing a displacement and a time of the detected gestures via a pattern matching technique; and reconstructing a video of the identified user performing the detected gestures in 3D.

Abstract: This disclosure relates generally to an optical strobing based multi-frequency vibration measurement, and more particularly to systems and methods for autonomous stroboscopic machine inspection for multi-point and multi-frequency vibration measurement. Embodiments of the present disclosure provide for an optical strobing based multi-frequency vibration measurement by selecting a strobe frequency, obtaining one or more image frames, obtaining a marker position, calculating a fast fourier transformation, obtaining one or more peak prominent frequencies, obtaining a product set of the one or more peak prominent frequencies, optimizing the strobing frequency where the value of the product set of the one or more peak prominent frequencies is not equal to an optimum pre-defined system value and detecting and measuring a plurality of vibrations of multiple frequencies by applying a chinese remainder theorem on the product set and the strobe frequency set.

Abstract: 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.