Abstract: This disclosure relates generally to a method and system for multi-hop path selection for mobile robots based on cloud platform providing an optimal path for end-to-end communication in the multi-hop network. Multi-hop path selection for mobile robots, conventionally performed at mobile robot end, may not provide an optimal path as mobile robots are unaware of the global scenario of the multi-hop network. Further, computation at mobile robot end is not an energy efficient solution. The disclosed cloud system communicates the optimal path to the source mobile robot to reach the destination mobile robot through the plurality of Access Points (APs). Multi-hop path selection for mobile robots, currently performed at mobile robot end, may not provide an optimal path as mobile robots are unaware of the global scenario of the multi-hop network. The optimal path computed at cloud system increases the life-time of robotics network there by increasing the efficiency.

Abstract: This disclosure relates generally to the use of distributed system for computation, and more particularly, relates to a method and system for optimizing computation and communication resource while preserving security in the distributed device for computation. In one embodiment, a system and method of utilizing plurality of constrained edge devices for distributed computation is disclosed. The system enables integration of the edge devices like residential gateways and smart phone into a grid of distributed computation. The edged devices with constrained bandwidth, energy, computation capabilities and combination thereof are optimized dynamically based on condition of communication network. The system further enables scheduling and segregation of data, to be analyzed, between the edge devices. The system may further be configured to preserve privacy associated with the data while sharing the data between the plurality of devices during computation.

Abstract: Robotic platform for tele-presence applications has gained paramount importance, such as for remote meetings, group discussions, and the like and has sought much attention. There exist some robotic platforms for such tele-presence applications, these lack efficacy in communication and interaction between remote person and avatar robot deployed in another geographic location thus adding network overhead. Embodiments of the present disclosure for edge centric communication protocol for remotely maneuvering tele-presence robot in geographically distributed environment.

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: Traditionally arousal classification has been broadly done in multiple classes but have been insufficient to provide information about how arousal level of user changes over time. Present disclosure propose a continuous and unsupervised approach of monitoring the arousal trend of individual from his/her heart rate by obtaining instantaneous HR for time windows from a resampled time series of RR intervals obtained from ECG signal. A measured average heart rate (a measured HR) is computed from instantaneous HR specific to user for each time window thereby estimating apriori state based on a last instance of an aposteriori state initialized and observation of a state space model of Kalman Filter is determined for computing error and normalizing thereof which gets compared with a threshold for continuous monitoring of arousal trend of the user. The aposterior state is further updated using Kalman gain computed based on measurement noise determined for state space model.

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: Many capacitive sensing based biosignal measurements methods exist, which are generic as they do not personalize biosignal measurement. Further, are do not provide device agnostic solutions. A method and system for capacitive touch panel based biosignal measurement is provided. The method senses a change in raw capacitance value of a capacitive touch panel. However, unlike existing methods that directly utilize the raw signal for biosignal measurements, the method disclosed derives a normalized signal by normalizing a raw signal corresponding to the change in raw capacitance of the capacitive touch panel. The normalization considers inter-relationships between a plurality of variables that affect the raw capacitance value such as a set of device specific parameters associated with the capacitive touch panel of the device, a set of ethnographic parameters, and metadata associated with the subject.

Abstract: A method and system for blood pressure (BP) estimation of a person is provided. The system is estimating pulse transit time (PTT) using the ECG signal and PPG signal of the person. A plurality of features are extracted from the PPG. The plurality of PPG features and the PTT are provided as inputs to an automated feature selection algorithm. This algorithm selects a set of features suitable for BP estimation. The selected features are fed to a classifier to classify the database into low/normal BP range and a high BP range. The correctly classified normal BP data are then used to create a regression model to predict BP from the selected features. The current methodology uses automated feature selection mechanism and also employs a block to reject extreme BP data. Thus the available accuracy in predicting BP is expected to be more than the existing BP estimation methods.

Abstract: This disclosure relates generally to human-robot interaction (HRI) to enable a robot to execute tasks that are conveyed in a natural language. The state-of-the-art is unable to capture human intent, implicit assumptions and ambiguities present in the natural language to enable effective robotic task identification. The present disclosure provides accurate task identification using classifiers trained to understand linguistic and semantic variations. A mixed-initiative dialogue is employed to resolve ambiguities and address the dynamic nature of a typical conversation. In accordance with the present disclosure, the dialogues are minimal and directed to the goal to ensure human experience is not degraded. The method of the present disclosure is also implemented in a context sensitive manner to make the task identification effective.

Abstract: Identification of pulmonary diseases involves accurate auscultation as well as elaborate and expensive pulmonary function tests. Also, there is a dependency on a reference signal from a flowmeter or need for labelled respiratory phases. The present disclosure provides extraction of frequency and time-frequency domain lung sound features such as spectral and spectrogram features respectively that enable classification of healthy and abnormal lung sounds without the dependencies of prior art. Furthermore extraction of wavelet and cepstral features improves accuracy of classification. The lung sound signals are pre-processed prior to feature extraction to eliminate heart sounds and reduce computational requirements while ensuring that information providing adequate discrimination between healthy and abnormal lung sounds is not lost.

Abstract: This disclosure relates to attention shifting of a robot in a group conversation with two or more attendees, wherein at least one of them is a speaker. State of the art has dealt with several aspects of Human-Robot Interaction (HRI) including responding to a source of sound at a time, addressing a fixed viewing area or determining who is the speaker based on eye gaze direction. However, attention shifting to make the conversation human-like is a challenge. The present disclosure uses audio-visual perception for speaker localization. Only qualified direction of arrivals (DOAs) are used for the audio perception. Further the audio perception is complimented by visual perception employing real time face detection and lip movement detection. Use of HRI rules, clustering of the DOAs, dynamic adjustment of rotation of the robot and a dynamically updated knowledge repository enriches the robot with intelligence to shift attention with minimum human intervention.

Abstract: Cloud robotics infrastructures generally support heterogeneous services that are offered by heterogeneous resources whose reliability or availability also varies widely with varying lifetime. For such systems, defining a static redundancy configuration for all services is difficult and often biased. Also, it is not feasible to define a redundancy configuration separately for each unique service. Therefore, in the present disclosure a trade-off between the two is ensured by providing At-most M-Modular Flexible Redundancy Model wherein an exact degree of redundancy is defined and is given to each service in a heterogeneous service environment and monitoring each task and subtask status to ensure that each subtask gets accomplished thereby enabling the tuning of the tradeoff between redundancy and cost and determining efficiency of the system by estimating number of resources utilized to complete specific subtask and comparing the resources utilization with the exact degree of redundancy defined.

Abstract: A multi-dimensional sensor data analysis system and method is provided. The multi-dimensional sensor data analysis system receives indoor and outdoor location, online and physical activity, online and physical proximity and additional a plurality of inputs (specific to a user), for example, surrounding of the subject, physiological parameters of the subject and recent social status of the subject, both online and offline. The multi-dimensional sensor data analysis system processes these inputs along with the knowledge of past behavior and traditional parameters of location, proximity and activity by performing a multi-dimensional sensor data analysis fusion technique, producing one or more outputs, for example, predicting or determining a human behaviour to a given stimuli.

Abstract: The disclosure relates to digital twin of cardiovascular system called as cardiovascular model to generate synthetic Photoplethysmogram (PPG) signal pertaining to disease conditions. The conventional methods are stochastic model capable of generating statistically equivalent PPG signals by utilizing shape parameterization and a nonstationary model of PPG signal time evolution. But these technique generates only patient specific PPG signatures and do not correlate with pathophysiological changes. Further, these techniques like most synthetic data generation techniques lack interpretability. The cardiovascular model of the present disclosure is configured to generate the plurality of synthetic PPG signals corresponding to the plurality of disease conditions. The plurality of synthetic PPG signals can be used to tune Machine Learning algorithms. Further, the plurality of synthetic PPG signals can be utilized to understand, analyze and classify cardiovascular disease progression.

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: 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: This disclosure relates generally to telecommunication networks, and more particularly to a method and system for delay aware uplink scheduling in a communication network. The telecommunication network performs data uplink and data downlink associated with data communication between multiple transmitter-receiver pairs connected to the network, by using specific scheduling schema as part of the data processing. Disclosed are method and system for performing a delay-aware uplink scheduling in the communication network. For an uplink request received from a transmitter, the system estimates downlink delay at the corresponding receiver side. The system further estimates a processing delay for the received uplink request. Based on the estimated downlink delay and the processing delay, the system determines an uplink delay budget for the transmitter. Further, based on the uplink delay budget and an achievable data rate computed for the transmitter, the system schedules uplink for the transmitter.

Abstract: Conventional protocols for live media streaming are not lightweight and hence not suitable for constrained video transmitting devices. The protocols are poor in terms of delay performance under lossy conditions and need to maintain a lot of states at the constrained transmitting end leading to load on the memory and draining energy of the devices. The conventionally used protocols do not perform well for intermittent connectivity. Usually the existing streaming solutions act either in completely reliable manner, using reliable transport protocol like TCP, or in completely unreliable manner using best effort unreliable transport protocol like UDP. The present disclosure provides a single streaming solution which can change the protocol semantics and maintains a balance between reliability and delay-performance, thereby optimizing the overall system goodput. The protocol does this intelligently by inferring the criticality of the segment in flight and enable live video streaming for Internet of Things (IoT).

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.