Abstract: Fluids are normally transported from one place to another through pipelines. It is essential to monitor the pipeline to avoid leakage or theft. It is expensive and not feasible to install cameras and sensors along the whole length of the pipeline. A system and method for inspecting and detecting fluid leakage in a pipeline has been provided. The system is using vibration sensors along with pressure sensors to detect the leakage or theft along with the exact location of the leakage or theft. The pressure sensors are mounted on the pipeline so that the fluid touches the diaphragm of the pressure sensors to sense the wave generated due to leakage. The vibration sensors are mounted on top of the pipeline surface and on the nearby ground to eliminate general noise conditions. Moreover, two pressure sensors are also installed at opposite sides to pinpoint the leakage location.

Abstract: Lighting conditions affect quality of images being captured. In traditional systems, illuminators (light sources) are used to illuminate the objects without considering illumination levels at different zones/sides of an object being photographed. As a result, all illuminators may run at maximum capacity, resulting in wastage of power and compromising efficiency of the system. The disclosure herein generally relates to illumination of objects, and, more particularly, to a method and system for adaptive illumination of objects. The system determines illumination at different zones of the object, and further identifies zones that are not illuminated properly in comparison with a threshold of illumination.

Abstract: Embodiments herein provide a method and system for a non-invasive mechanism providing simultaneous determination of viscosity-temperature variation of a lubricant for predicting machine health using a Photo Acoustic (PA) sensing mechanism, Laser-enabled swept frequency acoustic interferometry (LE-SFAI), wherein the lubricant produces acoustic wave only if it absorbs the laser irradiation, thus overcomes the limitation of ultrasound based SFAI through optical absorption based contrast and proper selection of laser excitation wavelength. A PA signal received from the lubricant is processed by a Vector Network Analyzer (VNA), then converted to time domain to obtain normalized first peak that corresponds to the PA signal generated by the lubricant. A squared rise time of the first peak is indicative of viscosity of the liquid and shift in the first peak is indicative of variation of the viscosity as temperature of the lubricant varies.

Abstract: In sensor data analytics, physics-based models generate high quality data. However, these models consume lot of time as they rely on physical simulations. On the other hand, generative learning takes much less time to generate data, and may be prone to error. Present disclosure provides system and method for generation of synthetic machine data for healthy and abnormal condition using hybrid of physics based and generative model-based approach. Finite Element Analysis (FEA) is used for simulating healthy and faulty parts in machinery with set of parameters and pre-condition(s). Small output data from FEA is fed into a generative model for generating synthesized data by learning data distribution knowledge and representing into latent space. Rule engine is built using statistical features wherein realistic bounds serve as faulty data indicators. Synthesized data which does not satisfies features bounds are discarded. Further, AI-based validation framework is used to analyze quality of synthesized data.

Abstract: Ultra Wide Band (UWB) based Real Time Location Systems (RTLS) that are being used for location tracking suffer from due to environment specific errors that are introduced due to factors such as difference in reflection and propagation. The disclosure herein generally relates to object localization, and, more particularly, to a method and system of error modelling for object localization using Ultra Wide Band (UWB) sensors. The error modelling allows the system to correct a determined location of an object being tracked, to determine a corrected location.

Abstract: This disclosure generally relates to the field of structural health monitoring, and, more particularly, to a method and system for evaluating residual life of components made of composite materials. Existing methods require performing computational methods such as Finite Element Analysis (FEA) on the results of Non-Destructive Testing (NDT) every time a component is inspected. This makes the process expensive and time-consuming. Thus, embodiments of present disclosure provide a method wherein NDT is performed using different sensing methods such as ultrasound, ultrasound pulse echo, thermography to determine type of defect, location of defect and depth of defect in a test component which are then fed into a pre-trained machine learning model to predict residual life of the component. Testing time is greatly reduced since the pre-trained machine learning model is trained offline using results of the computational methods.

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: Small and compact Deep Learning models are required for embedded Al in several domains. In many industrial use-cases, there are requirements to transform already trained models to ensemble embedded systems or re-train those for a given deployment scenario, with limited data for transfer learning. Moreover, the hardware platforms used in embedded application include FPGAs, AI hardware accelerators, System-on-Chips and on-premises computing elements (Fog/Network Edge). These are interconnected through heterogenous bus/network with different capacities. Method of the present disclosure finds how to automatically partition a given DNN into ensemble devices, considering the effect of accuracy—latency power—tradeoff, due to intermediate compression and effect of quantization due to conversion to AI accelerator SDKs.

Abstract: This disclosure relates generally to a method and system for determining viscosity information of fluids. The present disclosure utilizes an intensity modulated continuous wave (CW) laser diode-based PA sensing method to obtain a continuous wave photoacoustic (CWPA) spectra. Through this CWPA spectra, a full width half maximum (FWHM) and a spectral area is determined to obtain the information about the viscosity of fluids. Although, the CWPA based sensing technique is used for distinguishing different types of abnormalities in tissues, so far it is not used for measuring viscosity which is an important thermo-physical property. The viscosity information of the fluids from the normalized Gaussian fitted CWPA spectra is based on a viscosity feature computed from a FWHM, and a spectral area. The viscosity feature improves the good of fit parameter (R2) significantly to 0.98 as compared to the traditional only FWHM based viscosity determination for which R2 is 0.91.

Abstract: 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.

Abstract: Fluids are normally transported from one place to another through pipelines. It is essential to monitor the pipeline to avoid leakage or theft. It is expensive and not feasible to install cameras and sensors along the whole length of the pipeline. A system and method for inspecting and detecting fluid leakage in a pipeline has been provided. The system is using vibration sensors along with pressure sensors to detect the leakage or theft along with the exact location of the leakage or theft. The pressure sensors are mounted on the pipeline so that the fluid touches the diaphragm of the pressure sensors to sense the wave generated due to leakage. The vibration sensors are mounted on top of the pipeline surface and on the nearby ground to eliminate general noise conditions. Moreover, two pressure sensors are also installed at opposite sides to pinpoint the leakage location.

Abstract: 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.

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 generally to method and system for determining label value for labels in unstructured documents. Typical systems have challenge in understanding variations in layout of unstructured documents and extract information therefrom. The disclosed method and system facilitate systematically identifying sections and bounding boxes in the page images, taking image portion of the bounding boxes and extracting labels and label values therefrom. In case the label values are not present in the same bounding box having the label, the neighboring labels are examined for the matching label values. The system also obtains label-label value pairs from the document by utilizing a trained deep learning model, and compares the output with the label-label value pairs extracted earlier. An aggregated confidence score is assigned to the text in the bounding box.

Abstract: This disclosure relates generally to surveillance, and more particularly to perform entry and exit monitoring of a user. In an embodiment, the system identifies an entry event (during which a user enters a room being surveilled) and/or an exit event (during which a user leaves a room being surveilled), based on a Bluetooth Low Energy (BLE) based system. This system uses two receivers one positioned outside and the other positioned inside the room being surveilled, to receive BLE beacon transmitted by a user who is in motion. Based on relative change in Received Signal Strength Indicator (RSSI) values of this beacon with respect to the first and second receivers, the system identifies direction of movement of the user, and in turn, determines one of the entry or exit events.

Abstract: A mobile device and a method for estimation of direction of motion of a user are described. The mobile device comprises an inertial sensor to capture acceleration signals based on motion of the user and a direction estimation module. The direction estimation module determines direction of gravity based on filtering acceleration values obtained from captured the acceleration signals using a low-pass filter to identify a plane orthogonal to the direction of gravity. The plane orthogonal to the gravity comprises two orthogonal axes orthogonal to the direction of gravity. Further, displacement values are evaluated based on a user input for placement of the mobile device with respect to user's body, and integration of the acceleration values across the two orthogonal axes with respect to time. A direction of motion of the user is estimated based on a ratio of the displacement values along the two orthogonal axes.

Abstract: This disclosure relates generally to surveillance, and more particularly to perform entry and exit monitoring of a user. In an embodiment, the system identifies an entry event (during which a user enters a room being surveilled) and/or an exit event (during which a user leaves a room being surveilled), based on a Bluetooth Low Energy (BLE) based system. This system uses two receivers one positioned outside and the other positioned inside the room being surveilled, to receive BLE beacon transmitted by a user who is in motion. Based on relative change in Received Signal Strength Indicator (RSSI) values of this beacon with respect to the first and second receivers, the system identifies direction of movement of the user, and in turn, determines one of the entry or exit events.

Abstract: A method and system for real-time analytics of sensor-based data is disclosed. Also disclosed is a Cloud-based Paltform-as-a-Service (PaaS) offering for sensor driven applications with services and features for their complete life-cycle management including prompt development, testing, deployment and so forth. The method of the present disclosure enables real-time tracking of various physical parameters and attributes related to smart-spaces using sensor devices implemented in the premises of the smart-space environment and using crowd-sourced user input data. Further, the parameters obtained are sent to the cloud-computing server, wherein the analytics are performed in real-time based on the obtained parameters.

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.

Abstract: The application provides a method and system for automatically recommending television program to a user. The application provides a method and system for recommending related television programs while viewing video on internet based, using context of the said video. Further, the application provides a method and system for extracting electronic program guide information for all the channels available on the television and correlating them for recommending related television programs.