Abstract: Provided is a method for predicting an internal state of a machine. The method includes obtaining real time machine test data from a plurality of sensors installed in a test bench of the machine and identifying differences between the obtained real time machine test data and simulation data of a machine model. The method further includes updating the machine model by eliminating the identified differences and generating synthetic data corresponding to each of a normal condition and at least one deteriorated condition of the machine using the updated machine model. The method further includes detecting one or more deterioration levels of the machine over a period of time along with timestamp data based on a plurality of machine parameters using an Artificial Intelligence (AI) model and predicting a deterioration time period of the machine indicating an RUL of the machine based on the detected deterioration levels.

Abstract: A method for predicting a condition of living-being in an environment, the method including capturing image-data associated with the at-least one person and based thereupon determining a current-condition of the person; receiving content from a plurality of content-sources with respect to said at least one person being imaged, said content defined by at least one of text and statistics; defining one or more weighted parameters based on allocating a plurality of weights to at least one of the captured image data and the received content based on the current-condition; and predicting, by a predictive-analysis module, a condition of the at-least one person based on analysis of the one or more weighted parameters.

Abstract: The present subject matter refers a method to evaluate concentration of a living being based on artificial intelligent techniques. The method comprises detecting a continuous increase in concentration of a living being based on an artificial neural network (ANN), The method comprises receiving a parameter of the continuous increase in concentration, determining a first value of the concentration based on a first condition, said first condition defined by increase of the received parameter by more than a first predetermined threshold; and determining a second value of the concentration based on a second condition, said second condition defined by decline in the concentration from the first value by more than a second predetermined threshold.

Abstract: A system for gaze direction detection is disclosed herein. The system comprises a face detection unit configured to detect face information from a captured image of a spectator, a head pose unit configured to detect a head pose angle based on the face information; an eye measurement unit configured to detect eye information of at-least one of a left eye or a right eye of the spectator based on the detected face information; an eye-gaze detection unit configured to estimate a gaze angle of the at-least one of the left eye or the right eye of the subject based on the eye information; a conditional gaze detection unit configured to calculate a resultant gaze angle based on the estimated gaze angles of the left eye and right eye and the head pose angle; and an effective gaze detection unit configured to estimate an effective gaze angle based the resultant gaze angle and head-pose angle.

Abstract: A method for predicting a condition of living-being in an environment, the method including capturing image-data associated with the at-least one person and based thereupon determining a current-condition of the person; receiving content from a plurality of content-sources with respect to said at least one person being imaged, said content defined by at least one of text and statistics; defining one or more weighted parameters based on allocating a plurality of weights to at least one of the captured image data and the received content based on the current-condition; and predicting, by a predictive-analysis module, a condition of the at-least one person based on analysis of the one or more weighted parameters.

Abstract: The present subject matter refers an image-processing method comprises receiving a first-image of an object captured by a range-imaging device at a first viewing location. The transforming the first-image into a second image of the object, said second image corresponding to an image captured based on range-imaging at a second viewing location with respect to the object. The gaps in the second-image are identified based on comparison with the first image, such that the identified gaps within the second image are complemented to result in a complemented second image.