Abstract: A method, device and system for managing collaboration amongst robots is disclosed. The method may include assigning a color tag from a set of predefined color tags to each of a plurality of robots, based on associated functional capabilities. The method may further include dynamically creating a plurality of groups for a plurality of tasks based on at least one attribute associated with each of the plurality of tasks and functional capabilities associated with the plurality of robots. The method may include electing a plurality of chief robots for the plurality of groups based on a first predefined logic. The method may include selecting a prime robot from the plurality of chief robots based on a second predefined logic and the selected prime robot may be configured to monitor activity of each of the plurality of groups and each robot in each of the plurality of groups.

Abstract: This disclosure relates to method and system for performing effective orchestration of cognitive functions (CFs) in a distributed heterogeneous communication network. In one embodiment, the method may include determining a fault or a performance issue and associated causes, related to a set of network slices in the distributed heterogeneous communication network or a set of services across the set of network slices, using CFs associated with each of the set of services or with each of the set of network slices. The method may further include determining possible resolutions for the fault or the performance issue based on the associated causes, identifying a resolution by evaluating each of the possible resolutions for at least one of a suitability to or an impact on the set of services or the set of network slices, and implementing the resolution on one or more affected network segments of the set of network slices.

Abstract: Disclosed subject matter relates to a field of vehicle navigation system that performs a method for navigating an autonomous vehicle at an intersection of roads. An intersection management system may receive sensor data including at least one of depth of an object, images and a video of environment surrounding the autonomous vehicle. Further, traffic police and auxiliary objects associated with each traffic police are detected from plurality of objects of interest present in the images, when the autonomous vehicle is within a predefined distance from an intersection of roads. Thereafter, a correlation matrix comprising inferred data related to each traffic police and the auxiliary objects may be generated. Based on the correlation matrix, the video and the images, a gesture of the traffic police may be determined accurately. Finally, navigation information may be determined based on the correlation matrix and determined gesture, for navigating the autonomous vehicle.

Abstract: A method and activity continuation system for managing continuous execution of an activity during a user device switchover is disclosed. The method includes detecting a switchover from a first user device to a second user device, where one or more activities are being executed in the first user device during the switchover. On detecting the switchover, the method includes determining device data and user related data associated with the second user device and applications data associated with one or more activities operated at the first user device. Further, based on the device data, the user related data and the applications data, contextual information is generated for the one or more activities. Thereafter, the method includes managing continuous execution of the one or more activities in the second user device on switchover based on the contextual information. Thus, the present disclosure facilitates users in providing application session continuity while switching between user devices.

Abstract: A method and system for navigating vehicles based on road conditions determined in real-time is disclosed. The method includes the steps of receiving a first dataset including an image of a section of a road within a Field of View (FOV) of a camera attached to a vehicle and a second dataset associated with the road. The method further includes detecting edges and a vanishing point in the image, correcting road perspectivity in the image, and determining surface anomalies in the road based on a set of parameters, the second dataset and a Time of Flight technique (ToF), creating a digital elevation model for the image, and assigning a value, in real-time, from a predefined value range to each of a plurality of grids in the image based on a digital elevation model to generate a digital elevation image. The set of parameters includes volume associated with the surface anomalies.

Abstract: A method of identifying relevant keywords from a document is disclosed. The method includes splitting text of the document into a plurality of keyword samples, such that each of the plurality of keyword samples comprises a predefined number of keywords extracted in a sequence. Further, each pair of adjacent keyword samples in the plurality of samples includes a plurality of common words. The method further includes determining a relevancy score for each of the plurality of keyword samples based on at least one of a trained Convolution Neural Network (CNN) model and a keyword repository. The method further includes classifying keywords from each of the plurality of keyword samples as relevant keywords or non-relevant keywords based on the relevancy score determined for each of the plurality of keyword samples.

Abstract: Disclosed herein is method and interactive assistance system for providing personalized assistance to a driver or person in an autonomous vehicle. Parameters related to the user and the vehicle are monitored and compared with historical data to determine a deviation in the parameters. An abnormal condition is detected when the deviation is more than an optimal threshold. Further, a personalized interaction is initiated with the user through a selected one of the interactive assistance engine and one or more assistive activities are performed for handling the abnormal condition. In an embodiment, the method of present disclosure enhances both safety and user experience of the user of the autonomous vehicle.

Abstract: This disclosure relates to method and system for validating readings of orientation sensor mounted on autonomous ground vehicle (AGV). The method may include receiving distances and angles of observation of at least two fixed objects with respect to AGV at a first position and then at a second position, calculating a first orientation and a second orientation of AGV at the first position and at the second position respectively based on the distances, the angles of observation, and coordinate positions of each of the at least two fixed objects, determining an actual change in orientation of AGV based on the first orientation and the second orientation, and validating the readings of the orientation sensor based on the actual change in orientation. The at least two fixed objects are objects with pre-identified properties in a field of view of a vision sensor mounted on AGV and on both sides of AGV.

Abstract: A system and method for auto resolution of errors during compilation of data segments is disclosed. The method includes the steps of detecting one or more errors to be resolved associated with a data segment, determining an error type for each of the one or more errors from predefined error types based on neuron activations and a code logic derived from the data segment, arranging the one or more errors in a sequence of resolving, predicting a solution for each of the one or more errors, resolving the one or more errors sequentially for generating an error free data segment, and optimizing the error free data segment. The method further includes generating a pseudo code corresponding to the error free data segment and converting the pseudo code into at least one of the plurality of native languages.

Abstract: The present disclosure relates to a methods and systems for autonomous parking of vehicles (103). The vehicle receives an input signal for parking the vehicle in parking premises (100) comprising a plurality of parking space (102) having an elevated parking boundary indicator (101). The vehicle (103) obtains a map of the parking premises (100). Further, the vehicle (103) receives a plurality of LIDAR data points (205) of the parking premises (100) and identifies a plurality of linear patterns from the plurality of LIDAR data points (205). Thereafter, the vehicle (103) detects at least two linear patterns (401) from the plurality of linear patterns, having a predefined length and parallelly spaced apart, indicating the elevated parking boundary indicator (101) of an available parking space, where the vehicle (103) can be autonomously parked in the available parking space.

Abstract: A method for de-prejudicing Artificial Intelligence (AI) based anomaly detection is disclosed. The method includes training and testing an AI model based on a labelled training data, determining whether the AI model reveals a bias, based on one or more prejudicing variables, and thereafter re-building the AI model based on iterative process of de-prejudicing the feature set of the AI model and de-prejudicing the training data. A check is made to determine whether the feature set of the AI model feature set includes any proxy variables associated with any of the prejudicing variables and identifies the weight to be assigned to a proxy variable based on the intra-cohort variation in separate machine learning models built for each cohort associated with each value of the prejudicing variable. The feature set of the AI model is de-prejudiced based on the explanatory power of the proxy variables independent of the prejudicing variables.

Abstract: A method and system for task execution in dynamic heterogeneous robotic environment is disclosed. The method includes extracting data associated with a plurality of data categories and further deriving a plurality of factors from the extracted data. The method further includes determining a plurality of correlations among the plurality of factors based on the deep learning network. The method further includes deriving a plurality of sentiment parameters for a set of factors from the plurality of factors based on the plurality of correlations. The method may further includes simulating execution of the at least one current task by employing a plurality of robots. The method may further includes iteratively re-adjusting at least one of the plurality of sentiment parameters based on reinforcement learning performed on a result of the simulating. The method may further includes executing the at least one current task by employing the plurality of robots.

Abstract: The present disclosure relates to a method of stitching images captured by a vehicle. A first image and a second image are received. The first image and the second image are segmented based on characteristics of pixels. Groups of pixels having similar characteristics are identified to form clusters in a predetermined portion of overlap of the first image and the second image. A confidence score is generated for the first image and the second image. A difference in the confidence score is computed. At least one of, the first image capturing unit and the second image capturing unit is aligned to capture at least one of, a first aligned image and a second aligned image based on the difference in the confidence score. The first aligned image and the second aligned image are stitched.

Abstract: This disclosure relates generally to information processing, and more particularly to method and system for generating a learning path for a topic. The method may include extracting a plurality of key phrases from each of a plurality of learning resources related to the topic, determining a learning context for each of the plurality of learning resources based on the plurality of key phrases, forming a set of key phrase groups from among the plurality of key phrases for each of the plurality of learning resources, determining a relationship among the key phrases in each of the set of key phrase groups based on the learning context, generating a structured graph for the plurality of learning resources based on the plurality of key phrases and the relationship among the key phrases, and generating the learning path for the topic based on the structured graph for the plurality of learning resources.

Abstract: This disclosure relates to method and system for improving relevancy and ranking of a search result for a search query. The method may include accessing documents of the search result. Each document may be associated with derived document features that may be derived based on an evaluation of document features with respect to query features. For each document, the method may further include determining a feature score for each of the derived document features based on one or more of the query features and initializing each element of an order array with the feature score for each ordered document feature. The ordered document features may be the derived document features that are ordered based on pre-defined rules. The method may further include ranking the documents by comparing and ranking the order array for each of the documents and presenting an updated search result based on the ranking of the documents.

Abstract: Disclosed herein is method and system for detecting intent as an ordered sequence from user query. The system identifies word embedding feature for each word using word embedding model and identifies Part of Speech tag feature. Thereafter, system determines dependency label feature based on dependency role and POS tag feature. Further, system provides feature vector comprising POS tag feature of target word, POS tag feature of previous two words of target word, word embedding feature of target word, word embedding feature of head word for each target word and dependency label feature of target word to deep neural network for detecting intent as ordered sequence. The ordered sequence includes desired action in user query, focal point pertaining to which desired action must be performed and one or more descriptors associated with focal point. In this manner, in present disclosure, overall intent from user query is captured for accurately providing response.

Abstract: This disclosure relates generally to image processing, and more particularly to method and system for reconstructing an image. In one embodiment, the method includes pre-processing an input image to generate character images corresponding to characters in the input image, determining a local character thickness threshold value for each character image, determining a global character thickness threshold value for the input image based on the local character thickness threshold values for the character images, and reconstructing each character image based on the local character thickness threshold value for each character image and the global character thickness threshold value to generate reconstructed character images. The local character thickness threshold value in a character image may be based on a set of character pixel values in a pre-determined number of segments in the character image. The method further includes re-constructing the input image based on the reconstructed character images.

Abstract: The present invention relates to a method of identifying a brand and a model of a vehicle. The method comprises obtaining one or more video frames. Further, the method comprises detecting one of presence or absence of text in the at least one vehicle. Upon detecting the presence of the text, the method comprises determining at least one of the brand and the model of the at least one vehicle by accumulating the text recognized in the one or more video frames. Further, identifying at least one of the brand and the model of the at least one vehicle based on an accumulated text. Upon detecting the absence of the text, the method comprises determining the brand of the at least one vehicle based on logo associated with the vehicle.

Abstract: The present invention discloses method and system for multimodal analysis based emotion recognition. The method comprising segmenting video data of a user into a plurality of video segments. A plurality of visual features, voice features and text features from the plurality of video segments is extracted. Autocorrelation values among each of the plurality of visual features, the voice features, and the text features is determined. Each of the plurality of visual features, the voice features and the text features is aligned based on video segment identifier and the autocorrelation values to obtain a plurality of aligned multimodal features. One of two classes of emotions is determined for each of the plurality of aligned multimodal features. The determined emotion for each of the plurality of aligned multimodal features is compared with historic multimodal features from a database, and emotion of the user is determined at real time based on comparison.

Abstract: This disclosure relates to method and system for of dynamically annotating data or validating annotated data. The method may include receiving input data comprising a plurality of input data points. The method may further include one of: a) generating a plurality of annotations for each of the plurality of input data points using at least one of a state-label mapping model and a comparative ANN model, or b) receiving the plurality of annotations for each of the plurality of input data points from an external device or from a user, and validating the plurality of annotations using at least one of the state-label mapping model and the comparative artificial neural network (ANN) model.