Abstract: The disclosure relates to system and method for generating recommendations for capturing images of a real-life object with essential features. The method includes detecting an Augmented Reality (AR) plane for a target object. The method further includes capturing a set of poses corresponding to the target object and a set of coordinate points in the AR plane. The set of poses includes a tracking marker, and the set of coordinate points indicates a location of the target object. The method further includes determining an instant distance between the AR imaging device and the target object, and an instant angle of the AR imaging device with respect to the target object. The method further includes dynamically generating the recommendations for adjusting a position and an orientation of the AR imaging device with respect to the target object.

Abstract: This disclosure relates to method and system for validating an Autonomous Vehicle (AV) stack. The method may include receiving an Operational Design Domain (ODD) and real-world data for evaluating at least one of an Advanced Driver Assistance System (ADAS) and the AV. The ODD is based on at least one feature of at least one of the ADAS and the AV. For each of a plurality of iterations, the method may further include generating a driving scenario based on the ODD of the AV and the real-world data through a Quality of Ride Experience (QoRE)-aware cognitive engine, plugging and running at least one of the ADAS and the AV algorithm based on the driving scenario, and determining a set of performance metrics corresponding to the at least one feature of at least one of the ADAS and the AV in the driving scenario based on the simulating.

Abstract: Disclosed herein is method and congestion management system for reducing road congestion. Traffic data related to plurality of vehicles is analyzed by a trained traffic model for predicting speed of each vehicle and signal time associated with intersection points. Optimal speed for each vehicle and an optimal signal time for each of the intersection points is determined based on analysis of the previous values and historic traffic data. The determined optimal speed and the optimal signal time are respectively provided to a vehicle control system associated with each vehicle and a traffic controller associated with each intersection point. In an embodiment, the method of present disclosure reduces traffic congestion on any selected portion of road. Further, the method of present disclosure eliminates and/or minimizes number of instances that a vehicle has to stop/start at the traffic signals, thereby enhancing fuel economy and reducing waiting time for the vehicles.

Abstract: The present disclosure is related to Just-In-Time (JIT) services, that discloses a method and system for providing JIT services to automotive users. A Point of Interest (PoI) service aggregator system may receive a service request from an automotive user, including one of: information related to a preferred PoI service provider, request to recommend PoI service providers, or request to list PoI service providers based on user query. Based on service request, the PoI service aggregator system may perform one of: dynamically on-boarding the preferred PoI service provider, recommending PoI service providers, or providing PoI service providers based on user query. Thereafter, a real-time synchronization may be established between a candidate PoI service provider and the automotive user to enable the candidate PoI service provider to determine arrival events including an estimated time of arrival and non-arrival events of the automotive user, to provide JIT service to the automotive user.

Abstract: The present invention relates to a method of detecting an anomaly using a plurality of images. The method comprises determining a subset of images from the plurality of images, comprising one or more first features. Further, one or more regions comprising one or more second features are identified in each image from the subset of images. Finally, detecting the anomaly from the subset of images based on the one or more regions. Therefore, accuracy of detecting anomalies is increased by using the subset of images.

Abstract: A method of determining a navigation trajectory for an autonomous ground vehicle (AGV) is disclosed. The method may include receiving first Region of Interest (ROI) data associated with an upcoming trajectory path, and receiving predicted attributes associated with a future navigation trajectory for the upcoming trajectory path. The predicted attributes are derived based on map for the upcoming trajectory path. The method may further include modifying the predicted attributes based on environmental attributes extracted from first ROI data to generate modified attributes, and dynamically receiving a second ROI data associated with the upcoming trajectory path upon reaching the upcoming trajectory path. The method may further include predicting dynamic attributes associated with an imminent navigation trajectory for the upcoming trajectory path based on the second ROI data, and refining the modified attributes based on the one or more dynamic attributes to generate a final navigation trajectory.

Abstract: System and method for diagnosing a disease using image classification is provided. The method includes receiving diagnostic images associated with a subject. The diagnostic images comprise a first image and a second image captured at a first instance of time and at a second instance of time, respectively. The method further includes extracting feature maps from the first image and the second image, using a first pipeline and a second pipeline of stacked convolutional layers of a temporal convolutional neural network (CNN) model respectively. The method further includes identifying relevant feature maps from the feature maps using temporal CNN layer of the temporal CNN model, generating a concatenated feature map based on the relevant feature maps, determining an image class corresponding to the second image using fully connected layers of the temporal CNN model, and diagnosing the disease associated with the subject based on the image class.

Abstract: A method and system for determining and resolving network issues impacting application performance in multi-domain networks is disclosed. The method includes obtaining at least one of health and performance data associated with an application and one or more alerts related to fault and/or performance issues associated with the application. The method further includes determining at least one of network faults and performance issues that influence at least one of fault and/or performance issues associated with the application. The method further includes determining one or more underlying network problems that impact performance of the application. The method further includes determining at least one appropriate resolution action to address the one or more underlying network problems, implementing the at least one appropriate resolution action; monitoring an effectiveness of the implementation of the at least one appropriate resolution action; and adapting at least one of rules, parameters, and thresholds.

Abstract: The present invention discloses a method and a system for navigating an Autonomous Ground Vehicle (AGV) using a radio signal and a vision sensor. The method comprising generating a trajectory plan for a short distance from a path plan, wherein the path plan is determined using destination location and AVG location, identifying an approximate AGV location using a radio signal-based trilateration mechanism, estimating AGV location error with respect to a road lane center by determining distance from the approximate AGV location to road boundary and road lane marking line and orientation difference between AGV orientation and road orientation, and correcting the trajectory plan by using the estimated AGV location error for navigating an AGV.

Abstract: This disclosure relates generally to artificial intelligence system, and more particularly to method and system for tracing a learning source of an explainable artificial intelligence (AI) model. In one example, the method may include receiving a desired behavior of the explainable AI model with respect to input data, generating a learning graph based on similarities among a plurality of learning sources with respect to the input data for the desired behavior and for a current behavior, retracing a learning of the explainable AI model by iteratively comparing the learning graph for the desired behavior and for the current behavior at each of a plurality of layers of the explainable AI model starting from an outer layer, and detecting the learning source responsible for the current behavior based on the retracing.

Abstract: Method and system for predicting failures in interconnected systems based on quantum computing is disclosed. The method may include identifying a set of unique patterns from input data received from a plurality of input data sources, determining a correlation between at least two input data sources, creating a plurality of sets of clusters corresponding to the plurality of input data sources based on the correlation, extracting data associated with each of the set of unique patterns based on the plurality of sets of clusters, predicting, based on the extracted data, a failure of at least one interconnected system using a trained ML model, processing the extracted data associated with each of the set of unique patterns and information associated with the predicted failure through a quantum computing layer, and generating, through the quantum computing layer, at least one corrective action for the at least one interconnected system.

Abstract: The disclosure relates to method and system for performing real-time data validation. The method includes fetching a plurality of metadata from a set of external data sources and a set of external file storage systems. The plurality of metadata is fetched along with a set of connection configuration parameters and column mapping information The method further includes generating a set of clusters for performing data validation in an external processing infrastructure based on an analysis of the plurality of metadata and of the external processing infrastructure. The method further includes determining a set of test scripts from a plurality of test scripts based on the column mapping information and the set of connection configuration parameters. The method further includes performing a real-time data validation by executing the set of test scripts in the set of clusters.

Abstract: The disclosure relates to system and method for providing assistance to a user using augmented reality. The method includes acquiring a video stream and a set of data associated with a task being performed by a user, in real-time, using a camera and/or a sensor device. The video stream includes sequential frames. The method further includes determining a present state associated with the task based on the sequential frames using an Artificial Neural Network (ANN) based action prediction model; determining scenarios and events corresponding to the scenarios based on the video stream and the set of data using an ANN based augmented intelligence model; and determining sequential instructions required for assisting the user to accomplish the task, dynamically, based on the present state and the events associated with the task, using at least one of a rule-based engine and an ANN based instruction prediction model.

Abstract: The present invention discloses a method and a server for authentication adaptive to a secured application. The method comprising encrypting a part of continuous streams of random real-time data using a user's public key to form a first encrypted data when the request is received from a first entity, transmitting the first encrypted data to the first entity, wherein the first entity communicates the first encrypted data to a second entity, receiving a second encrypted data from the second entity, wherein the second encrypted data is created by decrypting the first encrypted data using a user's private key and encrypting the decrypted data using the user's private key, authenticating the second encrypted data received from the second entity by comparing data decrypted from the second encrypted data with the part of continuous streams of random real-time data stored in the authentication server and initiating action based on authentication.

Abstract: The present disclosure relates to generating maneuvering trajectories using Machine Learning (ML) model. The ML model scores each candidate maneuvering trajectories based on a plurality of dynamic profile parameters. A candidate maneuvering trajectory from a plurality of candidate maneuvering trajectories, having a best trajectory score is selected as the final maneuvering trajectory and is provided to the vehicle for navigating according to the final maneuvering trajectory. The final maneuvering trajectory is the most ideal trajectory as it is generated using the ML model based on the plurality of dynamic profile parameters. Also, the vehicle navigation is most efficient when navigated according to the final maneuvering trajectory.

Abstract: This disclosure relates to a method and system for identifying products using digital fingerprints. The method includes receiving, by a product tracking system, a set of images corresponding to a product, wherein the set of images are received along with associated context information. The method generates a set of standardized images by pre-processing the set of images. Each standardized image of the set of standardized images are further segmented into a plurality of zones. A zone wise fingerprint is generated for each zone of the plurality of zones. A product digital fingerprint is generated for the product by combining zone wise fingerprints associated with the set of standardized images, wherein the product digital fingerprint identifies the product.

Abstract: The disclosure relates to method and system for improving performance of an artificial neural network (ANN) model. The method includes receiving the ANN model and input dataset. The ANN model includes neurons arranged in multiple layers and employing corresponding activation functions. The method further includes assigning a random activation threshold value to each of the corresponding activation functions, determining activated neurons in each layer for a majority of input data in the input dataset based on the random activation threshold value for each of the corresponding activation functions, identifying removable layers based on a number of activated neurons and a pre-defined threshold value, evaluating a relative loss of the ANN model upon removing each removable layer from the ANN model and for a random input data in the input dataset, and deriving a modified ANN model by removing one or more of the removable layers based on the evaluation.

Abstract: The present invention relates to a method of determining stock in an inventory. The method comprises obtaining one or more images comprising one or more objects. Further, estimating a three dimensional (3D) location of a Stock Keeping Unit (SKU) marker associated with each of one or more visible objects. Furthermore, determining a stacking pattern of the one or more objects for each level on the pallet using one of the 3D location of SKU marker and a learning model. Thereafter, detecting at least one of presence or absence of one or more undetected objects at each level based on the stacking pattern and the 3D location of the SKU marker. Finally, determining the stock in the inventory based on the presence or the absence of the one or more undetected objects and the one or more visible objects.

Abstract: The present invention discloses method and virtual assistance system for determining response to user queries. The virtual assistance system receives data comprising plurality of interaction between one or more users and one or more real agents for resolving query, where data is classified into user and real agent data. Entities and intent identified from each of the classified user data and real agent data are classified using predefined domain model. The entities and intent are combined to identify plurality of sequence of resolution data. Based on classification of entities and intent, virtual assistance system determines first set of resolution data and second set of resolution data. Thereafter, each of plurality of sequence of resolution data is clustered into one or more category associated with type of users, based on first set and second set of resolution data, parameters associated with users and historical resolution data used for responding to query.

Abstract: A method and road assistance system for safe handling an autonomous vehicle during emergency failure situation is disclosed. The road assistance system establishes a network connection with autonomous vehicle, where request for the network connection is transmitted by the autonomous vehicle on detection of operation failures. Upon establishing the network connection with the autonomous vehicle, vehicle failure information is received from the autonomous vehicle. The road assistance system determines type of failure in the autonomous vehicle based on the vehicle failure information. Further, current surrounding environment information is obtained for the autonomous vehicle from one of autonomous vehicle and one or more sensing devices located in proximity to the autonomous vehicle. Thereafter, the road assistance system generates at least one control instruction based on the type of failure and the current surrounding environment information.