Abstract: The disclosure relates to method and system for generating trajectory plan for autonomous ground vehicles (AGV). The method includes assessing an upcoming goal position for an AGV with respect to a current position of the AGV to establish a need for preparing a trajectory plan for a critical segment of the path. The method further includes determining, upon establishing the need, a next free road region based on a hint next rest pose along the critical segment, generating a trajectory sub-plan corresponding to the next free road region by iteratively determining a set of intermediate poses between the current rest pose and the hint next rest pose, and generating the trajectory plan for the critical segment of the path by iteratively generating the trajectory sub-plans between the current rest pose and the final goal pose.

Abstract: The disclosure relates to method and system for localizing an autonomous ground vehicle (AGV). In an example, the method includes receiving a line drawing corresponding to a two-dimensional (2D) camera scene captured by a camera mounted on the AGV, determining a plurality of ground-touching corner edges based on a plurality of horizontal edges and a plurality of vertical edges in the line drawing, determining a plurality of three-dimensional (3D) points corresponding to a plurality of 2D points in each of the plurality of ground-touching corner edges based on a mapping relationship between an angular orientation of a ground touching edge of an object in real-world and in camera scene and a set of intrinsic parameters of the camera, generating 2D occupancy data by plotting the plurality of 3D points in a 2D plane, and determining a location of the AGV based on the 2D occupancy data and the mapping relationship.

Abstract: Disclosed herein is method and system for determining correctness of Lidar sensor data used for localizing autonomous vehicle. The system identifies one or more Region of Interests (ROIs) in Field of View (FOV) of Lidar sensors of autonomous vehicle along a navigation path. Each ROI includes one or more objects. Further, for each ROI, system obtains Lidar sensor data comprising one or more reflection points corresponding to the one or more objects. The system forms one or more clusters in each ROI. The system identifies a distance value between, one or more clusters projected on 2D map of environment and corresponding navigation map obstacle points, for each ROI. The system compares distance value between one or more clusters and obstacle points based on which correctness of Lidar sensor data is determined. In this manner, present disclosure provides a mechanism to detect correctness of Lidar sensor data for navigation in real-time.

Abstract: This disclosure relates to method and system for data sampling using an artificial neural network (ANN) model. In an embodiment, the method includes identifying a plurality of numerical data columns and a plurality of categorical data columns in population dataset, determining a set of predictor variables and a set of predictand variables by applying a linear regression on the plurality of numerical data columns, generating a sequential prediction model based on the set of predictor variables and the set of predictand variables, and performing stratified sampling on the plurality of categorical data columns to generate a set of stratified samples. The method further includes generating a sample key based on the set of stratified samples and the sequential prediction model, and generating a sample dataset representative of the population dataset based on the sample key.

Abstract: This disclosure relates to method and system for certificate-less security management of interconnected hybrid resources. The method includes selecting at least one hybrid resource from a plurality of hybrid resources in network to install pre-calculated security configuration. The method further includes receiving a One Time Password (OTP) valid for pre-configured time period, in response to an identity generation request for a hybrid resource; installing security data payload including the OTP and the pre-calculated security configuration, in the hybrid resource; receiving an identity issuance request from the hybrid resource through a secure channel upon installation of security data payload in the hybrid resource; assigning unique identity to the hybrid resource upon successful validation of the OTP received in identity issuance request; and generating, upon assignment, metadata corresponding to the hybrid resource for a security association map (SAM) associated with the hybrid resource.

Abstract: The present disclosure relates to method and system for performing classification of real-time input sample using compressed classification model. Classification system receives classification model configured to classify training input sample. Relevant neurons are identified from neurons of the classification model. Classification error is identified for each class. Reward value is determined for the relevant neurons based on relevance score of each neuron and the classification error. Optimal image is generated for each class based on the reward value of the relevant neurons. The optimal image is provided to the classification model for generating classification error vector for each class. The classification error vector is used for identifying pure neurons from the relevant neurons. A compressed classification model comprising the pure neurons is generated. The generated compressed classification model is used for performing the classification of real-time input sample.

Abstract: A method and system for performing adaptive consensus in a distributed ledger network are disclosed. The method includes identifying a selector node from plurality of nodes within distributed ledger network, based on random selection algorithm. The method includes adaptively selecting set of consensus nodes from plurality of nodes based on set of predefined node parameters and plurality of sensitivity parameters to create an unverified block in a ledger of each of adaptively selected set of consensus nodes. The method includes computing hash value for each of at least one new transaction in distributed ledger network. The method includes performing consensus based on computed hash value for identifying set of valid transactions in unverified blocks created by each of adaptively selected set of consensus nodes. The method includes creating verified block including set of valid transactions, and commits verified block to distributed ledger in distributed ledger network.

Abstract: This disclosure relates to method and system for managing Internet of Things (IoT) devices in heterogeneous communication networks. The method includes receiving metadata corresponding to each of a set of IoT devices including a plurality of IoT sensors; validating each of the set of IoT devices based on the received metadata; establishing communication with each of the set of IoT devices through an associated predefined data communication protocol; receiving real-time data from each of the plurality of sensors associated with each of the set of IoT devices through an IoT protocol; monitoring the real-time data received from each of the plurality of sensors at predefined time intervals through a Graphical User Interface (GUI); and managing one or more device parameters corresponding to each of the set of IoT devices in the heterogeneous communication network through the GUI based on the real-time data.

Abstract: The present disclosure is related to Virtual Desktop Infrastructure (VDI) that discloses a method and system for predicting an occurrence of a failure condition in a VDI environment. A failure prediction system simulates a workload condition, to generate a functional experience corresponding to each information system. Thereafter, the failure prediction system determines a deviation in, performance patterns of each information system, and the functional experience corresponding to each information system, based on historical data of the corresponding information system and transactional data of an enterprise. Finally, an occurrence of a failure condition in a VDI environment is predicted by performing predictive analytics on the determined deviation, based on one or more benchmark metrics. The present disclosure rectifies the performance issues based on the prediction, which in turn prevents the occurrence of the failure condition, thereby improving user experience and productivity in the VDI environment.

Abstract: A method and system for rendering object detection graphics on image frames is disclosed. The method includes receiving an object detection information for an image frame. The object detection information includes bounding box data and a class label data associated with an object in the image frame. The method further includes determining a first value for each pixel in a first set of pixels associated with a bounding box for the object and determining a second value for each pixel in a second set of pixels associated with a class label for the object. The method includes modifying values for each of the first set of pixels based on the associated first value to render the bounding box on the image frame and modifying values for each of the second set of pixels based on the associated second value to render the class label on the image frame.

Abstract: This disclosure relates to method and system for verifying a positive classification performed by an artificial neural network (ANN) in a given class. The method includes generating a weight matrix comprising a weight of each neural node in a given layer; determining a contribution factor of a given neural node in the given layer with respect to an output of the ANN for the given class based on a known input vector to the given layer and a modified weight matrix; and generating a dominance matrix based on the contribution factor of each neural node in the given layer. The method further includes determining a rank of each neural node based on the corresponding dominance factor; and verifying the positive classification performed by the ANN in the given class for a test input vector based on the rank of each neural node in each layer of the ANN.

Abstract: A method and system for maintenance of network slice templates for slice orchestration is disclosed. The method includes extracting a plurality of parameters from a template data within a template request message and determining at least one network slice template from a plurality of templates, based on comparison of the plurality of parameters with parameters associated with the plurality of templates. The method further includes receiving performance feedback for each of the at least one network slice template based on usage of the at least one network slice template and determining modifications required to be performed on the at least one network slice template, based on the performance feedback. The method includes adapting the at least one network slice template based on the determined modifications.

Abstract: This disclosure relates to method and system for improving classifications performed by artificial neural network (ANN) model. The method may include identifying, for a classification performed by the ANN model for an input, activated neurons in each neural layer of the ANN model; and analyzing the activated neurons in each neural layer with respect to Characteristic Feature Directive (CFDs) for corresponding neural layer and for a correct class of the input. The CFDs for each neural layer may be generated after a training phase of the ANN model and based on neurons in corresponding neural layer that may be activated for a training input of the correct class. The method may further include determining differentiating neurons in each neural layer that are not activated as per the CFDs for the correct class of the input based on the analysis; and providing missing features based on the differentiating neurons.

Abstract: System and method of detecting infestation in agricultural products is disclosed. In one embodiment, an infestation detection system captures hyperspectral imaging data and depth imaging data for a plurality of points on an agricultural product upon directing a light source at the agricultural product. The system analyses the captured imaging data to derive morphological details as well as spectral signatures for complete 360° view of the plurality of points on the agricultural product. In an embodiment, the spectral signatures may be corrected for one or more pixels associated with the plurality of points in the agricultural product by integrating the hyperspectral imaging data with the depth imaging data. The system further classifies one or more regions of the agricultural product based on matching of spectral signatures for the one or more pixels with pre-defined spectral signatures stored for a plurality of agricultural products, and accordingly detect infestation.

Abstract: The present invention relates to a method for generating abstractive summary. The method comprises receiving a query for generating an abstractive summary from a document and splitting the query into one or more lexical units. Further, a semantic graph and a graph index is generated based on a role assigned to the one or more lexical units. Furthermore, a measure of information is determined for the retrieved one or more sentences. The one or more sentences having a semantic graph analogous to the generated semantic graph of the query are retrieved from the document. Finally, at least one of re-ordering and re-phrasing is performed on at least one of the retrieved one or more sentences based on the computed measure of information and the one or more lexical units in the retrieved one or more sentences to generate the abstractive summary.

Abstract: A method and system for automating repetitive task on a user interface is disclosed. The method includes identifying a plurality of Document Object Model (DOM) elements from a repetitive pattern. The method further includes identifying a set of dynamic DOM elements from the plurality of DOM elements. The method further includes determining a path and a path position within the application code of the repetitive pattern for each of the set of dynamic DOM elements. The method further includes training an Artificial Intelligence (AI) model to identify the repetitive pattern and to identify the corresponding path and the path position within the application code component, for each of the set of dynamic DOM elements. The method further includes automatically executing a code for each of the set of dynamic DOM elements based on the associated path and path position.

Abstract: Disclosed subject matter relates to field of vehicle navigation system that performs a method of generating trajectory for navigating an autonomous vehicle. A trajectory generating system associated with autonomous vehicle detects Points of Interest (POIs) for a selected segment which is at predefined distance from current position of autonomous vehicle, in real-time. Further, features of each of the POIs are determined and first level trajectory is generated for selected segment based on features of POIs proximal to selected segment. Furthermore, the trajectory generating system generates second level trajectory for portions of first level trajectory from current position of autonomous vehicle by modifying each portion based on real-time environment data.

Abstract: A method and authentication system for alleviating authenticity of sensors in biometric authentication is disclosed. The authentication system receives fingerprint data from a plurality of sensing devices configured in the authentication system and extract one or more attributes associated with the fingerprint data. An expanded value for each of the one or more attributes is determined based on one or more predefined techniques. The authentication system (101) trains a model associated with authentication of fingerprints using the one or more attributes and corresponding expanded value. Further, one or more errors associated with the fingerprint data are predicted based on fingerprint data received over a period of time in real-time and the model is retrained based on the predicted one or more errors to alleviate authenticity of sensors in biometric authentication.

Abstract: A method and system for executing processes in an operating system is disclosed. The method may include assigning a tag Identifier (ID) and a first tree ID to each of a plurality of processes based on associated at least one attribute. The method may further include determining content patterns associated with each of the plurality of processes using a deep learning network. The method may include assigning a second tree ID to each of at least one process from the plurality of processes based on the identified content pattern. The method may further include generating a set of clusters for the plurality of processes based on the second tree ID assigned to each of the at least one process. The method may include executing each process within a cluster from the set of clusters based on execution of a single process within the cluster.

Abstract: Disclosed herein is a system and a method of guiding a plurality of agents 106 for complete coverage of the inspection area 102. The system and the method provide navigational instructions to navigate the plurality of agents 106 across the plurality of signalling unit 104 for traversing the inspection area 102. The plurality of signalling units 104 are communicatively coupled with the multi-agent visual navigation system for transmitting navigational instructions to the plurality of agents 106 based on pass-by information associated with the plurality of agents 106 obtained at the plurality of signalling units 104 and the pre-determined proximity associated with each pair of the plurality of signalling units. The navigational instructions are provided to the plurality of agents 106 at the plurality of signalling units 106 for subsequent navigation of the plurality of agents 106 across the plurality of signalling units 104 for complete coverage of the inspection area 102.