Abstract: Disclosed herein is a method and system for assessing one or more defects in a material. The method comprises extracting one or more assessment parameters from ultrasound waves propagated through a cross-section of the material. Further, the method identifies presence of one or more defects in the material by analyzing the one or more assessment parameters using a first machine learning model. Further, the method determines a position of each of one or more defects present in the material based on a graphical representation. Thereafter, the method determines a severity score and size of each of the one or more defects using a second machine learning model. Thus, an improved method and system for assessing one or more defects within a material by generating graphical representations of the one or more defects, thereby enhancing accuracy of defect detection is provided.

Abstract: The present disclosure discloses a method and a system for identifying fault resolution steps for an equipment. Method captures multi-modal diagnosis data associated with at least one primary part in the equipment. Method obtains multi-modal features of the at least one primary part from the multi-modal diagnosis data. Method detects a condition state of the at least one primary part using the multi-modal features and a trained object fault detection model. Method determines location of a fault on the at least one primary part using a trained fault location prediction model when the condition state is detected as a faulty state. Method identifies primary fault resolution steps for the at least one primary part based on historic data associated with the at least one primary part and the location of the fault. Method identifies secondary resolution steps for secondary parts based on the primary fault resolution steps before rendering.

Abstract: Embodiments of present disclosure relates to method and gesture prediction system for predicting gesture of subjects for controlling AV during navigation. The gesture prediction system obtains data from sensors and generates context information of environment of AV. The gesture prediction system generates parameters for sampling frames for determining gesture of subjects. The gesture prediction system estimates current pose, and subsequent poses by extrapolating current pose and subsequent poses using deep learning techniques. Further, the gesture prediction system infers current behaviour of subjects by classifying current pose and subsequent poses into one of predefined gesture categories. The gesture prediction system predicts gesture of subjects based on current behaviour, context information and location information of subjects for controlling AV during navigation. Thus, the present disclosure forecast gestures of subjects at a faster rate and controls the AV during the navigation.

Abstract: Present disclosure discloses method and system for automatically generating virtual driving environment using real-world data for autonomous vehicle (AV). Method extracts object feature data and road feature data from information related to an environment surrounding the AV. Thereafter, method generates a dynamic tree-based model for one or more objects in the environment with reference to the AV based on the object feature data and road network information based on the road feature data. Subsequently, method generates a pre-virtual driving environment by combining the dynamic tree-based model for the one or more objects and the road network information using a tree traversal technique and validates the pre-virtual driving environment for inaccuracies based on configurable validation rules.

Abstract: Embodiments of present disclosure relates to method and dimension determination system for determining dimensions of carton box. The dimension determination system receives plurality of datapoints associated with open carton box. The dimension determination system extracts depth datapoints from plurality of datapoints for identifying plurality of flaps. The dimension determination system determines height of open carton box using depth datapoints. The dimension determination system generates contour and estimates rectangle figure for contour of open carton box. Further, the dimension determination system determines width and length by extracting vertices of rectangle figure. Thereafter, the dimension determination system utilises width, length and height to obtain dimensions of open carton box. Thus, the present disclosure automatically determines dimensions of carton box.

Abstract: This disclosure relates to method and system for optimizing artificial neural network (ANN) classification model and training data thereof for appropriate model behavior. The method may include extracting entities and domain specific entities from the training data for each of classes of the ANN classification mode, determining model parameters of the ANN classification model based on the training data, determining missing data with respect to the training data or the model parameters based on the entities and the domain specific entities for each the classes, iteratively analysing a relative advantage of a modified ANN classification model with a modified training data with respect to the ANN classification model with the training data, and determining an optimized ANN classification model and an optimized training data for appropriate model behavior based on the iterative analysis. The modified data may be generated based on the missing data.

Abstract: Disclosed herein is a system and a method for generating automation test scripts dynamically for Human Machine Interface (HMI) testing. Test configurations are generated for a Device Under Test (DUT) (115) based on a screen transition dataset upon receiving a user request (105). Based on test configurations and the screen transition dataset, HMI components located in a test path are identified for transitions from source HMI screens to destination HMI screens. Based on the HMI components, reference images are determined for the destination HMI screens from a screen design dataset. The test configurations are executed on the DUT (115) via an external simulating device (113) and transition associated with the test path is validated based on matching the real time destination HMI screen image with the reference image. Based on a validation result, automation test report (117) is generated for the DUT (115).

Abstract: A system and method for onboarding and managing assets in a decentralized identity network is disclosed. The method may include receiving an authorization proof from a member of a team of an enterprise to access an asset in the decentralized identity network. The method may further include validating the member of the team through a set of validator nodes. The method may further include provisioning the asset on the decentralized identity network. The method may further include onboarding the provisioned asset on the decentralized identity network. The method may further include generating a set of derived credentials of the onboarded asset. The method may further include validating a user access request corresponding to at least one of owners of an application and user to access the asset. The method may further include dynamically validating an employee access request from an employee and the unique asset DID to access the asset.

Abstract: Disclosed herein is a method and system for determining quality of an input document during risk and compliance assessment. The method includes receiving input document for risk and compliance assessment, identifying a document type, and at least one sub-type of the input document using a Natural Language Processing (NLP) technique and a trained neural network model. Layout of content present in the input document is detected based on each of a plurality of segments extracted from content and structural parameters associated with respective segments. A document review model is identified from a plurality of document review models based on type and at least one sub-type of input document. Thereafter, the quality of the input document and a compliance score is determined by identifying one or more deviations of content of the input document from content of a predefined template for the input document.

Abstract: A method and a system for providing recommendations to users by securely accessing user sensitive data in a trusted execution environment (TEE) is disclosed. The method includes receive a request comprising a unique user identifier for accessing user sensitive data corresponding to at least one user. The method further includes validating a source of the request; providing an access to the user sensitive data upon identifying the source of the request to be the trusted application. The method for providing the access includes hosting a secure application session with the trusted application based on the unique secret key. The method further includes processing the user sensitive data for generating one or more user specific product and service recommendations corresponding to each of the at least one user; and rendering the one or more user specific product and service recommendations to each of the at least one user.

Abstract: Disclosed herein is method and a system for extracting information from an input document comprising multi-format information. In an embodiment, a Hypertext Markup Language (HTML) document corresponding to the input document is created by analyzing the input document comprising documents of multiple data formats. Further, the HTML document is realigned based on a number of columns in each page of the HTML document. Furthermore, a document Identifier (ID) associated with each of the documents is determined in realigned HTML document by classifying information in each of the document pages using a pretrained Machine Learning (ML) model. Subsequently, a hierarchy configuration file, corresponding to the realigned HTML document, is generated based on the document ID. Finally, information from the hierarchy configuration file associated with each of the document ID is extracted by orchestrating one or more data extractors for extracting data attributes from the hierarchy configuration file.

Abstract: A system and method for providing assistance to vehicle occupants is disclosed. The method includes the steps of receiving a set of static information and a set of dynamic information associated with each of a vehicle, a set of Human Machine Interfaces (HMIs), and an occupant within the vehicle; processing the set of static information and the set of dynamic information through at least one of a first Artificial Neural Network (ANN) Model and a rule engine; determining an accessibility score for the occupant in response to an event based on an output of the processing; generating at least one of at least one accessibility compliant HMI content for at least one of the set of HMIs and vehicle control content for the vehicle based on the accessibility score; and executing at least one of the at least one accessibility compliant HMI content and the vehicle control content.

Abstract: The present disclosure is related to Virtual Desktop Infrastructure (VDI) that discloses a method and system for performing dynamic patch management in VDI platform. A patch managing system retrieves operational data and vulnerability remediation data related to IT services and infrastructures of the VDI platform from first and second data sources. Thereafter, the patch managing system detects gap in patching level based on operational data, vulnerability remediation data and corresponding industrial standard, and rolls out patches based on detected gap in patching level. Further, a patch prediction score that facilitates in identifying a probability of rolling back the patches rolled out for patching IT services and infrastructures of VDI platform is determined based on prediction parameters. A plan is generated based on the patch prediction score and executed to optimally patch the patches to IT services and infrastructures of the VDI platform, based on patching rules.

Abstract: A method and a system for maneuvering vehicles using adjustable ultrasound sensors is disclosed. The method includes determining at least one first position of an object relative to a vehicle using at least one high range sensor and determining for each of at least one first position of the object non-conformance with one or more object position criteria. The method further includes determining at least one second position of object relative to vehicle, when at least one first position of the object is in non-conformance with one or more object position criteria. The method further includes assigning at least one ultrasound sensor to dynamically focus on the object and maneuvering the vehicle on a trajectory plan based on the at least object attribute. Each of plurality of ultrasound sensors is deployed on rotatable mount and assigned at least one ultrasound sensor is dynamically focused by rotating on associated rotatable mount.

Abstract: Embodiments of the present disclosure relate to a method and an apparatus for alerting threats to users. The apparatus may capture a plurality of signals including at least one of Electro-Magnetic (E-M) signals and sound signals. The E-M signal and sound signals are used to detect objects around the user. A threat to the user is predicted based on the objects around the user and one or more alerts are generated such that the user avoids the threat. The prediction of the threat enables the user to take an action even before the threat has occurred. Also, the alerts are generated based on the prediction such that the user can avoid the threat well in advance of the occurrence of the threat.

Abstract: The present disclosure relates to wastewater management that provides a method and a system for monitoring a sewer manhole from a remote location. The sewer monitoring system configured in a sewer manhole receives measured values from a level sensor and determines an accuracy error in the measured values for different conditions. The sewer monitoring system resolves the accuracy error in the measured values to obtain accurate measured values by either measuring a level of wastewater in the sewer manhole by setting a first range limit for the measured values dynamically based on an actual depth of the sewer manhole, or iteratively measuring the level of wastewater in the sewer manhole by setting unique a second range limit for the measured values dynamically. A risk associated with the sewer manhole based on the accurate measured values of the level sensor is determined, for monitoring the sewer manhole from a remote location.

Abstract: A method and system for effective service fulfillment in a communication network is disclosed. The method includes determining utilization of each of a plurality of resources for each of a plurality of network slice instances. The method further includes determining a service allocation schedule and a service resource utilization across one or more service classes and one or more resource classes for each of the plurality of resources; determining at least one of a set of possible actions required to be performed in at least one of the plurality of resources, a plurality of services, and the plurality of network slice instances based on a consolidation plan; assessing an impact of each of the set of possible actions based on a plurality of factors; and triggering a relevant network function(s) to perform at least one of the set of determined possible actions based on the assessed impact.

Abstract: Disclosed herein is a method and system for optimizing video content acquisition and delivery during events. In an embodiment, an optimal video content for transmission is selected by analyzing plurality of videos of a live event captured by one or more video capturing units. Further, optimal video content is transmitted to a Media Processing Center (MPC) using a predefined unicast network. Furthermore, the optimal video content is processed into one or more predefined streaming formats corresponding to one or more streaming channels of a hybrid transmission service. Subsequently, an optimal delivery channel for each of a plurality of users is selected by analyzing a plurality of user parameters associated with the plurality of users and a plurality of sociological parameters associated with the live event. Finally, the optimal video content is transmitted to the plurality of users through the optimal delivery channel selected for each of the plurality of users.

Abstract: A method and activity recognition system for recognising activities in surrounding environment for controlling navigation of an autonomous vehicle is disclosed. The activity recognition system receives first data feed from neuromorphic event-based camera and second data feed from frame-based RGB video camera. The first data feed comprises high-speed temporal information encoding motion associated with change in surrounding environment at each spatial location, and second data feed comprises spatio-temporal data providing scene-level contextual information associated with surrounding environment. An adaptive sampling of second data feed is performed with respect to foreground activity rate based on amount of foreground motion encoded in first data feed. Further, the activity recognition system recognizes activities associated with at least one object in surrounding environment by identifying correlation between both data feed by using two-stream neural network model.

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.