Abstract: A method performed by a processing system including at least one processor includes collecting a set of data from a plurality of sensors that is monitoring a system, wherein the plurality of sensors includes sensors of a plurality of different modalities, detecting an instance of out-of-distribution data in the set of data by providing the set of data as an input to a machine learning model that generates as an output an indicator that the instance of out-of-distribution data is out-of-distribution with respect to the set of data, identifying a root cause for the instance of out-of-distribution data, and initiating an action to remediate the root cause of the instance of out-of-distribution data.

Abstract: Aspects of the subject disclosure may include, for example, a device, having a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations of: collecting data traffic of one or more network devices of a user, wherein the data traffic is associated with multiple channels of interactions; building a channel-specific user signature and a cross-channel user signature of normal usage for the user based on the data traffic collected; detecting a change in a characteristic of the data traffic, wherein the change indicates fraudulent activity based on the channel-specific user signature and the cross-channel user signature; and issuing an alert of the fraudulent activity based on the change. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, capturing a first depiction of an exhibit environment, wherein the first depiction of the exhibit environment comprises an image of at least one artifact and an image of at least one interface element, and wherein the at least one interface element is located in the exhibit environment at a first location relative to the at least one artifact; obtaining a first user profile of a first user, wherein the first user profile comprises at least one first preference of the first user, and wherein the first user is located in a first remote environment; and facilitating a presenting of a first modified version of the first depiction of the exhibit environment in the first remote environment, wherein the first modified version moves the image of the at least one interface element to a second location relative to the at least one artifact, wherein the second location is different than the first location, and wherein the second location is selected based upon

Abstract: A method may include receiving current environment condition information associated with an extended reality device; receiving historical environment condition information associated with the extended reality device; based on current environment condition information and the historical environment condition information, determining one or more adjustments to meet a performance threshold for rendering objects on the an extended reality device or using the an extended reality device; and sending instructions to implement the one or more adjustments to meet the performance threshold for rendering objects on the extended reality device or using the extended reality device.

Abstract: Aspects of the subject disclosure may include, for example, capturing a first depiction of an exhibit environment, wherein the first depiction of the exhibit environment comprises an image of at least one artifact and an image of at least one interface element, and wherein the at least one interface element is located in the exhibit environment at a first location relative to the at least one artifact; obtaining a first user profile of a first user, wherein the first user profile comprises at least one first preference of the first user, and wherein the first user is located in a first remote environment; and facilitating a presenting of a first modified version of the first depiction of the exhibit environment in the first remote environment, wherein the first modified version moves the image of the at least one interface element to a second location relative to the at least one artifact, wherein the second location is different than the first location, and wherein the second location is selected based upon

Abstract: A method may include receiving current environment condition information associated with an extended reality device; receiving historical environment condition information associated with the extended reality device; based on current environment condition information and the historical environment condition information, determining one or more adjustments to meet a performance threshold for rendering objects on the an extended reality device or using the an extended reality device; and sending instructions to implement the one or more adjustments to meet the performance threshold for rendering objects on the extended reality device or using the extended reality device.

Abstract: Devices, non-transitory computer-readable media, and methods for job negotiation for workflow automation tasks are disclosed. An example method includes receiving a delegation of a task from a controller, wherein the task is one of a plurality of tasks that collectively forms a workflow, assessing an ability of the processing system to perform the task as defined in the delegation, suggesting a modification to the task as defined in the delegation, determining whether the modification was accepted by the controller, and declining the task when the modification is not accepted by the controller, and performing the task including the modification when the modification is accepted by the controller.

Abstract: Aspects of the subject disclosure may include, for example, capturing a first depiction of an exhibit environment, wherein the first depiction of the exhibit environment comprises an image of at least one artifact and an image of at least one interface element, and wherein the at least one interface element is located in the exhibit environment at a first location relative to the at least one artifact; obtaining a first user profile of a first user, wherein the first user profile comprises at least one first preference of the first user, and wherein the first user is located in a first remote environment; and facilitating a presenting of a first modified version of the first depiction of the exhibit environment in the first remote environment, wherein the first modified version moves the image of the at least one interface element to a second location relative to the at least one artifact, wherein the second location is different than the first location, and wherein the second location is selected based upon

Abstract: For example, a method includes collecting orientation data from a mobile device as a user of the mobile device moves within an indoor space, generating orientation estimates for the mobile device from the orientation data, generating distance estimates representing distances of the mobile device to a wireless access point in the indoor space, storing the orientation estimates and the distance estimates together as a series of data blocks, constructing a plurality of trajectory segments from the orientation estimates, identifying identifiers for a last number of trajectory segments, using data blocks corresponding to the last number of trajectory segments, and identifying a predicted place within the indoor space to which the user is expected to go by using the identifiers to traverse a prediction tree, where branches of the prediction tree that are associated with the identifiers define a path that ends at a leaf node corresponding to the predicted place.

Abstract: Creating scent models and using scent models in cross-reality environments can include capturing experience data identifying a scent detected and a context in which the scent was detected. The experience data can be provided to a scent modeling service to generate a scent model that can represent perceived scents and perceived scent intensities for a user. The scent model can be used to generate cross-reality session data to be used in a cross-reality session presented by a cross-reality device. The cross-reality device can include a scent generator and can generate the cross-reality session using data obtained from the user device. The cross-reality device can generate a further scent during the cross-reality session based on the scent model.

Abstract: Tasks associated with users can be managed for efficient workflow management. A task management component (TMC) can analyze, including performing artificial intelligence-based analysis on, task-related information relating to associated with a user(s), assessment information relating to assessing performance or expertise associated with a task, biometric information relating to health, diet, and activity associated with the user(s), and/or user(s) feedback information. Based on the analysis, TMC can adaptively adjust respective attributes associated with respective tasks, resulting in respective adjusted attributes associated with the respective tasks. Based on the respective adjusted attributes, TMC can determine task information and can present the task information to a device(s) associated with the user(s) to facilitate performance of the tasks.

Abstract: Extended reality augmentation of situational navigation (e.g., using a computerized tool) is enabled. For example, a system can comprise: a processor and a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations, comprising: based on a route of a vehicle, determining a navigational instruction to be displayed via an augmented reality interface of the vehicle, and displaying the navigational instruction via the augmented reality interface, wherein displaying the navigational instruction comprises displaying a virtual leading vehicle to be followed by the vehicle.

Abstract: Aspects of the subject disclosure may include, for example, obtaining contextual information associated with a user, wherein the user is engaged in an immersive environment using a target user device, and wherein the contextual information comprises user profile data, data regarding a location of the user, data regarding one or more inputs provided by the user, or a combination thereof, receiving data regarding a metaverse object in the immersive environment, determining a relevance of the metaverse object to the user based on the contextual information and the data regarding the metaverse object, responsive to the determining the relevance of the metaverse object to the user, generating a personalized recommendation or review of the metaverse object for the user, and causing the personalized recommendation or review to be provided to the user in the immersive environment for user consumption. Other embodiments are disclosed.

Abstract: An artificial intelligence (AI) automation to improve network quality based on predicted locations is provided. A method can include training, by a first device comprising a processor and according to model configuration parameters received from a second device that is not the first device, a local machine learning model with training data derived from first location data collected by the first device; transmitting, by the first device to the second device, anonymized model features associated with the local machine learning model; in response to the transmitting of the anonymized model features, receiving, by the first device from the second device, an aggregated machine learning model; and estimating, by the first device, a future position of the first device by applying the aggregated machine learning model to second location data collected by the first device.

Abstract: In one example, a method performed by a processing system including at least one processor includes downloading at least one digital resource relating to a user-defined location, acquiring data about the user-defined location from a sensor located in the user-defined location, while the user is present in the user-defined location, detecting a user need based on the data from the sensor, augmenting the at least one digital resource with the data from the sensor to produce content that is responsive to the user need, and presenting the content that is responsive to the user need.

Abstract: Aspects of the subject disclosure may include, for example, obtaining a list of a plurality of communication channels, each communication channel being associated with at least one respective feature of a plurality of features; correlating each communication channel in the list with at least one respective user response of a plurality of user responses; receiving an identification of a new communication channel that does not exist in the list, the new communication channel being associated with at least one feature of the plurality of features; determining, based upon the at least one feature that is associated with the new communication channel, with which one or more of the plurality of communication channels in the list the new communication channel is similar, resulting in a determination; and assigning, based upon the determination, at least one of the plurality of user responses to the new communication channel. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, analyzing, by a processing system, a customer message to determine a customer care issue and a customer sentiment, and generating a response to engage with the customer based on the customer sentiment; the response includes the information to address the customer care issue. The system also delivers the response to the equipment of the customer; monitors for a customer reaction to the delivered response to determine a change in the customer sentiment; and generates an additional response to further engage with the customer based on the change in the customer sentiment. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, a method in which a processing system analyzes data including a user profile and historical data relating to previous interactions between an automated agent and equipment of the user. The method also includes determining a desirable outcome of an interaction between the automated agent and the user equipment; constructing a model for generating an expected outcome of a step of the interaction; using the model to perform a simulation of a next step of the interaction by generating an expected outcome for each of a plurality of possible actions, resulting in a plurality of expected outcomes; and selecting a next action for the next step of the interaction. If the desirable outcome is not obtained, the system can refine the plurality of possible actions to perform a simulation of a subsequent step of the interaction. Other embodiments are disclosed.

Abstract: A volumetric content enhancement system (“the system”) can annotate at least a portion of a plurality of voxels from a volumetric video with contextual data. The system can determine at least one actionable position within the volumetric video. The system can create an annotated volumetric video that includes the volumetric video, an annotation with the contextual data, and the at least one actionable position. The system can provide the annotated volumetric video to a volumetric content playback system. The system can obtain viewer feedback associated with the viewer and can determine an emotional state of the viewer based, at least in part, upon the viewer feedback. The system can receive viewer position information that identifies a specific actionable position of the viewer. The system can generate manipulation instructions to instruct the volumetric content playback system to manipulate the annotated volumetric content to achieve a desired emotional state of the viewer.

Abstract: In one example, a method performed by a processing system including at least one processor includes acquiring a first item of media content from a user, where the first item of media content depicts a subject, acquiring a second item of media content, where the second item of media content depicts the subject, compositing the first item of media content and the second item of media content to create, within a metaverse of immersive content, an item of immersive content that depicts the subject, presenting the item of immersive content on a device operated by the user, and adapting the presenting of the item of immersive content in response to a choice made by the user.