Abstract: Aspects of the subject disclosure may include, for example, a device, including: 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: detecting a target behavior of a person and a first location of the person using a computer vision system in a monitored location; confirming the first location detected by the computer vision system matches a mobile location of a mobile device possessed by the person, wherein the mobile device is connected to a network providing communication services at the monitored location, and wherein the mobile location is determined by the network; and providing a reward to the mobile device responsive to the target behavior detected and the first location matching the mobile location. 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 method, where the method includes discovering an event where at least one device is offline and instantiating an emergency mode causing the at least one device to permit data or message aggregation. The method further includes defining a community of devices including an identity of the at least one device and establishing communication between the at least one device and a mobile aggregation device. The method further includes when the mobile aggregation device is in communication with the at least one device, aggregating a payload of a message or data from the at least one device and the community having an artificial intelligence instantiated as a virtual network function or network device, the community communicating with the mobile aggregation device to receive data from the at least one device, and the artificial intelligence being configured to assess the event based on the data obtained by the mobile aggregation device.

Abstract: In one example, a method includes detecting a new message sent by a first user to a second user, wherein at least the second user is engaged in an extended reality environment, determining whether the new message should be delivered to the second user while the second user is engaged in the extended reality environment, and sending the new message to the second user when it is determined that the new message should be delivered to the second user while the second user is engaged in the extended reality environment, wherein the sending is performed according to a routing strategy that is based on at least one of: a context of the second user or a preference of the second user.

Abstract: In one example, a method includes instructing a mobile device of a user to establish a connection with an application server via a first network slice, where the first network slice is configured based on an initial resource need of a network connected application executing on the mobile device and an initial set of network conditions, sending, to the mobile device, a prediction of at least one network condition for the first network slice at a time in the future, receiving, from the mobile device, an indication of an updated resource need of the network connected application, and providing, to the mobile device, instructions for establishing a connection to the application server over a second network slice, where the second network slice is configured based on the updated resource need and a current set of network conditions.

Abstract: Aspects of the subject disclosure may include, for example, detecting communications between a source device and a destination device, wherein the communications relate to a particular context and are facilitated over a first network associated with the destination device, determining a state or trust level for the particular context based on reference data, detecting a change in behavior of the source device, updating the state or trust level based on the detecting the change in behavior of the source device, resulting in an updated state or trust level, identifying a loss of trust condition based on the updated state or trust level, restricting communications between the source device and the destination device, and performing a trust rebuild process in an attempt to address the loss of trust condition and to enable the source device to resume communications with the destination device. Other embodiments are disclosed.

Abstract: In one example, a method performed by a processing system including at least one processor includes acquiring information about a first physical environment of a first user of an extended reality environment, acquiring information about a second physical environment of a second user of the extended reality environment, rendering the extended reality environment in a manner that is compatible with both the first physical environment and the second physical environment, based on the information about the first physical environment and the information about the second physical environment, and applying a first adjustment to a presentation of the XR environment that is displayed to the first user, based on the information about the first physical environment, without making the first adjustment to a presentation of the XR environment that is displayed to the second user.

Abstract: Aspects of the subject disclosure may include, for example, a method, including: receiving, by a processing system including a processor, a request to play content; querying, by the processing system, for matches between the content and a user library; receiving, by the processing system, recommendations for alternate content of the user library and associated cue points in the content; and presenting, by the processing system, portions of the content and presenting other portions of the content replaced with the alternate content at the associated cue points. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, machine learning models that learn reusable contributor embedding models representing contribution impacts. The contribution impacts represent the impact of contributions to media works made by contributors such as writers, directors, producers, actors, or combinations thereof. Machine learning models may then be used to perform contribution predictions from the reusable contributor embedding models. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, a device with 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 ingesting facilities infrastructure data for more than one facility; training a machine-learning (ML) model from the facilities infrastructure data, wherein the ML model infers features absent in the facilities infrastructure data and yields a score of a facility described by the facilities infrastructure data; receiving a query for a region from a user; identifying one or more facilities provided in the region; generating a map of the one or more facilities using the ML model; and providing a visualization interface to the user including the map and the score of the one or more facilities responsive to the query. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, a device, including 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 constructing a composite machine-learning (ML) model for facilities infrastructure from facilities infrastructure data; training the composite ML model with historical availability data, historical performance data, and historical error rates, wherein the composite ML model yields quality of the facilities infrastructure; receiving a query of a facility in an area from a user; predicting a quality of the facility based on recent facilities data using the composite ML model; and providing the quality of the facility responsive to the query. Other embodiments are disclosed.

Abstract: A method, system, computer readable storage medium, or apparatus provides for obtaining first information of a user (e.g., a user profile), wherein the user may be associated with a mobile device; based on the first information of the user, determining whether to communicate with the user via local area communication or wide area communication (e.g., a communication context) during a first period; determining to communicate via wide area communication during the first period; based on the determining to communicate via the wide area communication during the first period, sending an alert to invite the user associated with the mobile device to communicate with a remote domain (e.g., a remote physical location, such as a home, business, park, etc.); and based on acceptance of the invite, assigning a token for the user associated with the mobile device to further communicate with the remote domain.

Abstract: Aspects of the subject disclosure may include, for example, a device that has a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations, including downsampling a full point cloud to obtain a downsampled point cloud, wherein the downsampling reduces a data size of the full point cloud; and using a machine-learning model to assign labels for segmentation and object identification to points in the downsampled point cloud, wherein the machine-learning model is trained on the full point cloud. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, receiving information about an augmented reality (AR) environment which includes a plurality of objects and a user participating in the AR environment, the user viewing the AR environment through a user equipment, receiving context information for the AR environment, identifying a diminished reality (DR) object of the plurality of objects, wherein the identifying is responsive to the context information, modifying the AR environment to render the DR object invisible to the user viewing the AR environment through user equipment, monitoring movement of one or more objects of the AR environment including the DR object, and modifying visibility of the DR object to the user viewing the AR environment through user equipment as a notification of a possible collision between the user and the DR object, wherein the modifying is responsive to detecting a risk of collision. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, obtaining an image of an object over a communication network from a first communication device associated with a user, obtaining first information associated with the object, and receiving user-generated input over the communication network from the first communication device. The user-generated input indicates to generate a group of complementary objects associated with the object. Further embodiments can include, in response to receiving the user-generated input, providing instructions to generate the group of complementary objects over the communication network to a second communication device associated with the user based on the image of the object and the first information. The second communication device generates the group of complementary objects. Other embodiments are disclosed.

Abstract: Management and configuration of internet of things network connected devices is facilitated herein. A probe device comprises a memory that stores executable instructions that, when executed by a processor, facilitate performance of operations that comprise determining a first identity and a first operational parameter of a first device and a second identity and a second operational parameter of a second device. The first device and the second device can be associated with a defined communication network. The probe device can be provisioned within the defined communication network and can operate as a security update probe node for the first device and the second device. The operations can also comprise facilitating a first security update at the first device and a second security update at the second device based on a determination that the first device and the second device have delegated responsibility for security synchronization to the probe device.

Abstract: In a dataset exchange environment in which datasets are available for exchange or transformation, a dataset validation platform may be configured to update a cryptographically signed record based on each dataset that is available via the data exchange environment. The dataset validation platform may be further configured to control access to the datasets based on whether a request to access a particular dataset is compliant with an availability requirement of the particular dataset. The dataset validation platform may be further configured to update the cryptographically signed record based on requests to access the datasets, transformations that are based on the datasets, or modifications to the availability requirement of the datasets, such as a modification to a privacy limitation or other availability requirement indicating a criteria for usage of the requested dataset.

Abstract: A device includes 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 loading a user profile for a user consuming undigitized, static media content; identifying an area of interest in the undigitized, static media content; analyzing the area of interest; responsive to the user profile, creating immersive content to enhance the area of interest; and providing the immersive content for presentation to the user.

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: The disclosed technology is directed towards inserting user-personalized or other user-related supplementary media content into primary media content being presented to the user. The personalized media content can be inserted into available insertion slots associated with the primary media content. The inserted content is based on the context of the primary media, e.g., a location or theme of a movie scene. For example, upon obtaining primary media content that is video, supplementary media content related to a group of frames of the primary media content can be determined. Supplementary media content is combined with the primary media content at a presentation position associated with the group of frames to output modified media content. For a video, for example, the supplementary content can be inserted between scenes, overlaid onto a scene, or presented proximate a scene.