Abstract: Embodiments described herein provide for the dynamic adjustment of traffic associated with audiovisual conferences or other types of communication sessions in situations where a network connection of one or more conference participants exhibits issues that may affect audio and/or video quality. The adjustment may include the determination at a particular conference participant (e.g., a particular User Equipment (“UE”)) of degraded network conditions, the generation of condensed conference information at the UE, and the outputting of the condensed conference information via the network. The condensed conference information may be included in control signaling. The condensed conference information may be used to generate reconstructed conference information, which may be distributed to other conference participants.

Abstract: Embodiments described herein provide for the dynamic adjustment of traffic associated with audiovisual conferences or other types of communication sessions in situations where a network connection of one or more conference participants exhibits issues that may affect audio and/or video quality. The adjustment may include the determination at a particular conference participant (e.g., a particular User Equipment (“UE”)) of degraded network conditions, the generation of condensed conference information at the UE, and the outputting of the condensed conference information via the network. The condensed conference information may be included in control signaling. The condensed conference information may be used to generate reconstructed conference information, which may be distributed to other conference participants.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content providing, streaming and/or hosting systems supported by or configured with devices, servers and/or platforms. The disclosed systems and methods provide a novel conference framework that automatically determines and prioritizes speaker allocation within a conference in order to remedy and/or avoid conflicts between speakers so that a clear and decisive dialog can occur. The disclosed conference framework balances a determined weighting factor and queue management ranking of the conference to provide a prioritized speaker queue that enables all participants to speak without conflict or interruption. The disclosed systems and methods enable a prioritized, conflict-resolution based conferencing environment where orderly conferencing can occur while maintaining each participants rights to participate accordingly.

Abstract: Disclosed are systems and methods for a power management framework that can computationally minimize the power consumption of a device with Real-Time Kinematic (RTK) enabled. The disclosed framework can analyze the operating characteristics of a device (e.g., applications executing, movement, battery level, signal strength and current battery consumption of the device, and the like), which can provide an indication of the device's need for updated location information, and determine a frequency for updating RTK. Thus, the disclosed framework provides computerized mechanisms for the automatic optimization between the need for an RTK power update and the device's capabilities for actually performing the update.

Abstract: Provided are systems and methods for performing dynamic spectrum allocation and state shifting in order to provide high quality stateful services to user equipment (“UE”) that access the stateful services from different network locations. The dynamic spectrum allocation and state shifting may include tracking mobility of a UE accessing a stateful service using a first allocation of spectrum from a first Radio Access Network (“RAN”), predicting continued stateful service access via a second RAN, determining latency requirements of the stateful service, selecting a second allocation of spectrum at the second RAN with a frequency range that provides a first amount of latency, transferring the stateful service state to a Multi-Access Edge Computing (“MEC”) location that provides a second amount of latency for services accessed via the second RAN such that the first and second amounts of latency satisfy the performance requirements of the stateful service.

Abstract: A system may include a first device and a second device. The first device may be configured to select a second device for providing a first User Equipment device (UE) with media clips in accordance with Application Programming Interface (API) calls from a second UE. The second device may be configured to: receive a first API call from the second UE to generate and provide a media clip; generate the media clip; and send the generated media clip to the first UE.

Abstract: Systems and methods provide an adaptive avatar-based real-time holographic communication service. End devices implement a customized avatar for holographic communications. With the assistance of a network edge platform, a user's facial motions and gestures are extracted in real time and applied to the customized avatar in the form of an augmented-reality-based or virtual-reality-based holographic entity. When a connection to the network edge platform is interrupted or not available, a master holographic entity provides a graceful fallback to a less resource-intensive avatar presentation using, for example, a user's prerecorded motions as a basis for rendering avatar movement. The customized avatar may be automatically adjusted/altered depending on with whom a user is communicating (e.g., a friend vs. a business associate) or a purpose for the communication (e.g., a professional meeting vs. a social activity).

Abstract: A system may include a first device and a second device. The first device may be configured to select a second device for providing a first User Equipment device (UE) with media clips in accordance with Application Programming Interface (API) calls from a second UE. The second device may be configured to: receive a first API call from the second UE to generate and provide a media clip; generate the media clip; and send the generated media clip to the first UE.

Abstract: Embodiments described herein provide for the dynamic adjustment of traffic associated with audiovisual conferences or other types of communication sessions in situations where a network connection of one or more conference participants exhibits issues that may affect audio and/or video quality. The adjustment may include the determination at a particular conference participant (e.g., a particular User Equipment (“UE”)) of degraded network conditions, the generation of condensed conference information at the UE, and the outputting of the condensed conference information via the network. The condensed conference information may be included in control signaling. The condensed conference information may be used to generate reconstructed conference information, which may be distributed to other conference participants.

Abstract: Systems and methods provide an intelligent vehicle to everything (iV2X) service that ensures robust communication of teleoperations and other data. An edge slice proxy system is used to incorporate edge platforms into network slicing considerations. A network device may receive a request for a connection from an end device, such as a vehicle requiring the iV2X service, via wireless signals. The network device may detect that the request is a request for an iV2X service and assign the end device to a network slice that supports stateful and robust iV2X services. The network slice may include one of the virtual network functions executed on the edge platform.

Abstract: Systems and methods described herein perform computer vision (CV) model training in a distributed edge network. Regional Multi-access Edge Compute (MEC) clusters are provided with a local copy of a CV model and a local synthetic training data generator. A MEC cluster receives client data requiring computer vision and applies the local copy of the CV model to the client data. The MEC cluster detects an exception to the local copy of the CV model and generates local synthetic training data for the exception. The MEC cluster updates, based on the local synthetic training data, the local copy of the CV model to form an updated local CV model. The MEC cluster sends the local synthetic training data and the updated local CV model to a central network. The central network uses the local synthetic training data to update a master CV model and any other interconnected CV models.

Abstract: Provided are systems and methods that use artificial intelligence and/or machine learning to dynamically allocate services at different times and at different network edge locations within a Multi-Access Edge (“MEC”) enhanced network based on a multitude of factors that change the priorities of the services at the different times and at the different edge locations. For instance, a MEC controller, controlling the allocation of resources at a particular edge location, may modify the allocation of services at that particular edge location at different times based on time and/or location sensitive events that occur at different times and that relate to different services, changing usage patterns that are derived from prior service utilization, and/or categorization of the services as permanent, time insensitive, or other categories of services with permissions to execute at different times from different edge locations.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content providing, streaming and/or hosting systems supported by or configured with devices, servers and/or platforms. The disclosed systems and methods provide a novel conference framework that automatically determines and prioritizes speaker allocation within a conference in order to remedy and/or avoid conflicts between speakers so that a clear and decisive dialog can occur. The disclosed conference framework balances a determined weighting factor and queue management ranking of the conference to provide a prioritized speaker queue that enables all participants to speak without conflict or interruption. The disclosed systems and methods enable a prioritized, conflict-resolution based conferencing environment where orderly conferencing can occur while maintaining each participants rights to participate accordingly.

Abstract: Provided are systems and methods for performing dynamic spectrum allocation and state shifting in order to provide high quality stateful services to user equipment (“UE”) that access the stateful services from different network locations. The dynamic spectrum allocation and state shifting may include tracking mobility of a UE accessing a stateful service using a first allocation of spectrum from a first Radio Access Network (“RAN”), predicting continued stateful service access via a second RAN, determining latency requirements of the stateful service, selecting a second allocation of spectrum at the second RAN with a frequency range that provides a first amount of latency, transferring the stateful service state to a Multi-Access Edge Computing (“MEC”) location that provides a second amount of latency for services accessed via the second RAN such that the first and second amounts of latency satisfy the performance requirements of the stateful service.

Abstract: Systems and methods provide an intelligent vehicle to everything (iV2X) service that ensures robust communication of teleoperations and other data. An edge slice proxy system is used to incorporate edge platforms into network slicing considerations. A network device may receive a request for a connection from an end device, such as a vehicle requiring the iV2X service, via wireless signals. The network device may detect that the request is a request for an iV2X service and assign the end device to a network slice that supports stateful and robust iV2X services. The network slice may include one of the virtual network functions executed on the edge platform.

Abstract: Provided are systems and methods for performing dynamic spectrum allocation and state shifting in order to provide high quality stateful services to user equipment (“UE”) that access the stateful services from different network locations. The dynamic spectrum allocation and state shifting may include tracking mobility of a UE accessing a stateful service using a first allocation of spectrum from a first Radio Access Network (“RAN”), predicting continued stateful service access via a second RAN, determining latency requirements of the stateful service, selecting a second allocation of spectrum at the second RAN with a frequency range that provides a first amount of latency, transferring the stateful service state to a Multi-Access Edge Computing (“MEC”) location that provides a second amount of latency for services accessed via the second RAN such that the first and second amounts of latency satisfy the performance requirements of the stateful service.

Abstract: A method, a device, and a non-transitory storage medium are described in which an edge computing-based teleoperations service is provided. An edge network device may select an active and one or multiple backup remote-controlling devices in support of a teleoperations service session. The edge network device may include artificial intelligence to learn remote-controlling functions based on communications relayed between a remote-controlled device and the active remote-controlling device. The edge network device may use the learned remote-controlling functions during a failover procedure or other triggering network event.

Abstract: Systems and methods described herein perform computer vision (CV) model training in a distributed edge network. Regional Multi-access Edge Compute (MEC) clusters are provided with a local copy of a CV model and a local synthetic training data generator. A MEC cluster receives client data requiring computer vision and applies the local copy of the CV model to the client data. The MEC cluster detects an exception to the local copy of the CV model and generates local synthetic training data for the exception. The MEC cluster updates, based on the local synthetic training data, the local copy of the CV model to form an updated local CV model. The MEC cluster sends the local synthetic training data and the updated local CV model to a central network. The central network uses the local synthetic training data to update a master CV model and any other interconnected CV models.

Abstract: Systems and methods provide an adaptive avatar-based real-time holographic communication service. End devices implement a customized avatar for holographic communications. With the assistance of a network edge platform, a user's facial motions and gestures are extracted in real time and applied to the customized avatar in the form of an augmented-reality-based or virtual-reality-based holographic entity. When a connection to the network edge platform is interrupted or not available, a master holographic entity provides a graceful fallback to a less resource-intensive avatar presentation using, for example, a user's prerecorded motions as a basis for rendering avatar movement. The customized avatar may be automatically adjusted/altered depending on with whom a user is communicating (e.g., a friend vs. a business associate) or a purpose for the communication (e.g., a professional meeting vs. a social activity).

Abstract: A method, a system, and a non-transitory storage medium are described in which a health monitoring, analyzing, and response service is provided. The service may ingest monitoring information from end devices. The service may assign an adaptive weight value to each instance of monitoring information based on profile information pertaining to the end device. The profile information may include operational characteristics information and rating information. The service may aggregate the monitoring information based on the adaptive weight values to produce a weighted health or state value. The service may analyze and determine a health or condition of a person or object. The service may also generate response information reactive to the determined health or condition.