Abstract: An exemplary computer vision system implemented by a multi-access edge computing (“MEC”) server integrated within a provider network accesses an image captured by an image capture device coupled with the MEC server via the provider network. The image depicts a product that is to comply with a predefined product standard. The computer vision system identifies a criterion that is associated with the predefined product standard, and a region of the image that is associated with a product condition that is to be verified for compliance with the criterion. The computer vision system determines whether the product condition complies with the identified criterion for the identified region of the image, and, based on this determination, generates compliance verification data indicative of whether the product complies with the predefined product standard. The computer vision system also provides the compliance verification data to a monitoring system separate from the MEC server.

Abstract: An illustrative multi-access server system obtains trajectory data from a plurality of client devices engaged in a massive multiplayer application. The trajectory data is representative of asynchronous attempts, by users of the plurality of client devices, to direct respective virtual objects associated with each client device to a target at a real-world location and associated with a real-world event. Based on the trajectory data, the system determines a plurality of virtual trajectories for the asynchronous attempts to direct the respective virtual objects to the target, and, based on the plurality of virtual trajectories, renders a plurality of videos that each concurrently depict the asynchronous attempts to direct the respective virtual objects to the target. The system also streams different videos to different client devices, including customized videos for each client device. Corresponding methods and systems are also disclosed.

Abstract: An illustrative multi-access server system obtains trajectory data from a plurality of client devices engaged in a massive multiplayer application. The trajectory data is representative of asynchronous attempts, by users of the plurality of client devices, to direct respective virtual objects associated with each client device to a target at a real-world location and associated with a real-world event. Based on the trajectory data, the system determines a plurality of virtual trajectories for the asynchronous attempts to direct the respective virtual objects to the target, and, based on the plurality of virtual trajectories, renders a plurality of videos that each concurrently depict the asynchronous attempts to direct the respective virtual objects to the target. The system also streams different videos to different client devices, including customized videos for each client device. Corresponding methods and systems are also disclosed.

Abstract: An exemplary computer vision system implemented by a multi-access edge computing (“MEC”) server integrated within a provider network accesses an image captured by an image capture device coupled with the MEC server via the provider network. The image depicts a product that is to comply with a predefined product standard. The computer vision system identifies a criterion that is associated with the predefined product standard, and a region of the image that is associated with a product condition that is to be verified for compliance with the criterion. The computer vision system determines whether the product condition complies with the identified criterion for the identified region of the image, and, based on this determination, generates compliance verification data indicative of whether the product complies with the predefined product standard. The computer vision system also provides the compliance verification data to a monitoring system separate from the MEC server.

Abstract: A device may receive, from a user device, information that identifies a geolocation of the user device. The device may determine a set of sensor devices that are associated with the geolocation. The device may request, from the set of sensor devices, real-time information associated with the geolocation based on determining the set of sensor devices. The device may receive, from the set of sensor devices, the real-time information associated with the geolocation based on requesting the real-time information. The device may provide, to the user device, the real-time information associated with the geolocation to permit the user device to provide, for display, the real-time information as an augmented reality overlay.

Abstract: Artificial intelligence-based, intelligent agent (IA) services may include an IA server assisting users of a wireless network in various communication scenarios (e.g., calls, texts, chats, etc.). A user may specify rules for managing communications directed to a User Equipment (UE) of the user. Examples of such rules may include intercepting an incoming call to the user, managing the call based on whether the user is available, determining a reason for an incoming call and notifying the user about the reason, inviting the user to join the call, adding other users to the call, recording portions of the call, providing requested information, taking notes, scheduling meetings, and providing other assistant-type services, etc. The IA services may also include monitoring, interpreting, and responding to information that is sent to, or by, the user, during a communication, in addition to implementing Machine Learning procedures for self-improvement.

Abstract: Artificial intelligence-based, intelligent agent (IA) services may include an IA server assisting users of a wireless network in various communication scenarios (e.g., calls, texts, chats, etc.). A user may specify rules for managing communications directed to a User Equipment (UE) of the user. Examples of such rules may include intercepting an incoming call to the user, managing the call based on whether the user is available, determining a reason for an incoming call and notifying the user about the reason, inviting the user to join the call, adding other users to the call, recording portions of the call, providing requested information, taking notes, scheduling meetings, and providing other assistant-type services, etc. The IA services may also include monitoring, interpreting, and responding to information that is sent to, or by, the user, during a communication, in addition to implementing Machine Learning procedures for self-improvement.

Abstract: A device may receive, from a user device, information that identifies a geolocation of the user device. The device may determine a set of sensor devices that are associated with the geolocation. The device may request, from the set of sensor devices, real-time information associated with the geolocation based on determining the set of sensor devices. The device may receive, from the set of sensor devices, the real-time information associated with the geolocation based on requesting the real-time information. The device may provide, to the user device, the real-time information associated with the geolocation to permit the user device to provide, for display, the real-time information as an augmented reality overlay.