At&t Intellectual Property I, L.p.

At&t Mobility Ii LLC

At&t Intellectual Property Ii, L.p.

Hyundai Motor Company

Kia Corporation

At&t Global Network Services Belgium Luxembourg Sprl

James H Pratt

Eric Martin Zavesky

Marc Andrew Sullivan

Steven M Belz

Nigel Bradley

Ari Craine

Timothy Innes

Robert A Koch

Behzad Shahraray

Robert Raymond Miller, Ii

Horst Juergen Schroeter

Troy C Meuninck

Kevin Ansia Li

Yupeng Jia

Gregory Wesley Edwards

Michael Lattanzi

Constance Missimer

Nikhil Shreerang Marathe

Keith Aubrey Crowe

Randolph Wohlert

Jason Decuir

Barrett Morris Kreiner

Walter Cooper Chastain

Robert Torrence Moton, Jr

Adrianne Binh Luu

Paul Van Vleck

Garrett L Stettler

Sarah Everett

Greg W Edwards

Donald Perciful

Miranda Huet

James Jackson

John Oetting

Terrel Lecesne

Michael Gonzales

Bhumit Patel

Robert Gratz

David Crawford Gibbon

Milap V Majmundar

Robert Dailey

Martin Patrick McEnroe

William Knotts

Aaron Bangor

Mark Stockert

Guido Corona

Curtis Stephenson

Linda Baughman

Pamela Stuckman

Elizabeth Pratt

Sanjiv Singh

Parimal Pandya

Larry B Pearson

Kurt M Joseph

Eric Petajan

Abhay Dabholkar

Wiley C Wilkins

Vladimir Sevastyanov

Nikhlesh Agrawal

Vivek Rajasekharan

Seyed Amir Mir Bagheri

Jessica R Owensby

Jing Sasha Guo

Samir Bhatt

Taylor Gift

Barkha Pathik Patel

Nicholas Cassioppi

Zhi Cui

Jeffrey L Brandt

Jeffrey Paul Johnson

Prince Paulraj

Ana Armenta

Edmond J Abrahamian

Subhabrata Majumdar

Abhigyan Sharma Abhigyan

Roger Drew Wickes

Christophe Closset

Ni An

Prateek Baranwal

Kelly Dowd

Antoine Diffloth

Paul Carver

Andrew Kell

Michael L Hunter

Mun May Tee

Gregory Edwards

Gervais-Martial Ngueko

David Plunkett, Jr

Kostikey Mustakas

Terrel Michael LeCesne

Jason Allen DeCuir

Catherine Lefèvre

Rakhi Gupta

Emily Williams

Sherry Simon

Robert F Williams

Jun Yan

Morgan Friske

Brian Bachman

The described technology is generally directed towards emotion detection and translation for electronic communications. An emotional state of a first communication participant can be detected, e.g., through face recognition, biometric information, and/or communication content analysis. The emotional state can be encoded in metadata that can accompany the communication content. The metadata can be translated into one or more embellishments that represent the emotional state, and the embellishments can be inserted into the communication content. The embellished communication content can then be delivered to a second communication participant.

Emotion detection and translation for electronic communications

Methods, computer-readable media, and systems for enhancing food service operations using Internet of Things-enabled dinnerware are disclosed. One method performed by a processing system including at least one processor includes obtaining data about a food item that is being prepared for a consumer, forwarding the data about the food item to an internet of things-enabled item of dinnerware, receiving, from the internet of things-enabled item of dinnerware, data about consumption of the food item by the consumer, and providing feedback to an endpoint device of a person who prepared the food item for presentation to the person who prepared the food item, in response to the data about the consumption of the food item by the consumer.

Internet of things-enabled dinnerware to enhance food service operations

Aspects of the subject disclosure may include, for example, identifying an uncrewed aerial vehicle (UAV) for route planning and power management, obtaining information regarding the UAV, a present location of the UAV, a destination location for the UAV, or a combination thereof, determining, based on the information, a need for the UAV to recharge a power source of the UAV as part of a journey of the UAV from the present location of the UAV to the destination location for the UAV, responsive to the determining the need, identifying a recharging station associated with a network for recharging the power source of the UAV, and calculating a flight path for the UAV in accordance with the identifying the recharging station. Other embodiments are disclosed.

Method and system for routing/orchestration/management of aerial vehicles or data on a network

The technology described herein is generally directed towards determining that a user is passively attending a meeting via a connected device, collecting data created during the meeting, and outputting information based on the collected data for the user to monitor the meeting. Join criteria can be associated with passive meeting attendee, and if the collected meeting data satisfies the join criteria, the attendee can transition to an active attendee. Keyword data can be used to represent information relevant to a meeting attendee. Based on collected and monitored meeting data presented during the meeting and the keyword data, the meeting can be determined to have reached a relevance/pertinence level by which action is taken to change the user from a passive attendee to an active attendee. This can include a transition period that allows a user to catch up on previous meeting information before becoming an active attendee.

Virtual meeting management

Concepts and technologies disclosed herein are directed to automated optimization of events by engagement and format. According to one aspect disclosed herein, an event management system can create an event for a specified topic based upon input provided, at least in part, by an event creator. The input can identify initial event content, a plurality of event attendees, a location for the event, and an event presenter. The event management system can receive a selection of a desired audience for the event. The event management system can accept the initial event content to be presented during the event and can determine a time for the event. The event management system can perform engagement sampling during the event. The event management system can utilize the selection, the time, and the engagement sampling to optimize the event. The event management system can determine a follow-up action to be performed after the event.

Automated optimization of events by engagement and format

The disclosed technology is directed towards detection of personal threats to a user based on information known to a user's device and other information. A device with a personal threat application program and server communicate information, including data describing the user's current physical situation, e.g., including current location. The server and/or application program obtain data describing environmental conditions around the user's location, e.g., corresponding to a defined personal zone. The personal zone size automatically can vary based on current factors. Based on the situation and environmental data reaching a threshold threat level, a potential threat to the user can be predicted and the prediction, used to take some action, such as to send an alert to the user and/or otherwise output a warning signal. Historical data such as statistics related to the user's current location can be accessed to assist with the prediction.

Predictive personal threat levels via user device

Facilitating selection of the most significant set of categorical features in machine learning is provided herein. Operations of a system include determining a list of unique values of a categorical variable. The operations also include calculating respective mean values, of a target variable, for unique values of the list of unique values of the categorical variable. Further, the operations include sorting the list of unique values by the respective mean values, resulting in a sorted list. The operations also include calculating respective derivatives of the respective mean values in the sorted list considering the respective mean values as a function and a number of the respective mean values in the sorted list as an independent variable. Additionally, the operations include determining a minimum derivative value over the sorted list and outputting the minimum derivative value as a resulting variable significance value.

Facilitating selection of categorical features in machine learning

A processing system including at least one processor may obtain a first input data set associated with a telephone number from a first service provider that implements a multi-factor authentication process for permitting an access to a service of the first service provider and may apply at least the first input data set to a machine learning model implemented by the processing system to obtain a risk score associated with the telephone number for a subscriber identity module swap of a subscriber identity module, where the machine learning model is trained to generate the risk score associated with the telephone number in accordance with at least the first input data set. The processing system may then perform at least one remedial action associated with the telephone number and the subscriber identity module, in response to the risk score.

Machine learning model feature sharing for subscriber identity module hijack prevention

The technologies described herein are generally directed to using a transmission profile to provide availability and security options for communicating data in a fifth generation (5G) network or other next generation networks. For example, a method described herein can include identifying a transmission profile for a data item for transmission to a destination node, with the transmission profile including transmission parameters having an availability importance parameter applicable to an availability of the data item by the destination node and a security importance parameter applicable to a security applicable to transmission. The method can further include segmenting the data item into data segments comprising a first data segment and a second data segment. Further, the method can include, based on the transmission profile, selecting a first network route and a second network route for a transmission of the data segments.

Using a transmission profile to provide availability and security options for communicating data

Facilitating avatar modifications for learning and other videotelephony sessions in advanced networks is provided herein. Operations of a system include evaluating a recorded interaction associated with a first entity during consumption of a first portion of a video conference determined to include the first entity. The operations also can include transforming an actual representation of the first entity in the recorded interaction to an avatar representation, resulting in an edited interaction of the first entity. Further, the operations can include outputting the edited interaction of the first entity for consumption of a second portion of the video conference by rendering the edited interaction for a second entity.

Facilitating avatar modifications for learning and other videotelephony sessions in advanced networks

The disclosed technology is directed towards monitoring media content, including without presenting the monitored media content via a media presentation device, or while presenting in parallel. In general, supplementary data describing the monitored media content is obtained, e.g., generated by a media server based on the content being monitored. The supplementary data is presented via a user interface for a user to monitor, e.g., as displayed text, documents, audio in or other ways such as a combination of text and images. The user interface can be a primary presentation device the user is using, and/or another user device. The supplementary data can describe scenes of video, and/or transcriptions of audio, for example. The supplementary data can be interacted with, such as to switch to present the monitored media content or a selected portion thereof. Multiple media content presentations can be monitored, with supplementary data available for each.

Media content monitoring

A processing system may detect at least one endpoint device of at least one user at a premises having a first plurality of functions, may obtain at least one user profile that indicates a second plurality of functions associated with the at least one user, each function having a maximum available function level, and may obtain a visitor profile associated with the premises defining permitted function levels for one or more functions from among the first plurality that the at least one user is permitted to access. The processing system may then select a set of shared functions and function levels for the set based on the at least one user profile and the visitor profile, the set of shared functions including a first function of the first plurality and a second function of the second plurality, and may activate the set at the premises with the function levels.

Enrollment and sharing of devices and network-based services via on-premises network access point

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.

Method and system for adaptive trust recovery in mixed environment communications

An audio generation system is provided to enable coordinated control of multiple IoT devices for audio collection and distribution of one or more audio sources according to location and user preference. The audio generation system enables a location sensitive acoustic control of sound, both as a shaped envelope for a particular source, and as an individualized experience. The audio generation system also facilitates an interactive visual system for visualization and manipulation of the audio environment including via the use of augmented reality and/or virtual reality to depict soundscapes. The audio generation system can also facilitate a system for improving and achieving an audio environment (sound influence zone) and an intuitive way to understand where sounds will be heard.

Service for targeted crowd sourced audio for virtual interaction

Aspects of the subject disclosure may include, for example, a device comprising: a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations, the operations comprising: receiving from user equipment an indication that a user has been authenticated by the user equipment via a biometric process; responsive to the receiving of the indication, obtaining user profile data associated with the user; responsive to the receiving the user profile data, selecting a first service provider from among a plurality of service providers; and routing communications between the first service provider and the user equipment. Other embodiments are disclosed.

System and method for off-loading subscriber identification module (SIM) capabilities

Growing community of inventors

Round Rock, TX, United States of America

James H Pratt