Abstract: Aspects of the subject disclosure may include, for example, detecting data streams by a processing system including a processor, wherein the processing system is associated with an anomaly detection and alerting system in which stream processing and model maintenance is decoupled from one another, and wherein one or more dedicated virtual machines (VMs) store and maintain anomaly detection and alerting models, based on the detecting, causing, by the processing system, a plurality of stream-processing VMs to be instantiated for processing the data streams, and managing, by the processing system, data stream assignments for the plurality of stream-processing VMs based on monitoring of one or more conditions, wherein the plurality of stream-processing VMs process assigned data streams by executing instances of the anomaly detection and alerting models, and provide model outputs to the one or more dedicated VMs for updating of the anomaly detection and alerting models. 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: 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, receiving, via an interactive user interface, user selections of a dataset and a first dimension of a plurality of dimensions in a hierarchical structure, wherein the dataset corresponds to a specific domain and comprises anomalies or alerts that are aggregated in certain dimensions, and wherein a lattice of aggregations of the anomalies or alerts is defined for the specific domain, causing the interactive user interface to present a time series chart and a heatmap, wherein the time series chart portrays alert density across dimensions below the first dimension, wherein the heatmap displays, according to a visual scheme, concentrations of the anomalies or alerts across at least a portion of the dimensions below the first dimension, and wherein user interaction with the time series chart and/or the heatmap facilitates navigation of subspaces of the lattice and exploration of the concentrations of the anomalies or alerts.

Abstract: Restoring network configurations using network topology snapshots can include obtaining a first network topology snapshot that describes a first configuration of a network environment at a first point in time, obtaining a second network topology snapshot that describes a second configuration of the network environment at a second point in time, calculating a difference between the first network topology snapshot and the second network topology snapshot, presenting the difference for display, in response to determining that a request to restore a previous configuration has been received, identifying a configuration change that is to be reverted and a restore point associated with the configuration change to be reverted, and outputting a command that, when executed by an orchestration service, causes the orchestration service to revert the configuration change.

Abstract: Aspects of the subject disclosure may include, for example, a method that includes downloading, to each of a plurality of vehicles each including a sensor, a sharing microservice (SM) to collect sensor data comprising information regarding operation of the vehicle and an environment of the vehicle; receiving from each SM a sensor data feed comprising the collected sensor data, where each of the data feeds is accessible to each of the plurality of vehicles; generating for each of the plurality of vehicles an image of a local environment of that vehicle based on the sensor data feed; and communicating with a target vehicle to recommend a sensor data feed from another vehicle. 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: Aspects of the subject disclosure may include, for example, a method including generating a plurality of discrete polygons from a digital image of a location, modifying a boundary of a first discrete polygon of the plurality of discrete polygons based on a user input at a venue map graphical user interface, assigning, at the venue map graphical user interface, a first zone of a plurality of zones associated with a first venue of a plurality of venues to a second discrete polygon of the plurality of discrete polygons, and presenting a performance map graphical user interface for the first venue of the plurality of venues including the second discrete polygon of the plurality of discrete polygons overlaid onto the digital image of the location. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, determining a Reference Signal Received Power (RSRP) and a Signal to Noise Ratio (SNR) for a plurality of carriers at a user equipment (UE) device, the plurality of carriers transmitted by a source group of cells including a source primary cell (PCell) and one or more source secondary cells (SCells) associated with the source PCell, and initiating a handover of communication with the UE device from the source group of cells to a target group of cells, wherein the target group of cells includes a target PCell and one or more target SCells, wherein the initiating the handover is responsive to the RSRP exceeding a predetermined RSRP threshold and the SNR exceeding a predetermined SNR threshold. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, an end-user 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: storing for each other end-user device of a plurality of other end-user devices a respective identification, the end-user device and the plurality of other end-user devices forming a group; receiving a first indication of a first subset of the group with which to carry out first communications, the first subset comprising one or more first target end-user devices selected from the group; responsive to receipt of the first indication, sending to each of the one or more first target end-user devices a first instruction to communicate with the end-user device via a first dynamically determined channel; and engaging in the first communications with each of the one or more first target end-user devices after each of the one o

Abstract: Aspects of the subject disclosure may include, for example, receiving a data packet for transmission over a wireless network to a user equipment (UE) device in data communication with one or more network elements over one or more carrier legs of the wireless network, receiving information about current network conditions, retrieving a set of packet splitting rules which define initial boundary conditions for a process of splitting packets into smaller data packets for transmission to the UE device, applying, in a machine learning model, one or more packet splitting rules of the set of packet splitting rules to split the data packet into a set of smaller data packets, based on the information about current network conditions in the wireless network, selecting, in the machine learning model, a flow control arrangement for the data packet, including determining a number of smaller packets to split the data packet, and selecting respective carrier legs of the one or more carrier legs of the wireless network for c

Abstract: Aspects of the subject disclosure may include, for example, a device, including: a sensor affixed to an article of clothing; a transducer affixed to the article of clothing; 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: receiving sensor data from the sensor; processing the sensor data; sending the sensor data to a trained machine learning (ML) model having as inputs the sensor data, and providing as output, control data to control the transducer; receiving the control data from the trained ML model; and sending the control data to the transducer to provide therapy to a patient. Other embodiments are disclosed.

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: Aspects of the subject disclosure may include, for example, obtaining a first portion of a communication service via a first signal having a first frequency within a first band of frequencies, subsequent to the obtaining of the first portion of the communication service, obtaining data associated with a plurality of parameters, analyzing at least the data to identify when a scan for a second signal having a second frequency within a second band of frequencies should be performed, wherein the second band of frequencies is different from the first band of frequencies, and scanning for the second signal based on the analyzing. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, obtaining an image of a code from a first mobile device associated with a first user. The code is associated with a community social media platform. Further embodiments can include allowing the first mobile device access to the community social media platform in response to validating that the first user is associated with a community associated with the community social media platform, and obtaining a request from the first mobile device for a service. Additional embodiments can include identifying a second mobile device associated with a second user based on the second user providing the service, and providing a message to the second mobile device indicating the second user perform the service for the first user. Other embodiments are disclosed.

Abstract: Aspects include receiving a search request, comparing at least one term of the search request to a plurality of metadata items, wherein each metadata item of the plurality of metadata items is associated with a respective asset of a plurality of assets, generating a plurality of scores, wherein each score of the plurality of scores is associated with a respective asset included in the plurality of assets, and wherein a value of each score of the plurality of scores is based on an identification of a user, selecting at least one asset of the plurality of assets in accordance with the plurality of scores and in accordance with at least one threshold, providing the at least one asset to a communications device that is associated with the user, and providing at least a portion of a metadata item included in the plurality of metadata items to the communications device.

Abstract: Aspects of the subject disclosure may include, for example, transmitting a first value for a first parameter to a first user equipment, wherein the first parameter pertains to a first number of scans to be performed by the first user equipment to detect a first signal having a first frequency within a first frequency band as part of a first scanning procedure, and transmitting a second value for a second parameter to the first user equipment, wherein the second parameter pertains to a first amount of time that the first user equipment is to wait between the first scanning procedure and a second scanning procedure, the second scanning procedure pertaining to detection of the first signal having the first frequency within the first frequency band. Other embodiments are disclosed.

Abstract: The concepts and technologies disclosed herein are directed to home gateway monitoring for vulnerable home Internet of Things (“IoT”) devices. According to one aspect disclosed herein, a home gateway can scan a home network address space of a home network for an IoT device. The home gateway can perform a vulnerability test on the IoT device to determine whether the IoT device is vulnerable to a known vulnerability. In response to determining that the IoT device is vulnerable to the known vulnerability, the home gateway can change a device status of the IoT device to a vulnerable status and can change a permissions level of the IoT device to a quarantine permissions level.

Abstract: An access point impersonation protection system (“the system”) can scan for wireless network signals to detect a wireless network provided by a malicious access point. The system can collect a network feature associated with the wireless network. The system can analyze the network feature and can provide analysis results to a machine learning classifier. The machine learning classifier can assign a classification to the access point. The classification can be a benign classification indicative of the access point being benign. The classification can be a malicious classification indicative of the access point being malicious. The network feature can be an active time, an SSID name, a vendor, a model, a signal strength, an authentication requirement, or a combination thereof. The system can alert upon identifying a malicious access point and apply counter measures to prevent the malicious access point from causing harm to nearby devices.

Abstract: Aspects of the subject disclosure may include, for example, a drone service retrieving network state information describing a network state of at least a portion of a communication network, determining an impact of the network state on operation of an unmanned aerial vehicle (UAV), selecting a carrier frequency to be used for communication by the UAV, and providing the data describing the carrier frequency to the UAV and/or to communication network nodes. Other embodiments are disclosed.

Abstract: A method includes determining, by a vehicle, a failure with a computer or telecommunications system operating in the vehicle and when a failure is detected, activating an acoustic system on the vehicle, detecting a vibration by the vehicle; and transmitting an audible signal responsive to the detecting step. The audible signal may include words in a human vocabulary.

Abstract: Aspects of the subject disclosure may include, for example, an AT command that allows an application service provider to modify suspend/resume (S/R) and/or deactivate/activate (D/A) functionality specified in one or more elementary files of a UICC. The S/R and/or D/A functionality can be influenced by the application service provider without relying on SIM-OTA messages being forwarded by a mobile operator. 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, define operations of modules that monitor a computational hierarchy, the modules include a first module for generating base alerts with a hierarchical key associated with an operation of the computational hierarchy and for rolling up the base alerts based on the computational hierarchy, resulting in rolled-up base alerts; a second module for generating super alerts from a concentration of the rolled up base alerts; and a third module comprising a first plurality of models that selects the super alerts based on priority, persistence of anomalies, pervasiveness of the super alerts generated, recency, or a combination thereof, generates a smart alert based on voting on the super alerts selected by the first plurality of models, and presents the smart alert on a user interface.

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, the operations including monitoring, by a plurality of models implemented by the executable instructions, a plurality of data streams comprising super alerts; and generating a smart alert based on voting on the super alerts by the plurality of models. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, a device comprising: a female port configured to receive a data connector, the data connector comprising a surface with a first opening; a first movable member disposed within the female port, the first movable member being configured such that as the data connector is moved into the female port a first portion of the first movable member enters into the first opening; and a first blocking member disposed within the female port, the first blocking member being configured to move to a first blocking position to block the first portion of the first movable member from exiting the first opening after the first portion of the first movable member has entered the first opening. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, a non-transitory, machine-readable medium, comprising executable instructions that, when executed by a processing system including a processor, facilitate performance of operations including receiving a call; selecting a next carrier to handoff the call; generating a call data record (CDR) for the handoff to the next carrier; encrypting the CDR using a call encryption key, thereby creating an encrypted CDR; encrypting the encrypted CDR using a committee encryption key, thereby creating a double encrypted CDR; recording the double encrypted CDR to a blockchain; and sending the call encryption key to the next carrier. Other embodiments are disclosed.

Abstract: A method for bundling network functions as a single microservice in a cloud environment. A service deployment manager may acquire subscriber location information associated with a subscriber or a subscriber profile associated with the subscriber. Moreover, the service deployment manager may utilize the subscriber location information or the subscriber profile to select a cloud location. For example, the cloud location may be based on load, geographical proximity, service profile, etc.

Abstract: Aspects of the subject disclosure may include, for example, determining a capability of a mobile device, collecting a mobile station measurement, applying a rule according to the capability and measurement to obtain a radio access network (RAN) recommendation that identifies one of a first or second RANs as a preferred RAN, wherein a service is provided to the device via the preferred RAN. The first RAN comprises a first base station that supports a first exchange of user data and corresponding control signaling to facilitate access to a first set of services. The second RAN comprises a second base station adapted to support a second exchange of user data and a third base station adapted to support a corresponding exchange of control signaling to facilitate access to a second set of services. The second RAN is unable to facilitate access to the first set of services. Other embodiments are disclosed.

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: Concepts and technologies are disclosed herein for using user equipment data clusters and spatial temporal graphs of abnormalities for root cause analysis. User equipment data can be obtained from a cellular network. A filter having a threshold can be applied to the user equipment data to obtain records. A determination is made whether the threshold is to be adaptively adjusted. If a determination is made that the threshold is not to be adjusted, the records can be added to a record set. The records in the subset of records can be correlated based on a key to obtain a filtered and correlated version of the record set, a spatial temporal graph of abnormalities associated with the cellular network can be generated based on the filtered and correlated version of the record set, and a root cause of a failure can be determined based on the spatial temporal graph of abnormalities.

Abstract: Aspects of the subject disclosure may include, for example, a UAV communicatively coupling with a UAV controller over a first network, during a flight of the UAV, detecting availability of a device that is capable of providing network connectivity over a second network, based on the detecting the availability of the device, determining to communicatively couple with the device, responsive to the determining to communicatively couple with the device, submitting a request to the device for the network connectivity, and based on the submitting the request, establishing a communication session with the device to obtain the network connectivity. Other embodiments are disclosed.

Abstract: Concepts and technologies disclosed herein are directed to enhanced smart home services. According to one aspect disclosed herein, a home gateway device can capture, from a home device, home data associated with home user activity conducted via a fixed communications network. The home gateway device can determine, based upon the home data, a home data profile. The home gateway device can receive a mobility data profile determined by a mobility data profiler based upon mobility data associated with mobile user activity conducted via a mobile communications network. The home gateway device can determine, based upon the mobility data profile and the home data profile, a policy for the home device. In some embodiments, the home device is an IoT device. In other embodiments, the home device is a media device such as a television, a video streaming device, a music streaming device, or a video game device.

Abstract: Aspects of the subject disclosure may include, for example, obtaining first information indicative of data plane utilization, wherein the data plane is associated with a wireless communications network; obtaining second information indicative of control plane utilization, wherein the control plane is associated with the wireless communications network; applying the first information and the second information to one or more machine learning algorithms; and generating via the one or more machine learning algorithms one or more outputs, wherein the one or more outputs indicates whether one or more network resources should be added to improve the data plane utilization. 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, receiving, from a computing device, a user request to perform a subscriber identity module (SIM) swap for a subscriber, wherein the computing device and a user device are accessible to a user, based on the receiving the user request, generating a code for the SIM swap, resulting in a generated code, providing the generated code to the computing device for presentation, obtaining, from the user device, data associated with the user, the user device, or a combination thereof, facilitating user authentication responsive to the obtaining the data, detecting a transmission of a particular code from the user device, resulting in a detected code, and, based on the detecting the transmission and based on the facilitating the user authentication, performing an action relating to the SIM swap. 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: Aspects of the subject disclosure may include, for example, generating a set of SRLGs associated with a set of link bundles, wherein the set of SRLGs comprises for each SRLG in the set of SRLGs an indication for each failed link bundle in a particular SRLG a respective bandwidth failure fraction, and wherein for at least one of the failed link bundles the failure is less than a complete failure; generating a set of dominance relationships among the SRLGs in the set of SRLGs, and generating, based at least in part upon the set of SRLGs and the set of dominance relationships a packed set of SRLGs, wherein the packed set of SRLGs comprises a subset of the set of SRLGs. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, obtaining traffic that is conveyed at least in part within a private cloud network, based on the obtaining, identifying characteristics of the traffic, and based on the identifying of the characteristics of the traffic, causing at least one action to be performed within the private cloud network. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, obtaining a group of images of a premises from a group of cameras associated with a first time period, generating computer vision data associated with a premises from the group of images for a first time period utilizing a group of image recognition techniques, obtaining employee schedule information associated with the premises for the first time period, and obtaining point-of-sale information associated with the premises for the first time period. Further embodiments include determining a first walk-out metric associated with the premises for the first time period according to the computer vision data, the employee schedule information, and the point-of-sale information. The first walk-out metric is based on a first number of customers leaving the premises without interacting with an employee associated with the premises during the first time period. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, a device including a processing system that evaluates a need for additional data streaming resources at the device, and determines that a set of cooperating devices, located within a predetermined distance, is configured for sharing data streaming resources. The device receives the requested data from the cooperating devices in simultaneous streams, each stream including a segment of the requested data. The data source sends the requested data in parallel streams to the set of cooperating devices respectively, in accordance with addresses provided to the data source for each of the cooperating devices. The processing system assembles the requested data from the simultaneous streams. Other embodiments are disclosed.

Abstract: A method that incorporates the subject disclosure may include, for example, providing a first digital assistant to engage in a first communication exchange with a user of the first communication device where the first digital assistant has a first digital assistant persona that controls information provided by the first digital assistant during communication exchanges, analyzing user input during the first communication exchange, and adjusting the first digital assistant persona based on one or more of the user persona, user deficiency, or promotional offers. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, system and apparatus that enable operations that may include receiving, by a processing system, project data defining a proposed machine learning(ML) project of an entity and storing the project data in a project database with other project data for other projects. The operations may further include extracting extracted features of the proposed project and, based on the extracted features, determining a clustering assignment for the proposed project. Determining the clustering assignment may comprise comparing information about the proposed project including the extracted features with information about the other projects and assigning the proposed project to a cluster including one or more projects having similar bias characteristics as the proposed project. The operations may further include determining a risk of potential bias for the proposed project and, based on the risk of bias, recommending a corrective action to reduce the risk of bias.

Abstract: Aspects of the subject disclosure may include, for example, detecting whether a bandwidth capacity loss occurs on a first link bundle connecting one or more first core routers of a core Interior Gateway Protocol (IGP) network with one or more first provider routers, resulting in a detected capacity loss, wherein communication between the one or more first core routers of the core IGP network and the one or more first provider routers utilizes a Border Gateway Protocol (BGP), wherein a second link bundle connects one or more second core routers of the core IGP network with one or more second provider routers, and wherein communication between the one or more second core routers of the core IGP network and one or more second provider routers utilizes the BGP; responsive to the detected capacity loss, automatically increasing a cost associated with selected network traffic that was to be carried between the one or more first provider routers and the one or more first core routers of the core IGP network and that

Abstract: Aspects of the subject disclosure may include, for example, obtaining for a first path carrying first network traffic a corresponding first alternate path; obtaining for a second path carrying second network traffic a corresponding second alternate path, at least a first portion of the first alternate path being the same as at least a second portion of the second alternate path; responsive to a first detected failure on the first path, causing communication of first re-directed network traffic via the first alternate path instead of via the first path; responsive to a second detected failure on the second path, detecting whether total traffic, including the first re-directed network traffic, on the first portion of the first alternate path meets a threshold; responsive to the detected meeting of the threshold, obtaining for the second path a corresponding back-up alternate path; and causing communication of second re-directed network traffic via the back-up alternative path instead of via the second path.

Abstract: Aspects of the disclosure include transmitting first payload data to a first communication device via a first link, subsequent to the transmitting of the first payload data, obtaining a first indication that a handover is being negotiated between the first communication device and a second communication device, based on the first indication, placing, at a processing system, the first link in an inactive state, based on the first indication, storing second payload data in a buffer, and responsive to obtaining a second indication that the second communication device has accepted the handover: activating, at the processing system, a second link between the processing system and the second communication device, obtaining the second payload data from the buffer, and transmitting, based on the activating of the second link, the second payload data obtained from the buffer to the second communication device via the second link. Other aspects are disclosed.

Abstract: Methods, systems, and apparatuses, for real-time operation control, among other things. There may be adjustments to a first device in which a first network service operates. The adjustment to the device may include moving a second network service of the first device to a second device. The first network service and the second network service may be associated with virtual machines.

Abstract: Aspects of the subject disclosure may include, for example, a method including assessing a danger level associated with an object; locating a target person and a caregiver; monitoring movement of an unsupervised target person relative to a boundary around the object; and providing a warning in a caregiver's voice if the person crosses the boundary. A content and volume of the warning, a direction of the warning with respect to a trajectory of movement of the person, and a tone of voice of the warning can be selected according to the danger level and a profile of the person. The method also includes initiating a distraction procedure directed to the person according to the profile; the distraction can include an audio message directing attention of the person to another object. Other embodiments are disclosed.

Abstract: Concepts and technologies are disclosed herein for creating and using native virtual probes in computing environments. A request for a service that includes a virtual function can be received, where the virtual function is to be monitored by a native virtual probe. An image of the service can be obtained, where the image can include a first image component for the virtual function and a second image component for the native virtual probe. The image can be deployed. Deployment of the image can result in instantiation of the virtual function on a computing device and instantiation of the native virtual probe on the computing device.

Abstract: Aspects of the subject disclosure may include, for example, a method in which a processing system detects user equipment (UE) in communication with a network via a serving cell of the network; the network is configured to facilitate communications by one or more terrestrial UEs and one or more aerial UEs. The system monitors messages from an aerial UE regarding detection of a cell other than the serving cell, and receives information from the aerial UE regarding the detected cell. The method further includes analyzing the information to estimate a first quantity associated with the detected cell location relative to the serving cell and a second quantity associated with a power received at the aerial UE from the detected cell. The method also includes determining, based on the analyzing, whether the aerial UE is an unauthorized aerial UE. Other embodiments are disclosed.