Abstract: An embodiment for controlling a boundary of an AI system based on an environmental context is provided. The embodiment may include receiving data input from one or more sources. The embodiment may also include identifying one or more contextual situations in a surrounding environment. The embodiment may further include identifying one or more input data collection boundaries and a span of control boundary for an AI-enabled device. The embodiment may also include connecting the AI-enabled device to one or more data generation modules within the one or more input data collection boundaries. The embodiment may further include in response to determining none of the one or more data generation modules are unable to connect, identifying an action to be performed by the AI-enabled device. The embodiment may also include executing the action in a first set of one or more machines within the span of control boundary.

Abstract: By monitoring an in-person interaction using a first Internet of Things (IoT) device, an entity relationship between parties in the in-person interaction is identified. Using data resulting from the monitoring, a habit workflow corresponding to the entity relationship is generated, wherein the habit workflow comprises a sequence of habits and a habit in the sequence of habits comprises performance of a behavior. A second IoT device able to monitor execution of the habit workflow is identified. Using the second IoT device, execution of the habit workflow is monitored. A motivational method corresponding to the execution is identified from the monitored execution.

Abstract: A system and method for bandwidth management are provided. In embodiments, a method includes: training, by a computing device, a predictive machine learning (ML) model based on historic network usage data of software applications in a cloud environment and historic business context data; assigning, by the computing device, priority rankings to software application activities of the cloud environment using the predictive ML model based on predicted resource requirements for the software application activities of the cloud environment and predicted contextual scenarios that impact the predicted resource requirements using an input of real-time network usage data of the cloud environment and real-time business context data; and initiating, by the computing device, scheduling of the software application activities based on the priority rankings.

Abstract: A method for transferring content utilizing contextual positioning includes receiving a content selection for transferring from an originating device. The method also includes determining contextual positioning in a user interface of the originating device for each portion of the content selection, wherein the contextual positioning is based on the content selection and one or more objects in the user interface of the originating device. The method also includes sending, to a receiving device, each portion of the content selection with the determined contextual positioning in the user interface of the originating device. The method also includes placing, in the user interface of the receiving device, each portion of the content selection is based on the determined contextual positioning in the user interface of the originating device.

Abstract: A current state of a mobile computing device may be monitored. The mobile computing device has a set of one or more installed applications. The current state is related to the set of installed applications. A first computing action of a user of the mobile computing device is identified responsive to the current state. The first computing action is related to the set of installed applications. Responsive to the first computing action, a set of one or more candidate computing actions is determined. The mobile computing device generates, based on the first computing action, a projected visualization that relates to a first candidate computing action of the set of candidate computing actions.

Abstract: An embodiment for creating a tiled image using different zoom levels based on user interests is provided. The embodiment may include receiving one or more photographs captured by a user. The embodiment may also include analyzing features associated with the one or more photographs. The embodiment may further include identifying one or more known objects of interest. The embodiment may also include in response to determining the user wants to take a tiled zoom photograph, capturing a photographic image. The embodiment may further include scanning the photographic image for identifying features of the one or more known objects of interest. The embodiment may also include in response to determining at least one object of interest is found in the scanned photographic image, assembling the tiled zoom photograph with a plurality of tiles.

Abstract: Embodiments relate to a system, program product, and method for leveraging cognitive systems to facilitate the bilateral contextual alignment of textual material and associated diagrammatic matter. The system, computer program product, and method disclosed herein facilitate leveraging a trained cognitive system to understand textual and diagrammatic patterns established by a user, and to learn to draft and edit such textual material and associated diagrammatic matter based on user behavior and preferences. The cognitive system is trained to bilaterally translate between textual material and diagrammatic matter, where the cognitive system includes natural language processing (NLP) features, diagram analytics features, and one or more user profiles.

Abstract: A method, computer program product, and system include a processor(s) obtaining an instruction to perform an inspection of a given type at a geographic site. The processor(s) deploys a robotic drone to the geographic site, wherein based on the deployment, the robotic drone performs a contextual analysis on the geographic site to identify a use case and to collect locational data. The processor(s) obtains the locational data. Based on the locational data, the given type of the inspection, and the use case, the processor(s) generates an inspection plan comprising tasks. The processor(s) identifies robotic drone(s) to complete the tasks and distributes the tasks. The robotic drone( )automatically self-optimize/s to complete the tasks. The processor(s) obtain the collected data from the self-optimized identified one or more robotic drones. The processor(s) analyze the collected data to identify issue(s) at geographic site.

Abstract: An approach for reducing edge computing resources associated with autonomous vehicle infrastructure is disclosed. The approach utilizes digital twin computing to create a digital copy of the autonomous vehicle and edge computing demand. The approach can simulate the entire journey of the autonomous vehicle(s) on a travel path to determine the edge computing resources requirements. And based on the generated data set, the approach provides recommendations of proactive vehicle maintenance plan to improve edge computing capability of the vehicle based on the selected route. Other recommendation can include identifying whether road maintenance is to be performed for optimum usage of edge computing capability.

Abstract: Aspects of the present disclosure relate to in-air control regions. Communication between an electronic pen and a device can be established. Two or more in-air control regions above the device can be defined, each in-air control region specifying a set of functions that can be performed by the electronic pen. A determination can be made that the electronic pen is within a first in-air control region of the two or more in-air control regions, the first in-air control region specifying a first set of functions that can be performed by the electronic pen. In response to input received from the electronic pen within the first in-air control region, at least one function of the first set of functions can be executed.

Abstract: A computer-implemented method includes receiving data regarding an area to be cleaned, the data comprising data regarding movement of people or machines through the area to be cleaned; training a machine learning cleaning model based on the data; creating a floor cleaning plan using the machine learning cleaning model, the floor cleaning plan identifying a cleaning time to minimize a likelihood of a robotic cleaning device encountering a person or a machine while cleaning; and transmitting the floor cleaning plan to a robotic cleaning device.

Abstract: A processor may receive assembly data associated with one or more assembly robots and an object. The object may be assembled by the one or more assembly robots performing one or more assembly maneuvers. The processor may analyze the assembly data and the one or more assembly maneuvers associated with assembling the object. The processor may identify one or more alterable factors associated with the one or more assembly maneuvers. The processor may generate an optimized assembly plan based, at least in part, on altering the one or more alterable factors associated with the one or more assembly maneuvers. The processor may assemble the object based on the optimized assembly plan.

Abstract: A computer-implemented method, including: analyzing, by a computing device, historical information associated with a business application; determining, by the computing device, a business process based on the analyzed historical information; generating, by the computing device, a virtual reality simulation of the business process; identifying, by the computing device, a business application requirement based on a user interaction with the virtual reality simulation; and generating, by the computing device, the ad-hoc application based on the identified business application requirement.

Abstract: An approach for moving materials from one location to another is disclosed. The approach includes a mobility platform comprising of a lower construct comprising of mechanism for locomotion, a platform dispose on top of and adjacent to the lower construct and an upper construct dispose and adjacent to the platform, wherein the upper construct comprising of a mechanism for securing materials. Furthermore, the approach includes loading one or more materials onto the mobility platform from a first location, moving the mobility platform from the first location to a second location and unloading the one or more materials from the mobility platform at the second location.

Abstract: Aspects of the present disclosure relate to gesture-based one-time password (OTP) authentication for transactions. Initiation of a transaction can be detected. Contextual information associated with the transaction can be received. In response to detecting the initiation of the transaction and based on the contextual information associated with the transaction, a one-time password (OTP) comprising one or more gestures to be performed by a user can be generated. A command can be transmitted to display the one or more gestures to be performed on an extended reality (XR) device worn by the user. In response to validating user performance of the one or more gestures displayed via the XR device, the transaction can be authorized.

Abstract: A voice signal in a headphone is detected. The voice signal includes a person speaking an audible command. Based on detecting the voice signal a first biometric signature of a user is retrieved. The first biometric signature is compared to one or more biometric features of the person. Based on comparing the first biometric signature to the one or more biometric features an authentication of the user is determined. An authentication action is performed based on the detected voice signal. The authentication action is performed in response to verifying the authentication.

Abstract: In an approach for predictive forecasting of food allocation, a first data is received from one or more sensors. The amount and condition of available food is determined from the first data. The number and location of people is determined from the first data. The received data is modified to create a second data. One or more food requirements for the people are predicted based on the number and location of people and the second data. An optimal food allocation for the people is predicted based on the amount and condition of food available and the one or more food requirements. The optimal food allocation is reported.

Abstract: A computer system, computer program product, and computer-implemented method are provided for facility evacuation. The method includes determining one or more environmental conditions adverse to one or more occupants within a structure at least partially enclosing a ventilation system and one or more passageways therein. The method also includes predicting movement patterns of the one or more adverse environmental conditions within the at least a portion of the structure. The method further includes creating, through the ventilation system, at least partially subject to the predicting, one or more evacuation routes including at least a first portion of the one or more passageways comprising reducing, at least partially, the one or more adverse environmental conditions within the one or more evacuation routes.

Abstract: A processor may receive user command generated by a user. A processor may analyze user information for one or more official activities. The one or more official activities are based, at least in part, on a security policy. A processor may identify the user information is associated with the one or more official activities. A processor may prevent, responsive to determining the user command is associated with the one or more official activities, the one or more personal devices from collecting the user command.

Abstract: A computer-implemented method includes: predicting, by a computing device, devices for inclusion in an interface; generating, by the computing device, the interface including areas corresponding to the devices; detecting, by the computing device, a user selection of one of the areas of the interface; detecting, by the computing device, a hand gesture associated with the selected one of the areas; and transmitting, by the computing device, data defining the hand gesture to a respective one of the devices corresponding to the selected one of the areas, thereby causing the respective one of the devices to execute a command based on the hand gesture.