Abstract: A critical path based proactive optimization that includes collecting data on the tasks of contextual situation for performing a process and training a twin computing simulation model using the collected data for each task in the process. A contextual situation simulation is run using the simulation models for each task in the process to determine a critical path that causes delay in the process. An optimized task is determined from the tasks of the contextual situation using machine learning employing the collected data, wherein the optimized task mitigates delay in the process from the critical path.

Abstract: An embodiment for dynamically creating a vehicle fence is provided. The embodiment may include receiving GPS data from one or more vehicles and a real-time video feed of one or more intersections along a first roadway. The embodiment may also include identifying a number of autonomous vehicles and one or more routes of the autonomous vehicles traveling on the first roadway. The embodiment may further include in response to determining an emergency vehicle is traveling on the first roadway, identifying a route and speed of the emergency vehicle. The embodiment may also include estimating a width of a second roadway intersecting the first roadway at a nearest intersection. The embodiment may further include identifying a moving direction of one or more objects along the second roadway. The embodiment may also include deploying a required number of autonomous vehicles to block the one or more objects from entering the nearest intersection.

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: A computer-implemented dynamic supporting base creation method that interacts with a three-dimensional (3D) printer that prints an object, the method including providing a physical support, via a first robotic gripper, for an object during three-dimensional (3D) printing using a printing head of the 3D printer and transferring the object to a second robotic gripper to provide a physical support at a different location on the object.

Abstract: A processor may receive object data associated with an object in an environment. The processor may generate one or more simulations associated with the object using the object data. The processor may analyze the one or more simulations to identify one or more potential issues associated with the object. The processor may deploy the one or more smart devices to the object to capture issue data associated the one or more potential issues.

Abstract: A computer-implemented method, system and computer program product for seamlessly adjusting the utilization of computational resources of a computing device. A pattern of usage of computational resources of the computing device over a timeframe is determined. An artificial intelligence model uses such a pattern of usage and/or any identified contextual needs for upgrading or downgrading the computational resources of the computing device to determine the predicted amount of computational resources needed to be utilized by the computing device. Based on such a predicted amount, a blockchain transaction may be initiated and recorded to upgrade/downgrade the computational resources of the computing device.

Abstract: Decentralized cloud service assessment includes using a self-executing data structure, an error confirmation capsule (ECC) generated in response to a cloud service failure experienced by a cloud service client (CSC). One or more technical performance indicia corresponding to the cloud service failure are extracted from the ECC in response to the validating. The one or more technical performance indicia are compared to one or more electronically stored predefined performance norms of a cloud service provider (CSP) associated with the cloud service failure. Based on the comparing, a comparative ranking of the CSP is determined. A graphical user interface display is generated based on comparative rankings of the CSP and one or more other CSPs.

Abstract: A method for collaborative data sharing for data anomalies includes identifying an anomaly with data for a first system on a first vehicle. In response to determining the data associated with the anomaly is capturable by other vehicles, the method further includes identifying a second vehicle in the vicinity in the first vehicle, wherein the vicinity is defined by an operational distance of the first system on the first vehicle. The method further includes capturing, by a second system on the second vehicle, the data associated with the anomaly. In response to determining captured data by the second system on the second vehicle requires transformation to conform to the first vehicle, the method further includes transforming the captured data by the second system on the second vehicle to conform to the first vehicle.

Abstract: Computer technology for: (i) determining which version of a software service to use depending upon whether the user requesting the service is a beta tester, and (ii) if the user status of the user requesting a software service is beta tester then: (a) that user will have the newer, testing-phase version of the software service used to fulfill the software service request, and (b) the user will be given an opportunity to provide feedback on the effectiveness and/or performance of the service to effect the beta testing of the new version of the software service under test.

Abstract: A computer-implemented method for dynamic landscape channeling using an autonomous robotic soil dredger. The method derives one or more landscape metrics, wherein the one or more landscape metrics comprise soil metrics, environmental conditions, and vegetation water consumption metrics. The method further generates a digital twin of proposed trench and ridge metrics based on the derived one or more landscape metrics, wherein the proposed trench and ridge metrics comprise a depth of the trench, a distance between one or more trenches, a stream size, a slope of the trench, and a shape of the trench. The method further determines a trench pattern based on the generated digital twin of the proposed trench and ridge metrics and collaborates with the autonomous robotic soil dredger to generate the trench pattern.

Abstract: A processor may automatically select a cloud service provider. A processor may receive one or more parameters associated with an entity and a cloud service dataset associated with a provider. A processor may generate a digital twin of the entity using the one or more parameters. A processor may simulate the digital twin of the entity and the cloud service dataset. A processor may identify, responsive to simulating the digital twin of the entity and the cloud service dataset, one or more predicted conditions of cloud service dataset on the entity. A processor may select the provider based, at least in part, on the one or more predicted conditions.

Abstract: A method providing a support device to assist personnel includes receiving data values from various devices associated with a task being performed by personnel, wherein the various devices include at least one Internet of Things (IoT) device and at least one wearable device. The method also includes comparing the received data values to historical data values associated with a pre-established knowledge corpus and identifying the task being performed by the personnel. In response to determining the received values exceed the historical values by a predetermined threshold for the task being performed by the personnel, the method includes determining whether the personnel require assistance with performing the task. In response to determining the personnel requires assistance with performing the task, the method includes instructing a support device to perform an action to assist the personnel with performing the task.

Abstract: According to one embodiment, a method, computer system, and computer program product for converting traffic noises is provided. The embodiment may include capturing audio input relating to traffic conditions or environmental conditions surrounding a user or a vehicle containing a user. The embodiment may also identifying undesirable noises from within the captured audio. The embodiment may further include generating mood-improving sounds for a user based on the identified noises. The embodiment may also playing the generated sounds for the user. The embodiment may further include alerting the user or a second user of relevant traffic conditions or relevant environmental conditions including conditions that correspond to the identified noises.

Abstract: A method for authenticating a device based on a wireless power transmission signal includes receiving, at an authenticating device, a wireless power transmission signal for authentication of a user device attempting to accessing a resource, where the wireless power transmission signal includes a unique identifier for the user device. The method further includes translating, at the authenticating device, the wireless power transmission signal, wherein the unique identifier for the user device is embedded in the wireless power transmission signal as a bit representation. In response to authenticating the user device based on a translated wireless power transmission signal, the method further includes granting, the user device, access to the resource.

Abstract: A computer implemented method manages nonintelligent items. A computer system identifies a workflow to be performed. The computer system identifies a group of the nonintelligent items involved in actions for the workflow. The computer system attaches a set of computing devices to the group of the nonintelligent items to convert the group of the nonintelligent items into a group of converted nonintelligent items. The computer system performs the actions in the workflow using the group of converted nonintelligent items.

Abstract: A processor may receive object data associated with an object in an environment. The processor may generate one or more simulations associated with the object using the object data. The processor may analyze the one or more simulations to identify one or more potential issues associated with the object. The processor may deploy the one or more smart devices to the object to capture issue data associated the one or more potential issues.

Abstract: A processor may receive environment data associated with a robotic device in an environment. The processor may analyze the environment data to identify one or more activities the robotic device may perform in the environment. The processor may generate one or more simulations associated with the one or more activities and the robotic device. The processor may determine one or more limitations of the robotic device associated with the one or more activities. The processor may identify, responsive to determining one or more limitations, one or more apparatuses. The one or more apparatuses may be associated with the one or more limitations.

Abstract: Computer technology for: (i) determining which version of a software service to use depending upon whether the user requesting the service is a beta tester, and (ii) if the user status of the user requesting a software service is beta tester then: (a) that user will have the newer, testing-phase version of the software service used to fulfill the software service request, and (b) the user will be given an opportunity to provide feedback on the effectiveness and/or performance of the service to effect the beta testing of the new version of the software service under test.

Abstract: Provided are a computer program product, system, and method for determining content values to render in a computer user interface based on user feedback and information. Detection is made of a section of the document rendered in a computer user interface that the user is observing. A monitoring device detects user biometric data in response to detecting the section the user is observing. Input is provided to a machine learning module comprising the content value in the section the user is observing, the user biometric data, and personal information of the user. Output from the machine learning module indicates a likelihood that the user approved or disapproved of the content value in the section the user was observing. The output is used to determine whether to send a substitute content value of the plurality of content values to render in the section the user is observing.

Abstract: A critical path based proactive optimization that includes collecting data on the tasks of contextual situation for performing a process and training a twin computing simulation model using the collected data for each task in the process. A contextual situation simulation is run using the simulation models for each task in the process to determine a critical path that causes delay in the process. An optimized task is determined from the tasks of the contextual situation using machine learning employing the collected data, wherein the optimized task mitigates delay in the process from the critical path.