Abstract: Methods, computer program products, and systems are presented. The method computer program products, and systems can include, for instance: with a user engaged in a user session within a first environment, examining historical data of the user, wherein the examining historical data of the user includes examining historical data of a previously recognized article of the user previously recognized in a second environment; and provisioning an article of the user within the first environment to include a functional behavior.

Abstract: In an approach to improve the management of operating vehicles through smart contracts, embodiments generate a priority score based on received sensor feeds from a vehicle, co-located vehicles, and a smart contract rule. Further, embodiments assign the priority score to the vehicle and the co-located vehicles and the co-located vehicles and identify that the assigned priority score of the vehicle is higher than the co-located vehicles. Additionally, embodiments manage an operation of the co-located vehicles through a computing device within the co-located vehicles based on the smart contract rule and the priority score and create a priority lane for the vehicle by repositioning the co-located vehicles.

Abstract: The present inventive concept provides for a method of autonomous driving road space reservation and adaption. The method includes determining a target location of a first vehicle. Road space is reserved for the first vehicle at the target location. The reserved road space of the first vehicle is communicated to a second vehicle, and the driving plan of the second vehicle is adapted based on the communicated reserved road space of the first vehicle automatically before arrival.

Abstract: An embodiment for altering operational parameters of a machine in a multi-machine environment is provided. The embodiment may include receiving an IoT feed from one or more IoT devices and data relating to an activity in a multi-machine environment. The embodiment may also include identifying a health condition of one or more machines. The embodiment may further include in response to determining at least one machine of the one or more machines requires one or more maintenance actions, identifying a timeframe during which the one or more maintenance actions are able to be performed. The embodiment may also include updating a movement path of one or more service robots in the multi-machine environment. The embodiment may further include deploying the one or more service robots to execute the one or more maintenance actions. The embodiment may also include adapting one or more operational parameters of the one or more machines.

Abstract: A V2X computing system to manage air quality by reducing carbon emissions by changing a vehicle mode of operation from fuel to battery. The system identifies the position of the vehicle and changes the mode of the vehicle to a target battery-based vehicle. The system calculates how much aggregated emission can be allowed within a defined time range around a geo-fencing area to identify appropriate distribution of battery-operated vehicle and fossil fuel-based vehicle to ensure the required air-quality. The system leverages historical data around environmental parameters like wind direction, speed, etc. for a period to calculate the emission requirements vs. predicted emission. The system uses this data to dynamically switch vehicle from using fuel power to battery power based on the capability available within the vehicle for environmental sustainability. The system further spaces vehicles appropriately to ensure the air quality is maintained on the road in a geo-fenced area.

Abstract: A computer-implemented method to generate training data with increased fairness. The method includes identifying a set of training data comprising at least one independent variable and dependent variable. The method includes analyzing the set of training data to identify correlations between the independent and the dependent variables. The method further includes identifying at least one correlation between the one or more independent variable and the dependent variable. The method includes calculating a fairness score for each first independent variable against the dependent variable. The method further includes creating, based on the analyzing, a fairness profile for the set of training data. The method also includes generating, by a generative adversarial network (GAN) and based on the set of training data and the fairness profile, a set of synthetic training, where the GAN is configured to increases the fairness score for each variable with a disparate effect score above a threshold.

Abstract: Aspects of the present disclosure relate to collaborative rulesets for vehicles. A collaborative ruleset for a set of vehicles can be received, the collaborative ruleset defining relative positions each vehicle is required to maintain with respect to other vehicles within the set of vehicles. Sensor data indicating current positions of each vehicle within the set of vehicles while the set of vehicles are operating can be received. A command to display, on an augmented reality (AR) device of a user of a first vehicle within the set of vehicles, AR content for complying with the collaborative ruleset can be issued.

Abstract: A method, computer system, and a computer program product for sustainable power harvesting is provided. The present invention may include constructing a knowledge corpus using data received from a plurality of sources regarding electrical power harvesting from smart materials. The present invention may include determining one or more objects to be utilized for generating electrical power, wherein the one or more objects are comprised of at least one or more smart materials. The present invention may include generating printing instructions for the one or more objects to be executed by a three-dimensional (3D) printer. The present invention may include monitoring a performance of the one or more objects within an environment.

Abstract: A digital model is generated of a debris location where the digital model includes an augmented reality overlay of the debris location. Digital data from sensors at a debris field is received at a computer, and the digital data depicts debris in the debris field. Materials in the debris field are detected and identified based on the detected materials in the debris field. Layers of materials in the debris field are identified. A digital model is generated of the materials in the debris field including in the layers. Using the computer and an augmented reality (AR) device, an augmented reality overlay is generated based on the digital model of the materials in the debris fields. The augmented reality overlay is superimposed over the digital model of the materials in the debris field to indicate the materials in the debris field and the materials in the layers of the debris field.

Abstract: An embodiment for augmented reality (AR)-based visualization of an activity with collaboration amelioration is provided. The embodiment may include receiving real-time and historical data relating to an activity. The embodiment may also include identifying each step of the activity and a time to complete each step. The embodiment may further include executing a plurality of digital twin simulations of avatars of different types of workers performing each step of the activity. The embodiment may also include in response to determining a current distribution of human and robotic workers is not optimized, prompting a manager with an AR overlaid slider bar. The embodiment may further include generating a knowledge corpus including an optimized distribution. The embodiment may also include creating a visual animation of the optimized distribution. The embodiment may further include displaying the visual animation to at least one human worker via an AR device.

Abstract: Cropping volumetric media is provided. Received volumetric video data is represented by a Bloch sphere. A user selected sub-volume is received to which the volumetric video data is to be cropped. CNNs having different strides are applied to sub-spheres defined within the Bloch sphere. The CNNs generate a correlation score for each sub-sphere relative to a user specified parameter. Best rotation matrices for the sub-spheres are determined to achieve a user specified angle of view, and the sub-sphere correlation scores are optimized according to the best rotation matrices. Cylindrical weights are applied to the sub-spheres according to the optimized correlation scores, and a best solution is selected for the sub-volume according to the correlation scores. The rotation matrices are reflected orthogonally onto the sub-volume, and the sub-volume is cropped from the volumetric video according to the sub-sphere with the highest correlation score to create the cropped image.

Abstract: In an approach to improve risk assessment and management, embodiments monitor a predetermined area by collecting, by one or more sensing devices, data related to environmental conditions and spatial relationships between one or more objects in the predetermined area. Further, embodiments determine, based on a model and the monitoring, that an accidental event is likely to occur within a predetermined distance or within the predetermined area. Additionally, embodiments identify a predetermined mitigation action from a knowledge corpus to apply to the accidental event; and proactively implementing the identified mitigation action to prevent or manage the accidental event.

Abstract: According to one embodiment, a method, computer system, and computer program product for establishing access to vehicles is provided. The embodiment may include identifying at least two devices, including a requesting device and a target device. The embodiment may also include identifying one or more networks, including at least one alternative network. The embodiment may further include evaluating each network from the one or more networks to determine a best network. The embodiment may also include establishing access from the requesting device to the target device over the determined best network.

Abstract: According to one embodiment, a method, computer system, and computer program product for identifying induced deformation of a 3D object is provided. The embodiment may include receiving an unaltered three-dimensional (3D) rendering of an object and attribute information of the object. The embodiment may include identifying one or more influencing factors of forecasted local deformation of one or more portions of the 3D rendering based on the attribute information. The embodiment may include creating, via a generative adversarial network (GAN), a 3D rendering of the object showing the forecasted local deformation. The embodiment may include identifying induced deformation of one or more other portions of the 3D rendering caused by the forecasted local deformation. The embodiment may include creating, via the GAN, a 3D rendering of the object showing the identified induced deformation.

Abstract: Aspects of the present disclosure relate to extended reality (XR) device thermal load management. Thermal data associated with an XR device can be received. A determination can be made that a condition is met for offloading a thermal load of the XR device. One or more edge processing devices within the environment of the XR device can be identified. At least one edge processing device with sufficient computing resources for balancing the thermal load of the XR device can be selected. The XR device can be instructed to offload the thermal load to the selected at least one edge processing device.

Abstract: A computer-implemented method, a computer system and a computer program product adapt a vehicle communication network range based on an awareness of vehicle speed. The method includes identifying a plurality of devices within a recommended range of a vehicle. The method also includes obtaining a current driving environment from the plurality of devices. In addition, the method includes calculating a required range for a communications network based on the current driving environment and determining required devices within the required range. Lastly, the method includes dynamically creating the communications network when the required range is greater than the recommended range, where the communications network includes the vehicle, the plurality of devices within the recommended range and the required devices.

Abstract: A computer-implemented method, according to one approach, includes: sending one or more instructions to apply an initial influencing factor to smart materials of a 4D object. Moreover, the 4D object is configured to deliver one or more microparticles from a start location to a target location along a delivery path in response to the initial influencing factor being applied to the smart materials. One or more instructions to monitor movement of the 4D object along the delivery path in response to applying the initial influencing factor to the smart materials are also sent. In response to determining the 4D object has deviated from the delivery path, one or more instructions to use one or more machine learning models to dynamically weight the initial influencing factor applied to the smart materials are further sent.

Abstract: Aggregating worker skills and wearable robotic system capabilities is provided. Details of an activity that a worker is preparing to perform utilizing a wearable robotic system are retrieved. Skills of the worker related to the activity are retrieved. Capabilities of the wearable robotic system related to the activity are retrieved. An analysis of the details of the activity that the worker is preparing to perform utilizing the wearable robotic system, the skills of the worker, and the capabilities of the wearable robotic system is performed. An aggregation of the skills of the worker and the capabilities of the wearable robotic system to perform the activity is determined based on the analysis. It is determined that the worker can perform the activity utilizing the wearable robotic system based on the aggregation of the skills of the worker and the capabilities of the wearable robotic system.

Abstract: Described are techniques for appropriately gripping objects by robots. A target object (e.g., circuit board) is identified to be gripped by a robotic arm of a robot, such as a robot in an industrial facility. Upon identifying the target object to be gripped by the robotic arm, the attributes of the target object are determined. One or more pores of the robotic arm may then be selected to be enabled to secrete an adhesive based on the attributes of the target object. Furthermore, the adhesion level corresponding to the amount of the adhesive to be secreted by the selected pores of the robotic arm is determined based on the attributes of the target object. The selected one or more pores of the robotic arm are then activated to secrete the adhesive according to the adhesion level in order to appropriately grip the target object by the robotic arm.

Abstract: A computer-implemented method, according to one approach, includes: receiving a request to deliver one or more microparticles from a start location to a target location along a delivery path. Available characteristic data corresponding to the request to deliver the one or more microparticles is also obtained. The characteristic data corresponds to 4D objects capable of delivering microparticles, the one or more microparticles, the delivery path, and one or more ambient environments along the delivery path. Furthermore, one or more machine learning models are used to analyze the available characteristic data and determine a 4D object that is configured to deliver the one or more microparticles to the target location in response to an influencing factor being applied to the 4D object.