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: According to one embodiment, a method, computer system, and computer program product for creating virtual boundaries is provided. The present invention may include creating a virtual simulation of a physical space and of one or more workers and/or one or more machines and/or objects in the physical space; determining mobility boundaries required for performance of one or more activities; personalizing virtual boundaries for the one or more workers to perform the one or more activities based on the determined mobility boundaries; and displaying the virtual boundaries to the one or more workers depending on the one or more activities the worker is performing.

Abstract: In an approach to improve improving impact prevention in both manual and autonomous vehicles embodiments of the present invention generate a knowledge corpus based on data collected, from one or more internet of thing (IoT) sensors, associated with one or more predetermined risk factors of one or more predefined risks over time. Further, embodiments receive from the one or more IoT sensors input data to observe a vertical space above a vehicle and identify an object in a predetermined area based on the received input data and the knowledge corpus. Additionally, utilize the knowledge corpus and the input data to generate a risk score for the identified object and responsive to the risk score being above a predetermined threshold, embodiments issue a command for the vehicle to continue to drive or to progress to a predetermined safe zone.

Abstract: A method for cast based hybrid additive manufacturing includes receiving a three-dimensional digital model file for construction of an object utilizing an additive manufacturing device. The method also includes receiving one or more additional requirements for the object and identifying, based on the three-dimensional digital model file and the one or more additional requirements for the object, a cast for the three-dimensional digital model file for integration into hybrid additive manufacturing of the object. The method also includes instructing, a secondary manufacturing device, to dispose the cast at a position with respect to a partially constructed object by the additive manufacturing device. The method also includes resuming the hybrid additive manufacturing of the partially constructed object with the cast until the construction of the object is complete.

Abstract: In an approach to improve additive manufacturing embodiments receive, by a sensor set, data associated with an object or a predetermined area, and retrieve, by a knowledge corpus, historic data associated with the object or the predetermined area. Further, embodiments identify a defect on or within an object based on an identified difference in the received data and the historic data and identify, by the sensor set, a target area on the object to repair the defect. Additionally, embodiments, create, by a context-aware robotic system, a physical support around the target area, and repair, by an additive manufacturing mechanism and the physical support, the defect by applying three-dimensional printing-based rectification to the defect.

Abstract: A computer-implemented method, a computer system and a computer program product predict and project vehicle movements in an augmented reality (AR) environment. The method includes obtaining telemetry data from a vehicle in an environment, where the telemetry data is selected from a group consisting of: video data, audio data and text data. The method also includes determining a path for the vehicle based on the telemetry data. The method further includes identifying an augmented reality device in the path, where the augmented reality device is associated with a user proximate to the path. Lastly, the method includes displaying the path using the augmented reality device in the augmented reality (AR) environment.

Abstract: A method for boundary based edge device compliance includes receiving a request to process data and identifying a cluster of edge devices to process the data located within a boundary area. The method includes applying compliance rules to the cluster of edge devices and instructing the cluster of edge devices to perform computations while adhering to the compliance rules associated with the boundary area. In response to determining that a first edge device from the cluster of edge devices is relocating outside of the boundary area, the method includes instructing the first edge device to transfer data to a second edge device from the cluster of edge devices prior to crossing the boundary to adhere to the compliance rules.

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: A computer-implemented method for augmentation and printing of a three-dimensional (3D) object is provided. The computer-implemented method includes analyzing a model of the 3D object, information of sensors for deployment on the 3D object and environmental parameters of a location where the 3D object is deployable and determining, from results of the analyzing, a surface contour of the 3D object, power requirements of the sensors and power levels that can be generated at the location by algae-based power generation. The computer-implemented method further includes augmenting the model with microfluidic circuitry models for supporting the algae-based power generation on the surface contour to meet the power requirements to an extent possible given the power levels, printing the 3D object and microfluidic circuitry according to the model and the microfluidic circuitry models and supplying the microfluidic circuitry with algae for the algae-based power generation.

Abstract: Aspects of the present disclosure relate to augmented reality (AR) measurement display. A measurement of a quantity in an environment of a user currently using an AR device can be received. A preferred unit of measurement (UoM) for the measurement of the quantity can be selected based on an analysis of historical data of the user. The measurement of the quantity can be conceptualized by obtaining a virtual object associated with the measurement of the quantity. A command to display, on the AR device, the measurement of the quantity within the preferred UoM and the virtual object associated with the measurement of the quantity can be issued.

Abstract: Images placed in documents are enhanced based on the context in which the image is used. Context is determined according to document-specific indicators such as nearby text, headings, titles, and tables of content. A generative adversarial network (GAN) modifies the image according to the context to selectively emphasize relevant components of the image, which may include erasing or deleting irrelevant components. Relevant general-purpose images may be retrieved for use in the document and may be selectively enhanced according to usage of the general-purpose image in a given document.

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: A computer-implemented method, system and computer program product for transporting items from one location to another location, such as in a warehouse. A model is built and trained to determine an optimal movement path for transporting items using mobile robots either individually or in cooperation with other mobile robots. After training the model to determine an optimal movement path for transporting items, simulations of mobile robots transporting items from a source location to a target location using various movement paths are performed. An optimal movement path for transporting such items from the source location to the target location is identified using the trained model based on the simulated movement paths, the historical times for the movement of the items using various movement paths, the number of items to be transported and the properties of the items. Available mobile robots are then organized to implement the identified optimal movement path.

Abstract: A method, system and apparatus to generate an augmented voice command, including identifying a plurality of sounds from a respective plurality of transducers to a smart speaker device, generating a visualization of the sounds using an augmented reality device, wherein one or more of the sounds can be selected using the visualization, and generating the augmented voice command for the smart speaker device, wherein the augmented voice command comprises the one or more sounds selected using the visualization of the augmented reality device.

Abstract: Embodiments of the invention are directed to a computer-implemented method. A non-limiting example of the computer-implemented method includes accessing, using a processor system, a segmented three-dimensional (3D) model of a 3D physical object, the segmented 3D model including a plurality of 3D model segments. Instructions of a first 3D model segment of the plurality of 3D model segments control a first printhead of a multiple-printhead (MPH) 3D printer to print a first segment of the 3D physical object on a first print base of the MPH 3D printer. Instructions of a second 3D model segment of the plurality of 3D model segments control a second printhead of the MPH 3D printer to print a second segment of the 3D physical object on a second print base of the MPH 3D printer.

Abstract: A computer-implemented method, a computer system and a computer program product automatically generate product videos based on requested feature sets in stored data. the method includes acquiring a plurality of product features from a server, where each product feature in the plurality of product features is associated with data selected from a group consisting of: text data, audio data, and image data. The method also includes receiving a request for a product video, where a product in the product video comprises a set of product features in the plurality of product features. The method further includes identifying the data associated with each product feature in the set of product features for the request. Lastly, the method includes generating the product video based on identified data for the product.

Abstract: According to one embodiment, a method, computer system, and computer program product for activity progress validation is provided. The embodiment may include capturing user movements through one or more IoT devices. The embodiment may also include identifying an activity associated with the captured user movements. The embodiment may further include identifying performance requirements related to the identified activity. The embodiment may also include calculating a quality level metric and a progress-toward-completion metric of the activity based on the performance requirements. The embodiment may further include displaying each metric on a graphical user interface associated with a user device.

Abstract: Provided is a computer-implemented method, system, and computer program product for displaying information to a pedestrian using a visual indicator. A processor may detect that a vehicle is approaching a pedestrian. The processor may determine that the pedestrian is unable to see the approaching vehicle. The processor may display an indication that the vehicle is approaching the pedestrian on an object the pedestrian can currently view.

Abstract: Computer-implemented methods for dynamic sensor printing and deployment. Aspects include receiving, from one or more symptom tracking sensors disposed on an apparatus, data regarding a condition of the apparatus and analyzing the data regarding the condition of the apparatus. Aspects also include determining, based on the analysis, one or more required additional measurements of the apparatus and creating, by a three-dimensional printer, one or more sensors configured to measure the one or more required additional measurements. Aspects further include placing the one or more sensors on the apparatus.

Abstract: According to one embodiment, a method, computer system, and computer program product for wearable device activity analysis is provided. A computer receives a video of an activity. The computer identifies the activity based on analyzing the video. The computer identifies body movements from the video. The computer correlates the activity and the body movements to a wearable device. The computer identifies additional inputs for the activity and updates the wearable device based on the identified additional inputs.