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 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 computer-implemented method, system and computer program product for efficient resource utilization. A workflow of manufacturing a product using various machines at each plant of an organization is created, where the workflow illustrates which machines are utilized to produce the product using one or more raw materials. A production rate for the product at each plant manufacturing the product is predicted based on the workflow. An amount of a raw material required by a first plant to produce the product is determined based on the predicted production rate for the product at the first plant. An amount of the raw material is then routed to the first plant from one or more other plants based on minimizing the system inventory carrying cost and minimizing the system transportation cost if the first plant needs an additional amount of the raw material to realize the predicted production rate for the product.

Abstract: According to one embodiment, a method, computer system, and computer program product for eSIM configuration. The embodiment may include identifying contextual information of an internet-based activity being performed via a mobile device. The contextual information comprises one or more minimum performance requirements. The embodiment may include identifying a Wi-Fi network in use for performance of the internet-based activity. The embodiment may include evaluating the performance of the internet-based activity on the Wi-Fi network in use. In response to determining a deviation from the one or more minimum performance requirements, the embodiment may include reconfiguring an eSIM of the mobile device to compensate for the deviation.

Abstract: Computer technology that receives a query and a desired level of precision and/or accuracy (herein, a “p/a value”) associated with the received query, determines whether the p/a value exceeds a predetermined threshold, if the p/a value exceeds the predetermined threshold, then the virtual assistant system applies digital twin simulation to a digital twin data set in determining the query response to improve precision and/or accuracy of the query response, and outputs the query response to the querying party (for example, output as sound data in a voice assistant system). If the p/a value is below the threshold value, then the digital twin simulation is not performed, which makes the response quicker and puts less computational power demands on the virtual assistant system. In some embodiments, the virtual assistant system calculates the p/a value based on context.

Abstract: According to one embodiment, a method, computer system, and computer program product for light-based navigation of robotic device. The embodiment may include detecting a light beam. The embodiment may include identifying a source location and an endpoint location of the light beam. The endpoint location comprises a location where the light beam intersects a surface. The embodiment may include receiving a voice command to proceed to the endpoint location. The embodiment may include instructing a mobile robotic device to proceed directly to the endpoint location. In response to the mobile robotic device reaching the endpoint location, the embodiment may include instructing the mobile robotic device to perform an activity therein.

Abstract: According to one embodiment, a method, computer system, and computer program product for solar power generation is provided. The embodiment may include identifying relative positions of co-located electric autonomous vehicles (EAVs) within a group. The embodiment may include identifying solar power generation metrics for each EAV. The embodiment may include determining whether at least two EAVs have a same side unexposed to direct sunlight. In response to determining at least two EAVs have a same side unexposed to direct sunlight, the embodiment may include identifying a direction and an angle of solar light impacting the group. Based on the relative positions and the direction and angle of solar light, the embodiment may include instructing a collaborative movement among the group such that solar light is reflected from an exterior surface of at least one EAV to an exterior surface of at least one other EAV which was unexposed to sunlight.

Abstract: A processor may receive sound data associated with a bounded environment. The sound data may be associated the sound data is associated with a sound field. The processor may analyze the sound data associated with the sound field to identify one or more external sound sources and one or more internal sound sources. The processor may generate one or more simulations of the sound field based, at least in part, on a user preference set. The processor may modify a sound field within the bounded environment. The modified sound field may be based, at least in part, on the one or more simulations of the sound field and the user preference set.

Abstract: According to one embodiment, a method, computer system, and computer program product for solar power generation is provided. The embodiment may include identifying relative positions of co-located electric autonomous vehicles (EAVs) within a group. The embodiment may include identifying solar power generation metrics for each EAV. The embodiment may include determining whether at least two EAVs have a same side unexposed to direct sunlight. In response to determining at least two EAVs have a same side unexposed to direct sunlight, the embodiment may include identifying a direction and an angle of solar light impacting the group. Based on the relative positions and the direction and angle of solar light, the embodiment may include instructing a collaborative movement among the group such that solar light is reflected from an exterior surface of at least one EAV to an exterior surface of at least one other EAV which was unexposed to sunlight.

Abstract: A computer implemented system is used to implement a “roadside delivery” (see definition, herein). These deliveries involve two vehicles (for example, trucks, unmanned aerial vehicles). One vehicle delivers a Product (see definition, herein) from the supplier side. The other vehicle is the customer's vehicle, which receives the roadside delivery of the Product pursuant to the time and location scheduled through a computer network.

Abstract: A computer system provides, via a network, information to an employment candidate regarding an available job, including a description of the job and questions for the candidate, wherein the information is configured for presentation on a device used by the candidate. The computer system receives from the device via the network and in response to the information being presented to the candidate, answers of the candidate and inputs indicating actions of the candidate other than the answers. The computer system determines, responsive to the inputs, a metric indicating an evaluation of the candidate.

Abstract: A computer system provides, via a network, information to an employment candidate regarding an available job, including a description of the job and questions for the candidate, wherein the information is configured for presentation on a device used by the candidate. The computer system receives from the device via the network and in response to the information being presented to the candidate, answers of the candidate and inputs indicating actions of the candidate other than the answers. The computer system determines, responsive to the inputs, a metric indicating an evaluation of the candidate.