Abstract: Aspects of the present invention disclose a method for routing one or more autonomous vehicles to minimize a density of autonomous vehicles and passengers passing through network areas with oversubscribed bandwidth. The method includes one or more processors determining a bandwidth requirement of a first autonomous vehicle. The method further includes determining respective bandwidth requirement for one or more additional autonomous vehicles utilizing a wireless network. The method further includes determining a total bandwidth capacity of one or more nodes of the wireless network. The method further includes determining routing instructions from a current location of the first autonomous vehicle to a destination of the first autonomous vehicle based at least in part on the bandwidth requirement of the first autonomous vehicle and the total bandwidth capacity of the one or more nodes of the wireless network.

Abstract: In an approach to resource monitoring and allocation recommendation, a computer determines a work activity for a risk assessment. A computer determines one or more resources assigned to the work activity. A computer determines one or more current activities associated with the one or more resources assigned to the work activity. Based on the one or more resources assigned to the work activity and on the one or more current activities associated with the one or more resources assigned to the work activity, a computer determines a confidence level associated with successful completion of the work activity. A computer determines the confidence level does not exceed a pre-defined threshold. A computer determines one or more resource scenarios to improve the confidence level. A computer ranks the one or more resource scenarios. A computer generates a resource allocation recommendation based on the ranked one or more resource scenarios.

Abstract: One example of a computer-implemented method comprises receiving content data for a first physical note removably attached to a first display area of a first collaborative board located in a first location. The content data includes information displayed on the first physical note. The method further comprises determining a position of the first physical note on the first collaborative board; and outputting instructions to a second collaborative board located in a second location to generate a first virtual note in a second display area of the second collaborative board such that information displayed on the first virtual note corresponds to the information displayed on the first physical note and a position of the first virtual note on the second display area corresponds to the position of the first physical note on the first collaborative board.

Abstract: An apparatus for an mentor and expertise matching includes a profile module configured to populate a mentee profile in response to receiving information from the mentee. The mentee profile includes information about skills and preferences of the mentee. A scoring module compares information from the mentee profile with a plurality of mentor profiles from a mentor database to determine, using a mentor scoring algorithm, a mentor score for each of the plurality of mentor profiles. A selection module is configured to receive a mentee selection of a mentor from one or more mentors presented to the mentee. Each of the mentors presented to the mentee includes a higher mentor score than other mentors. A mentorship tracking module is configured to track interactions between the mentor and the mentee, and a mentor feedback module is configured to update a mentor profile of the mentor based on feedback from the interactions.

Abstract: Embodiments relate to a system, program product, and method for managing apparel to facilitate compliance through a cognitive system, i.e., using an artificial intelligence (AI) platform to dynamically analyze the apparel donned by individuals to determine compliance with established apparel compliance practices and provide suggestions for overcoming non-compliance. The determinations of non-compliance are accompanied with respective risk factors. The system, program product, and method disclosed herein facilitate leveraging written requirements processed by natural language processing (NLP) for the donning of apparel that includes proper clothing articles and accessories, as well as associated requirements of clothing articles and accessories that are not appropriate for the respective conditions.

Abstract: A method, computer program product, and a system where a processor(s) ingests content from a source(s) with an attribute(s) comprising a verified temporal context(s) of the source(s). The processor(s) cognitively analyzes the content, by applying an entity recognition algorithm(s) to identify and extract entities in the source(s). The processor(s) classifies each extracted entity into a given grouping from a plurality of groupings based on at least one attribute comprising the verified temporal context of the source from which the extracted entity was extracted. The processor(s) generates a corpus comprising the groupings; each grouping comprises extracted entities with verified temporal contexts consistent with a defined time period.

Abstract: Data-analysis-based processing is provided to validate audio content delivery via embedded inaudible sound signals. The processing obtains, by a validation system, an indication of detection of an inaudible sound signal embedded in an audio output of provided content initiated by a user on a user-device. The inaudible sound signal is inaudible to the user, and the audio output is from the user-device. Based on obtaining the indication of detection of the inaudible sound signal embedded in the audio output, the validation system validates that the audio output of the provided content is ON with respect to the user-device.

Abstract: Systems, methods, devices, and non-transitory media of the various embodiments may provide for managing data quality anomalies in an enterprise system. Various embodiments may enable one or more network computing device to identify control points for monitoring data sets in the enterprise system, track data quality metrics using at least one threshold for each of the identified control points, determine whether a data quality anomaly is detected, and classify a review priority in response to determining that a data quality anomaly is detected.

Abstract: Embodiments of the invention present invention provide an approach for governing Internet of Things (IoT) device operation. Specifically, the present invention relates to a method and system for utilizing digital twin-based simulation to selectively govern capabilities of surrounding IoT devices to improve a user experience.

Abstract: A method, computer program product, and a system where a processor(s) obtains data related to physical activities performed by an individual from a sensor(s) proximate to the individual. The processor(s) cognitively analyzes the data to identify baseline behavioral patterns of the individual, when the individual is engaged in each of the physical activities. The processor(s) obtains data indicating consumption of a substance by the individual at a first time. The processor(s) determines impacts of the consumption on the baseline behavioral patterns of the individual and generates a data structure (a predictive model) that includes expected deviations from the baseline behavioral patterns of the individual, when the individual has consumed the substance.

Abstract: In an approach to facilitating data transmission utilizing peer-to-peer communications and wireless ad hoc networks, one or more computer processors detect one or more data transmission failures. The one or more computer processors rank the one or more detected data transmission failures. The one or more computer processors detect one or more subsequent devices. The one or more computer processors determine one or more statuses associated with the detected one or more subsequent devices. The one or more computer processors the one or more detected subsequent devices based on the determined the determined statuses. The one or more computer processors match the one or more ranked data transmission failures with the one or more ranked subsequent devices. The one or more computer processors transmit the one or more data transmission failures with one or more matched subsequent devices.

Abstract: Aspects of the present invention disclose a method for recommending an activity based on a social media profile, IoT devices, and historical engagements of the user. The method includes one or more processors determining a past activity of a user based at least in part on social media posts and internet of things (IoT) enabled devices of the user. The method further includes determining a set of historical conditions corresponding to the past activity, wherein the set of conditions correspond to a positive sentiment of the user. The method further includes identifying a location of the user. The method further includes generating an activity recommendation based on the location of the user and the set of historical conditions corresponding to the past activity, wherein the activity recommendation includes a set of future conditions of a future activity, wherein the set of future conditions correlate with the set of historical conditions.

Abstract: A computer-implemented method prevents physical interference between co-located users in virtual environments. The method includes identifying a first user associated with a first virtual reality (VR) system and a second user associated with a second VR system. The method also includes predicting a future movement of the first user to perform a first task in a primary virtual environment. The method further includes identifying, in response to the predicting the future movement of the first user, a first physical space needed for the first user. The method includes determining, in response to identifying the first physical space, a likely interference in a first physical location of the first user. The method also includes preventing the likely interference.

Abstract: One or more computer processors generate a network fractal based on one or more predicted network conditions for a network that includes a change in user density, user device latency, and network throughput, wherein the network fractal is a deployment template comprised of a plurality of nodes. The one or more computer processors select a configuration of network infrastructure devices placed at each node in the plurality of nodes comprised in the generated network fractal. The one or more computer processors modify the network utilizing the generated network fractal and the selected configuration of network infrastructure devices. The one or more computer processors deploy the modified network.

Abstract: A computer-implemented method includes: receiving, by a computer device, preference information from a plurality of people, the preference information including an individual level of preference for various activities for each of the people; receiving, by the computer device, biometric data of the people, the biometric data relating to the various activities; building, by the computer device, a corpus of relationships between the preference information and the biometric data; receiving, by the computer device, biometric data of a user; and predicting, by the computer device, a user level of preference with a particular activity of the various activities, the predicting being based on a comparison of the biometric data of the user and the biometric data of the people who participated in the particular activity.

Abstract: In an embodiment, a correlated forecast is computer generated by a processor that receives input data for historic values of a first input variable, creates forecast data for future values of the first input variable using the historic values of the first input variable, generates diagnostic data based on a diagnostic analysis of the forecast data, creates a first diagnostic variable that includes a first diagnostic value from a first cognitive process, generates a feature vector based on a second cognitive process that determines the feature vector by identifying a correlation between the first diagnostic variable and a second diagnostic variable, and generates a final forecast using the feature vector as an input for a cognitive forecasting process, where the first cognitive process determines the first diagnostic value based on the diagnostic data.

Abstract: Techniques are described with respect to facilitating client ergonomic support. An associated method includes receiving a plurality of posture datapoints associated with multiple clients and constructing a machine learning knowledge model based upon the plurality of posture datapoints in order to identify a plurality of predefined ergonomic support design elements. The method further includes receiving client-specific posture datapoints associated with a first client and analyzing, via the machine learning knowledge model, the client-specific posture datapoints in view of the plurality of posture datapoints in order to select an initial ergonomic support design element among the plurality of predefined ergonomic support design elements. The method further includes facilitate printing of the initial ergonomic support design element for a seat component associated with the first client.

Abstract: A system including sensors configured to provide physiological markers of a developer and a controller configured provide information indicative of a user experience to the developer while receive signals from the sensors. The controller is configured to utilize cognitive analysis determine developer emotion responses as the developer receives the user experience. The controller compares a developer emotion classification with a user emotion classification of a user as the user generated the user experience. The system generates a prioritized backlog to identify points where emotion responses between user and developer are in common, or where emotion responses between user and developer differ.

Abstract: In an approach for derivation of progressively variant dark data utility for legacy system candidate microservices, a processor analyzes a variability of data stored in a legacy system for a plurality of data metrics. A processor measures, for each data metric, a utility of the data using an intra-analysis and a meta-analysis. A processor correlates the plurality of data metrics to candidate microservices. A processor generates insights for the candidate microservices based on the utility of the data.

Abstract: Aspects of the present disclosure relate to context based saving of content. A set of conditions for automatically saving content for a user currently engaged with savable content can be received. A current context of the user currently engaged with savable content can be determined. The current context of the user can be compared to the set of conditions to determine whether automatically saving the savable content should be completed. The savable content can be automatically saved in response to determining that automatically saving the savable content should be completed.