Abstract: An example operation may include one or more of ingesting data records from a plurality of external data sources via a plurality of API calls, generating a plurality of digital footprints for a plurality of users, respectively, which have access to a common finite space, wherein each digital footprint includes a respective health value of a respective user generated based on ingested data records of the user, identifying a user from among the plurality of users which is about to enter the common finite space, in response to identifying the user, determining a cumulative safety value for the common finite space based on the digital footprint of the identified user and a digital footprint of one or more other users already present within the common finite space, and transmitting an alert to a computing system based on the determined cumulative safety value for the common finite space.

Abstract: An embodiment for recommending routes in an enhanced navigation system is provided. The embodiment may include receiving a destination from a primary user. The embodiment may also include obtaining a tentative list of routes. The embodiment may further include identifying each user and characteristics associated with each user. The embodiment may also include analyzing current conditions of the tentative list of routes and the characteristics. The embodiment may further include identifying one or more optimal routes. The embodiment may also include recommending the one or more optimal routes to the primary user. The embodiment may further include in response to determining the primary user selects an optimal route of the one or more optimal routes, presenting the selected optimal route on a navigation display to the primary user.

Abstract: An embodiment for recommending routes in an enhanced navigation system is provided. The embodiment may include receiving a destination from a primary user. The embodiment may also include obtaining a tentative list of routes. The embodiment may further include identifying each user and characteristics associated with each user. The embodiment may also include analyzing current conditions of the tentative list of routes and the characteristics. The embodiment may further include identifying one or more optimal routes. The embodiment may also include recommending the one or more optimal routes to the primary user. The embodiment may further include in response to determining the primary user selects an optimal route of the one or more optimal routes, presenting the selected optimal route on a navigation display to the primary user.

Abstract: An embodiment of the invention may include a method, computer program product and computer system for object detection and identification. The method, computer program product and computer system may include computing device which may receive an image from a user device. The image may be a screenshot captured by the user device from a display. The computing device may classify the image based on features present in the image and detect a salient object contained within the image. The computing device may identify the object in the image and one or more sources of the object in the image.

Abstract: An embodiment of the invention may include a method, computer program product and computer system for object detection and identification. The method, computer program product and computer system may include computing device which may receive an image from a user device. The image may be a screenshot captured by the user device from a display. The computing device may classify the image based on features present in the image and detect a salient object contained within the image. The computing device may identify the object in the image and one or more sources of the object in the image.

Abstract: A tool for providing a version controller bulletin. The tool retrieves metadata from a plurality of version controller repositories in a development environment. The tool creates one or more snapshots for the metadata over a pre-determined period of time, wherein the pre-determined period of time includes a start time and an end time. The tool determines a metadata difference between non-code related issue clusters of the one or more snapshots. The tool determines a confidence to conflict value and a line of code range for code related issue clusters of the one or more snapshots, wherein the confidence to conflict value represents a probability of a merge conflict. The tool provides respective heat maps for code related issue clusters and non-code related issue clusters. The tool outputs to a version controller bulletin, the metadata difference, the confidence to conflict value, respective heat maps, and the line of code range.

Abstract: Embodiments for generating recommendations for user activity onboard a vehicle are provided. A first user and a second user onboard a vehicle are identified. A relationship between the first user and the second user is determined based on at least one information source associated with at least one of the first user and the second user. A traffic condition associated with the vehicle traveling to a destination is detected. A recommendation of an joint activity for the first user and the second user while onboard the vehicle is generated based on the determined relationship between the first user and the second user, the detected traffic condition, and the at least one information source.

Abstract: An approach is provided that trains an artificial intelligence system to understand user preferences with least some of these preferences being learned from social media data pertaining to the user. The approach identifies points of interest between a starting location and a planned destination. The identification is performed while the user is traveling by automobile to the planned destination. The planned destination is included in an itinerary. The approach calculates an affinity score between the points of interest and the user preferences and recommends a set of points of interest based on the calculated affinity scores. A selection is received from the user of one of the points of interest from the recommended set. The itinerary is updated to include traveling to the selected point of interest and the user is provided with a set of driving instructions according to the updated itinerary.

Abstract: Embodiments for generating recommendations for user activity onboard a vehicle are provided. A first user and a second user onboard a vehicle are identified. A relationship between the first user and the second user is determined based on at least one information source associated with at least one of the first user and the second user. A traffic condition associated with the vehicle traveling to a destination is detected. A recommendation of an joint activity for the first user and the second user while onboard the vehicle is generated based on the determined relationship between the first user and the second user, the detected traffic condition, and the at least one information source.

Abstract: An embodiment of the invention may include a method, computer program product and computer system for object detection and identification. The method, computer program product and computer system may include computing device which may receive an image from a user device. The image may be a screenshot captured by the user device from a display. The computing device may classify the image based on features present in the image and detect a salient object contained within the image. The computing device may identify the object in the image and one or more sources of the object in the image.

Abstract: An embodiment of the invention may include a method, computer program product and computer system for object detection and identification. The method, computer program product and computer system may include computing device which may receive an image from a user device. The image may be a screenshot captured by the user device from a display. The computing device may classify the image based on features present in the image and detect a salient object contained within the image. The computing device may identify the object in the image and one or more sources of the object in the image.