Abstract: Providing an activity for a participant may include receiving at least location data specifying a location of the participant. An engagement level of the participant may be predicted based on the location data. Sensor data associated with the participant may be received, the sensor data comprising at least current physiological data associated with the participant. Based at least on the predicted engagement level and the sensor data, an exercise for the participant to perform may be determined. A notification signal may be transmitted to the participant to perform the exercise.

Abstract: A method, computer program product, and a system where a processor(s), obtains pre-recorded visual data from a given location, captured by an image capture device at a visual input location at the given location. The processor(s) determines a position of the image capture device utilized to capture the visual data. The processor(s) obtains known landmarks from data related to the given location. The processor(s) analyzes the visual data to identify a portion of the known landmarks in the visual data, where the analyzing generates matched landmarks. The processor(s) determines a spatial orientation and positioning of the visual input location with respect to the matched landmarks, at the given location. The processor(s) generates an encryption key, utilizing the spatial orientation and the positioning of the visual input location with respect to the matched landmarks. The processor(s) encrypts a message with the encryption key, generating an encrypted message.

Abstract: Automatically capturing information and performing content searching may include extracting features from data content, for example, captured via an image capturing device or by another method. Features extracted from the data content are structured into an ontology graph representing keywords and contextual relationships. Search queries are generated based on the ontology graph, by inputting the ontology graph to a query generating machine learning model trained to predict one or more search queries. The search queries are executed and one or more search results are presented on a user interface, for example, a display device. Based on received feedback on the search results, the machine learning model is retrained.

Abstract: The present invention provides a method, a system, and a computer program product of directive controlled vehicles. In an exemplary embodiment, the system includes a plurality of computing systems comprising at least two vehicles, a directive source to transmit a directive to at least one of the plurality of computing systems, and a command source to issue at least one command to at least one vehicle of the at least two vehicles, wherein the at least one command controls a movement pattern and an operation of the at least one vehicle of the at least two vehicles based on the directive.

Abstract: A computer-implemented method for determining routes includes receiving a user's location and health measures, for a plurality of users, analyzing the plurality of users and their corresponding locations to determine health behaviors at a given location and time, receiving a request from a user for a route, developing a route to the user's destination from a current location to obtain a target health behavior within a given threshold or constraint based on the plurality of user's healthy behaviors, and presenting the a route on a computing device.

Abstract: A computer-implemented method includes determining a characteristic of a target audience for a viewing of a visual media, extracting a frame of the visual media from an electronic signal, identifying an object that is visible in the frame of the visual media, and digitally inserting an item of advertising content into the frame of the visual media, in a region of the object, wherein a selection of the item of advertising content has been optimized for at least the characteristic of the audience.

Abstract: A method includes registering a given client device with a server to receive personalized routing for a given user, building a user model for the given user, the user model being based on personal attributes for a plurality of users including the given user, identifying patterns of personal attributes for the given user, generating a personalized route for the given user based on matching the patterns of personal attributes with one or more route attributes, identifying one or more personalized incentives for the given user based on the personal attributes of the given user and the route attributes, modifying the personalized route for the given user to generate an incentivized personalized route for the given user, and transmitting a notification from the server to the given client device over a network, wherein the notification causes the given client device to display the incentivized personalized route for the given user.

Abstract: A method including: receiving physiological and external data of a user; predicting that the user is gravitating towards an undesirable mental state based on the physiological and external data; and providing the user with an ameliorative action in response to the prediction that the user is gravitating towards the undesirable mental state.

Abstract: Embodiments are directed to a computer-implemented method of creating a work. The method includes analyzing a set of media files. Thereafter, a set of metadata files is analyzed. Each metadata file is associated with a media file in the set of media files. A cognitive state of a user is estimated. Thereafter, the work is created from the set of media files based on the estimated cognitive state of the user.

Abstract: Embodiments are directed to a computer-implemented method of creating a work. The method includes analyzing a set of media files. Thereafter, a set of metadata files is analyzed. Each metadata file is associated with a media file in the set of media files. A cognitive state of a user is estimated. Thereafter, the work is created from the set of media files based on the estimated cognitive state of the user.

Abstract: A system to monitor visual health includes a processor operatively coupled to memory. The system further includes one or more subsystems configured to record data related to eye-health. The processor is configured to analyze the recorded data, detect a likelihood of eyestrain based on the analysis, and generate an alert to perform at least one action in response to the detection and based on the analysis.

Abstract: Providing heath activity for a participant in a conference call may include receiving data associated with the conference call and location data specifying a location of the participant conducting the conference call. An engagement level of the participant that is to participate in the conference call may be predicted based on the received data and the location data. Sensor data associated with the participant may be received, the sensor data comprising at least current physiological data associated with the participant. The participant's fitness goal may be identified. Based on the predicted engagement level, the sensor data and the participant's fitness goal, an exercise for the participant to perform during the conference call may be determined. A notification signal may be transmitted to the participant to perform the exercise.

Abstract: A method includes building a well-being profile for a given user based on data obtained from one or more sources associated with the given user. One or more personalized incentives for the given user are identified based on the well-being profile. A personalized route is generated based on the one or more identified personalized incentives, with the personalized route being designed to improve a well-being of the given user. A notification is transmitted to a given client device associated with the given user over a network, with the notification causing the given client device to display the personalized route.

Abstract: Embodiments are directed to a computer-implemented method of displaying a presentation. The method includes analyzing a set of media files that include the presentation. Thereafter, each media file is displayed in a predetermined order. Upon the detection of an audience viewing the media files, the displaying of the media files is adjusted based on characteristics of the audience.

Abstract: A system to monitor visual health includes a processor operatively coupled to memory. The system further includes one or more subsystems configured to record data related to eye-health. The processor is configured to analyze the recorded data, detect a likelihood of eyestrain based on the analysis, and generate an alert to perform at least one action in response to the detection and based on the analysis.

Abstract: A reality augmenting computer-implemented method, system, and computer program product, includes detecting a consumer and at least one of a product and a location, determining a current sensory state of the consumer, calculating a desired sensory state to achieve a target mood based on a correlation between the target mood and a user model, and executing an action according to the desired sensory state by a wearable to change the current sensory state of the consumer to the target mood.

Abstract: A display control method, system, and non-transitory computer readable medium for a digital billboard display, include an attribute identification circuit configured to identify attributes of each user of a group of users viewing the digital billboard display, a content determining circuit configured to determine a content type to be displayed on the digital billboard based on an aggregation of all of the attributes of the group of users identified by the attribute identification circuit, and a display augmenting circuit configured to deliver the content type to the digital billboard display.

Abstract: Automatically capturing information and performing content searching may include extracting features from data content, for example, captured via an image capturing device or by another method. Features extracted from the data content are structured into an ontology graph representing keywords and contextual relationships. Search queries are generated based on the ontology graph, by inputting the ontology graph to a query generating machine learning model trained to predict one or more search queries. The search queries are executed and one or more search results are presented on a user interface, for example, a display device. Based on received feedback on the search results, the machine learning model is retrained.

Abstract: A method for a cloud-based feedback-driven image training and recognition includes receiving a set of expert annotations of a plurality of training images of a predetermined subject matter, wherein the expert annotations include a clinical diagnosis for each image or region of interest in an image, training one or more classification models from the set of expert annotations, testing the one or more classification models on a plurality of test images that are different from the training images, wherein each classification model yields a clinical diagnosis for each image and a confidence score for that diagnosis, and receiving expert classification result feedback regarding the clinical diagnosis for each image and a confidence score yielded by each classification model.

Abstract: A method includes registering a given client device with a server to receive personalized routing for a given user, building a user model for the given user, the user model being based on personal attributes for a plurality of users including the given user, identifying patterns of personal attributes for the given user, generating a personalized route for the given user based on matching the patterns of personal attributes with one or more route attributes, identifying one or more personalized incentives for the given user based on the personal attributes of the given user and the route attributes, modifying the personalized route for the given user to generate an incentivized personalized route for the given user, and transmitting a notification from the server to the given client device over a network, wherein the notification causes the given client device to display the incentivized personalized route for the given user.