Abstract: Approaches presented herein enable cognitive oral health management. Specifically, data from at least one internet of things (IoT) sensor and data from at least one visual image sensor are collected over time for a user via one or more sensors operatively coupled with one or more personal daily oral care devices as the user is performing a periodic oral care activity with the one or more personal daily oral care devices. Collected data are subjected to cognitive diagnostics to identify abnormalities in a user's oral healthcare regimen and physiological abnormalities within the oral cavity by categorizing data. A report for a medical professional may be generated providing recommendation of potential diagnoses and treatment options.

Abstract: A computer implemented navigation method that provides a safest route by considering manual driver risk. The method may include providing at least two sets of directions from a user start location to a final user location based on a user navigation system and user permission for data access; and ranking said at least two sets of directions by a baseline safety value. The method may also include determining in real time travelers that are present on passageways for the at least two sets of directions; and ranking the travelers according to travel risk behavior. Finally, the method may assign an aggregate risk score to each passageway for the at least two sets of directions for each passageway specific grouping of the travels having the ranked travel risk behavior to provide a safety ranked set of the at least two sets directions to the final user location.

Abstract: Approaches presented herein enable cognitive oral health management. Specifically, data from at least one internet of things (IoT) sensor and data from at least one visual image sensor are collected over time for a user via one or more sensors operatively coupled with one or more personal daily oral care devices as the user is performing a periodic oral care activity with the one or more personal daily oral care devices. Collected data are subjected to cognitive diagnostics to identify abnormalities in a user's oral healthcare regimen and physiological abnormalities within the oral cavity by categorizing data. A report for a medical professional may be generated providing recommendation of potential diagnoses and treatment options.

Abstract: A method, system and computer-usable medium are disclosed for autonomous vehicle (AV) behavior synchronization. The AV driving pattern is adjusted to facilitate an occupant's satisfaction by receiving information as to person to form a driving history. The driving history is analyzed to identify preferences and patterns. Based on the driving history a driving preference model is formed for the person. AV driving algorithm(s) are adjusted based on the driving preference model for the person when the person is an occupant of the AV.

Abstract: A computer system monitors food preparation. Images of food preparation by a user are captured via one or more image capture devices disposed within an area containing food preparation items. A food preparation process being performed by the user is determined. Image processing is performed on the captured images to monitor the food preparation process and detect an event. The user is notified of the detected event, and provided information pertaining to the event. Embodiments of the present invention further include a method and program product for monitoring food preparation in substantially the same manner described above.

Abstract: A method includes: determining, by a computer device, conditions along a predefined driving route of a vehicle; determining, by the computer device and based on the conditions, risk factors of segments of the driving route; determining, by the computer device, an optimal one of the segments for switching the vehicle from autonomous driving mode to manual driving mode; and outputting, by the computer device, data defining the determined optimal one of the segments.

Abstract: Data regarding actions of a population of one or more persons may be received from a plurality of sensors. A baseline of behavior of the population may be determined using the data. Additional data regarding actions of an identified person may be received from one or more of the plurality of sensors. It may be determined that an amount of deviation between the actions of the identified person and the baseline of behavior exceeds a threshold deviation using the additional data. A notification for the identified person relating to the deviation may be generated in response to determining that the amount of deviation is above the threshold deviation.

Abstract: The present disclosure includes customizing responses by an Artificial Intelligence (AI) system using a response mode for interaction with a user. A question or command is received at an AI system from an associated AI device which receives the question or command from an initiating user of a plurality of users in a vicinity of the AI device. A preference of an interaction mode for the initiating user is determined, and the preferred interaction mode is determined using a knowledge corpus. An answer to the question or command using the AI system is generated. Using the AI device, a communication to the initiating user which includes the answer is initiated, via a communication mode based on the interaction mode preference of the initiating user.

Abstract: Data regarding actions of a population of one or more persons may be received from a plurality of sensors. A baseline of behavior of the population may be determined using the data. Additional data regarding actions of an identified person may be received from one or more of the plurality of sensors. It may be determined that an amount of deviation between the actions of the identified person and the baseline of behavior exceeds a threshold deviation using the additional data. A notification for the identified person relating to the deviation may be generated in response to determining that the amount of deviation is above the threshold deviation.

Abstract: Approaches presented herein enable performing an oral health diagnosis of a user using an oral monitoring device fixed in the oral cavity. Specifically, an oral monitoring device collects jaw movement data as a user goes about daily living. An oral healthcare analysis is performed comparing current measurement data against abnormality classifications to identify abnormal jaw movement. If an abnormality is identified, an oral healthcare professional can be notified.

Abstract: A computer implemented navigation method that provides a safest route by considering manual driver risk. The method may include providing at least two sets of directions from a user start location to a final user location based on a user navigation system and user permission for data access; and ranking said at least two sets of directions by a baseline safety value. The method may also include determining in real time travelers that are present on passageways for the at least two sets of directions; and ranking the travelers according to travel risk behavior. Finally, the method may assign an aggregate risk score to each passageway for the at least two sets of directions for each passageway specific grouping of the travels having the ranked travel risk behavior to provide a safety ranked set of the at least two sets directions to the final user location.

Abstract: A method includes: determining, by a computer device, conditions along a predefined driving route of a vehicle; determining, by the computer device and based on the conditions, risk factors of segments of the driving route; determining, by the computer device, an optimal one of the segments for switching the vehicle from autonomous driving mode to manual driving mode; and outputting, by the computer device, data defining the determined optimal one of the segments.

Abstract: Approaches presented herein enable performing an oral health diagnosis of a user using an oral monitoring device fixed in the oral cavity. Specifically, an oral monitoring device collects jaw movement data as a user goes about daily living. An oral healthcare analysis is performed comparing current measurement data against abnormality classifications to identify abnormal jaw movement. If an abnormality is identified, an oral healthcare professional can be notified.

Abstract: Embodiments for implementing intelligent transition between autonomous and manual driving modes by a processor. A customized transition plan for one or more entities may be generated for transitioning between an autonomous driving mode and a manual driving mode according to one or more identified contextual factors and driver performance requirements. The customized transition plan may be applied for transitioning between the autonomous driving mode and the manual driving mode.

Abstract: Embodiments for implementing intelligent transition between autonomous and manual driving modes by a processor. A customized transition plan for one or more entities may be generated for transitioning between an autonomous driving mode and a manual driving mode according to one or more identified contextual factors and driver performance requirements. The customized transition plan may be applied for transitioning between the autonomous driving mode and the manual driving mode.

Abstract: A computer system monitors food preparation. Images of food preparation by a user are captured via one or more image capture devices disposed within an area containing food preparation items. A food preparation process being performed by the user is determined. Image processing is performed on the captured images to monitor the food preparation process and detect an event. The user is notified of the detected event, and provided information pertaining to the event. Embodiments of the present invention further include a method and program product for monitoring food preparation in substantially the same manner described above.

Abstract: Approaches presented herein enable performing an oral health diagnosis of a user using an oral monitoring device fixed in the oral cavity. Specifically, an oral monitoring device collects jaw movement data as a user goes about daily living. An oral healthcare analysis is performed comparing current measurement data against abnormality classifications to identify abnormal jaw movement. If an abnormality is identified, an oral healthcare professional can be notified.

Abstract: Approaches presented herein enable cognitive oral health management. Specifically, data from at least one internet of things (IoT) sensor and data from at least one visual image sensor are collected over time for a user via one or more sensors operatively coupled with one or more personal daily oral care devices as the user is performing a periodic oral care activity with the one or more personal daily oral care devices. Collected data are subjected to cognitive diagnostics to identify abnormalities in a user's oral healthcare regimen and physiological abnormalities within the oral cavity by categorizing data. A report for a medical professional may be generated providing recommendation of potential diagnoses and treatment options.

Abstract: Approaches presented herein enable cognitive oral health management. Specifically, data from at least one internet of things (IoT) sensor and data from at least one visual image sensor are collected over time for a user via one or more sensors operatively coupled with one or more personal daily oral care devices as the user is performing a periodic oral care activity with the one or more personal daily oral care devices. Collected data are subjected to cognitive diagnostics to identify abnormalities in a user's oral healthcare regimen and physiological abnormalities within the oral cavity by categorizing data. A report for a medical professional may be generated providing recommendation of potential diagnoses and treatment options.

Abstract: Approaches presented herein enable performing an oral health diagnosis of a user using an oral monitoring device fixed in the oral cavity. Specifically, an oral monitoring device collects jaw movement data as a user goes about daily living. An oral healthcare analysis is performed comparing current measurement data against abnormality classifications to identify abnormal jaw movement. If an abnormality is identified, an oral healthcare professional can be notified.