Abstract: A method for applying GPS UAV attitude estimation to accelerate computer vision. The UAV has a plurality of GPS receivers mounted at fixed locations on the UAV. The method includes receiving GPS signals from each GPS satellite in view of the UAV, the GPS measurements comprising pseudo-range and carrier phase data representing the distance between each GPS receiver and each GPS satellite. Carrier phase and pseudo-range measurements are determined for each GPS receiver based on the pseudo-range and carrier phase data. The GPS carrier phase and pseudo-range measurements are compared pair-wise for each pair of GPS receiver and satellite. An attitude of the UAV is determined based on the relative distance measurements. A 3D camera pose rotation matrix is determined based on the attitude of the UAV. Computer vision image search computations are performed for analyzing the image data received from the UAV in real time using the 3D camera pose rotation matrix.

Abstract: A system, method and computer program product for composing persistent object instances that link resources across multiple, disparate systems. An example method includes associating resources with namespace-URLs and object instances. One of the namespace-URLs is designated as primary namespace-URL. A web-based object API is provided through which the object instance can be accessed. The web-based object API uses the primary namespace-URL as an identifier of the object instance.

Abstract: An embodiment of the invention provides a method for sending a message from a first user to a second user where an interface receives a message from the second user. A processor connected to the interface identifying one or more keywords in the message and searches an electronic database for the keyword(s) to identify one or more scripted message for the keyword(s). The electronic database includes scripted messages for each keyword in the electronic database. A communications device connected to the processor sends the identified scripted message(s) to the second user.

Abstract: A method for applying GPS UAV attitude estimation to accelerate computer vision. The UAV has a plurality of GPS receivers mounted at fixed locations on the UAV. The method includes receiving GPS signals from each GPS satellite in view of the UAV, the GPS measurements comprising pseudo-range and carrier phase data representing the distance between each GPS receiver and each GPS satellite. Carrier phase and pseudo-range measurements are determined for each GPS receiver based on the pseudo-range and carrier phase data. The GPS carrier phase and pseudo-range measurements are compared pair-wise for each pair of GPS receiver and satellite. An attitude of the UAV is determined based on the relative distance measurements. A 3D camera pose rotation matrix is determined based on the attitude of the UAV. Computer vision image search computations are performed for analyzing the image data received from the UAV in real time using the 3D camera pose rotation matrix.

Abstract: An embodiment of the invention provides a method for sending a message from a first user to a second user where an interface receives a message from the second user. A processor connected to the interface identifying one or more keywords in the message and searches an electronic database for the keyword(s) to identify one or more scripted message for the keyword(s). The electronic database includes scripted messages for each keyword in the electronic database. A communications device connected to the processor sends the identified scripted message(s) to the second user.

Abstract: A method for applying GPS UAV attitude estimation to accelerate computer vision. The UAV has a plurality of GPS receivers mounted at fixed locations on the UAV. The method includes receiving GPS signals from each GPS satellite in view of the UAV, the GPS measurements comprising pseudo-range and carrier phase data representing the distance between each GPS receiver and each GPS satellite. Carrier phase and pseudo-range measurements are determined for each GPS receiver based on the pseudo-range and carrier phase data. The GPS carrier phase and pseudo-range measurements are compared pair-wise for each pair of GPS receiver and satellite. An attitude of the UAV is determined based on the relative distance measurements. A 3D camera pose rotation matrix is determined based on the attitude of the UAV. Computer vision image search computations are performed for analyzing the image data received from the UAV in real time using the 3D camera pose rotation matrix.

Abstract: A vehicular alert system includes an autonomous aerial vehicle and a central computer. The autonomous aerial vehicle includes a processor, a display, and a detector. The processor controls a data transceiver. The detector detects one or more vehicular condition. The central computer communicates with the autonomous aerial vehicle via the data transceiver. The central computer includes a memory device. The memory device stores vehicular condition data and road condition data. The central computer communicates one of a vehicular condition or a road condition to the autonomous aerial vehicle. The processor of the autonomous aerial vehicle displays the received condition on the display.

Abstract: A method for controlling a drone includes receiving a request for information about a spatial location, generating data requests, configuring a flight plan and controlling one or more drones to fly over the spatial location to obtain data types based on the data requests, storing heterogeneous data captured by the one or more drones and creating spatio-temporal indices for identifying spatial or temporal coverage gaps in the data necessary to answer the request, controlling the one or more drones to fly over the spatial location to obtain a plurality of data types from the identified spatial or temporal coverage gaps and extracting and analyzing data to answer the request.

Abstract: A database comprises historical information of a user's response to previous notifications. The database is accessed to determine a time at which to provide a (new) notification to the user, utilizing at least: a) current user activity status (e.g., determined from measurement information collected from one or more personal devices and/or user calendar events; b) time/day; and c) context information about the notification (e.g., geo-location, indoors/outdoors) including notification type (e.g., calendar entry, email, IM). The user gets the notification via a portable device at the determined time. A machine learning model can select the determined time by discriminating features of the previous notifications for which the user immediately attended versus those that were deferred and/or ignored. Content of the notification can also be altered in view of such discriminating features so as to increase a likelihood the user will immediately attend to the provided notification.

Abstract: Detecting propensity profile for a person may comprise receiving artifacts associated with the person; detecting profile characteristics for the person based on the artifacts; receiving a plurality of predefined profiles comprising a plurality of characteristics and relationships between the characteristics over time, each of the plurality of predefined profiles specifying an indication of propensity; matching the profile characteristics for the person with one or more of the plurality of predefined profiles; and outputting one or more propensity indicators based on the matching, the propensity indicators comprising at least an expressed strength of a given propensity in the person at a given time.

Abstract: A vehicular alert system includes an autonomous aerial vehicle and a central computer. The autonomous aerial vehicle includes a processor, a display, and a detector. The processor controls a data transceiver. The detector detects one or more vehicular condition. The central computer communicates with the autonomous aerial vehicle via the data transceiver. The central computer includes a memory device. The memory device stores vehicular condition data and road condition data. The central computer communicates one of a vehicular condition or a road condition to the autonomous aerial vehicle. The processor of the autonomous aerial vehicle displays the received condition on the display.

Abstract: A vehicular alert system includes an autonomous aerial vehicle and a central computer. The autonomous aerial vehicle includes a processor, a display, and a detector. The processor controls a data transceiver. The detector detects one or more vehicular condition. The central computer communicates with the autonomous aerial vehicle via the data transceiver. The central computer includes a memory device. The memory device stores vehicular condition data and road condition data. The central computer communicates one of a vehicular condition or a road condition to the autonomous aerial vehicle. The processor of the autonomous aerial vehicle displays the received condition on the display.

Abstract: A method for controlling a drone includes receiving a request for information about a spatial location, generating data requests, configuring a flight plan and controlling one or more drones to fly over the spatial location to obtain data types based on the data requests, storing heterogeneous data captured by the one or more drones and creating spatio-temporal indices for identifying spatial or temporal coverage gaps in the data necessary to answer the request, controlling the one or more drones to fly over the spatial location to obtain a plurality of data types from the identified spatial or temporal coverage gaps and extracting and analyzing data to answer the request.

Abstract: A method, executed by one or more processors, includes monitoring a plurality of ambient condition sensors configured to sense a plurality of ambient conditions that are relevant to a plurality of communication modes provided by at least one user I/O device, deactivating a first communication mode of the plurality of communication modes and activating a second communication mode of the plurality of communication modes in response to determining, via the plurality of ambient condition sensors, that one or more of the plurality of ambient conditions are not conducive to the first communication mode and that the plurality of ambient conditions are collectively more conducive to the second communication mode than the first communication mode. A corresponding apparatus and computer program product are also disclosed herein.

Abstract: A system, computer program product, and method are provided for use with an intelligent computer platform to convert audio data intents to one or more physical actions. The aspect of converting audio data intent includes receiving audio, converting the audio to text, parsing the text into segments, identifying a physical action and associated application that are proximal in time to the received audio. A corpus is searched for evidence of the text to identify evidence of a physical user interface trace with a select application. An outcome is generated from the evidence. The outcome includes an instruction to invoke a user interface trace with the select application as a representation of the received audio.

Abstract: A system, computer program product, and method are provided for use with an intelligent computer platform to convert speech intents to one or more physical actions. The aspect of converting speech intent includes receiving audio, converting the audio to text, parsing the text into segments, identifying a physical action and associated application that are proximal in time to the received audio. A corpus is searched for evidence of a pattern associated with the received audio and corresponding physical action(s) and associated application. An outcome is generated from the evidence. The outcome includes identification of an application and production of an affirmative instruction. The instruction is converted to a user interface trace that is executed within the identified application.

Abstract: Mechanisms are provided for implementing a personalized health care management system. The mechanisms receive a personalized health care plan for a patient having at least one health goal of the patient, and dynamic patient monitoring data from one or more patient monitoring devices associated with the patient. The mechanisms analyze the dynamic patient monitoring data to determine at least one first communication to output to the patient containing content eliciting conformance of the patient with the personalized health care plan to achieve the at least one health goal. The mechanisms send, to a patient care manager computing device of a patient care manager associated with the patient, a second communication based on results of analyzing the dynamic patient monitoring data. The second communication initiates a new communication session, or continues an existing communication session, between the patient care manager computing device and a patient communication device associated with the patient.

Abstract: A method for controlling a drone includes receiving a request for information about a spatial location, generating data requests, configuring a flight plan and controlling one or more drones to fly over the spatial location to obtain data types based on the data requests, and extracting and analyzing data to answer the request. The method can include extracting data points from the data types, obtaining labels from a user for one or more of the data points, predicting labels for unlabeled data points from a learning algorithm using the labels obtained from the user, determining the predicted labels are true labels for the unlabeled data points and combining the extracted data, the user labeled data points and the true labeled data points to answer the request for information. The learning algorithm may be active learning using a support vector machine.

Abstract: Disclosed is a novel system and method for indicating a probability of errors in multimedia content. The system determines a user state or possible user distraction level. The user distraction level is indicated in the multimedia content. In one example, work is monitored being performed on the multimedia content. Distractions are identified while the work is being monitored. A probability of errors is calculated in at least one location of the multimedia content by on the distractions that have been identified. Annotations are used to indicate of the probability of errors. In another example, the calculating of probability includes using a function F(U,S,P) based on a combination of: i) a determination of user state (U), ii) a determination of sensitivity (S) of user input, and iii) a determination of user characteristics stored in a profile (P).

Abstract: Mechanisms are provided for implementing a personalized health care management system. The mechanisms receive a personalized health care plan for a patient having at least one health goal of the patient, and dynamic patient monitoring data from one or more patient monitoring devices associated with the patient. The mechanisms analyze the dynamic patient monitoring data to determine at least one first communication to output to the patient containing content eliciting conformance of the patient with the personalized health care plan to achieve the at least one health goal. The mechanisms send, to a patient care manager computing device of a patient care manager associated with the patient, a second communication based on results of analyzing the dynamic patient monitoring data. The second communication initiates a new communication session, or continues an existing communication session, between the patient care manager computing device and a patient communication device associated with the patient.