Abstract: A processor may record a first location at an event with at least one person. The processor may monitor a plurality of actions of that at least one person at the first location. The processor may interpret at least one action of the at least one person that indicates a change of interest to a second location at the event. Based on the at least one action, the processor may determine the second location at the event. The processor may record the second location at the event.

Abstract: A method controls a robot. One or more processors receive sensor readings from one or more sensors that are monitoring a human in real time, where the human is currently observing a robotic action by a robot, and where the robotic action is a physical movement performed by the robot. The processor(s) determine a cognitive state of the human while the human is observing the robotic action by the robot, and then adjust the robotic action being performed by the robot based on the cognitive state of the human.

Abstract: The method includes receiving a first set of data from a first client device. The method further includes determining a first topic from the first set of data. The method further includes generating a first productivity value for the first topic. The method further includes receiving a second set of date data from a second client device. The method further includes determining a second topic from by the second set of data. The method further includes generating a second productivity value for second set of data. The method further includes comparing the first topic to the second topic. The method further includes in response to comparing the first topic and the second topic and determining the difference between the first productivity value and the second productivity value is above a threshold value, triggering an action.

Abstract: In one embodiment, in accordance with the present invention, a method, computer program product, and system for performing actions based on captured interpersonal interactions during a meeting is provided. One or more computer processors capture the interpersonal interactions between people in a physical space during a period of time, using machine learning algorithms to detect the interpersonal interactions and a state of each person based on vision and audio sensors in the physical space. The one or more computer processors analyze and categorize the interactions and state of each person, and tag representations of each person with the respectively analyzed and categorized interactions and states of the respective person over the period of time. The one or more computer processors then take an action based on the analysis.

Abstract: A touch detection system is provided. The touch detection system includes a hardware processor. The touch detection system further includes a touch input surface mounted using a set of torque sensors, where a location of a touch on the touch input surface is calculated by the hardware processor based on collective results from the set of torque sensors, the touch comprising a user input.

Abstract: A touch detection system is provided. The touch detection system includes a hardware processor. The touch detection system further includes a touch input surface mounted using a set of torque sensors, where a location of a touch on the touch input surface is calculated by the hardware processor based on collective results from the set of torque sensors, the touch comprising a user input.

Abstract: A system, computer program product and computer-implemented method for presenting data. The system includes a sensor that obtains a measurement related to a viewing parameter of a viewer in the environment, a presentation surface that provides data for viewing by the viewer, and a processor. The viewing parameter of the viewer indicates the viewer's ability to perceive the data. The processor determines the viewing parameter of the viewer from the obtained measurement and dynamically alters a presentation parameter of the presentation surface based at least in part on the viewing parameter of the viewer.

Abstract: A method controls a robot. One or more processors receive sensor readings from one or more sensors that are monitoring a human in real time, where the human is currently observing a robotic action by a robot, and where the robotic action is a physical movement performed by the robot. The processor(s) determine a cognitive state of the human while the human is observing the robotic action by the robot, and then adjust the robotic action being performed by the robot based on the cognitive state of the human.

Abstract: In one embodiment, in accordance with the present invention, a method, computer program product, and system for performing actions based on captured interpersonal interactions during a meeting is provided. One or more computer processors capture the interpersonal interactions between people in a physical space during a period of time, using machine learning algorithms to detect the interpersonal interactions and a state of each person based on vision and audio sensors in the physical space. The one or more computer processors analyze and categorize the interactions and state of each person, and tag representations of each person with the respectively analyzed and categorized interactions and states of the respective person over the period of time. The one or more computer processors then take an action based on the analysis.

Abstract: In an approach to determining an introduction of a user in a meeting, one or more computer processors retrieve a document containing information associated with a user, wherein the document includes one or more fragments describing the user. The one or more computer processors determine an audience of a meeting associated with the user. The one or more computer processors determine a description of the meeting. The one or more computer processors prioritize one or more of the one or more fragments, based, at least in part, on the audience of the meeting and on the description of the meeting. The one or more computer processors select one or more of the one or more fragments for the introduction of the user in the meeting, based, at least in part, on the prioritization of the one or more fragments.

Abstract: A computer-implemented method manages remote electronic drop-ins on local conversations. A local audio sensor transmits a captured conversation from a local cluster of persons to a remote communication device where members of the local cluster of persons are within a predefined distance of one another, and where the remote communication device is at a location that is beyond a human hearing range from the local audio sensor. One or more processors determine that the captured conversation is about a particular topic. A request from a remote user is received from the remote communication device to electronically drop in on a particular remote cluster of persons who are having a conversation about the particular topic. In response to receiving the request from the remote user, one or more processors selectively connect a local communication device proximate to the cluster of persons to the remote communication device.

Abstract: A system, computer program product and computer-implemented method for presenting data. The system includes a sensor that obtains a measurement related to a viewing parameter of a viewer in the environment, a presentation surface that provides data for viewing by the viewer, and a processor. The viewing parameter of the viewer indicates the viewer's ability to perceive the data. The processor determines the viewing parameter of the viewer from the obtained measurement and dynamically alters a presentation parameter of the presentation surface based at least in part on the viewing parameter of the viewer.

Abstract: A method for managing and rendering one or more information nodes relative to a current focus. The method receives one or more principal topics from an analysis of the information nodes. The method determines a topic vector from a similarity of a first information node to each of the principal topics and a map from the topic vector to a storage location of the first information node. The method determines one or more current topics from a second information node that has been recently accessed by a user and a current focus vector from a similarity of the one or more current topics to the one or more principal topics. The method renders the current focus vector and the first information node according to a rendering algorithm that is applied to the current focus vector and the first information node.

Abstract: A computer-implemented method manages remote electronic drop-ins on local conversations. A local audio sensor transmits a captured conversation from a local cluster of persons to a remote communication device where members of the local cluster of persons are within a predefined distance of one another, and where the remote communication device is at a location that is beyond a human hearing range from the local audio sensor. One or more processors determine that the captured conversation is about a particular topic. A request from a remote user is received from the remote communication device to electronically drop in on a particular remote cluster of persons who are having a conversation about the particular topic. In response to receiving the request from the remote user, one or more processors selectively connect a local communication device proximate to the cluster of persons to the remote communication device.

Abstract: A computer-implemented method manages drop-ins on conversations near a focal point of proximal activity in a gathering place. One or more processors receive a first set of sensor data from one or more sensors in a gathering place, and then identify a focal point of proximal activity based on the first set of received sensor data received from the one or more sensors. One or more processors characterize a conversation near the focal point based on a second set of received sensor data from the one or more sensors, and then present a characterization of the conversation to an electronic device. One or more processors enable the electronic device to allow a user to drop-in on the conversation.

Abstract: A computer program product for managing and rendering one or more information nodes relative to a current focus. The computer program product receives one or more principal topics from an analysis of the information nodes. The computer program product determines a topic vector from a similarity of a first information node to each of the principal topics and a map from the topic vector to a storage location of the first information node. The computer program product determines one or more current topics from a second information node that has been recently accessed by a user and a current focus vector from a similarity of the one or more current topics to the one or more principal topics. The computer program product renders the current focus vector and the first information node according to a rendering algorithm that is applied to the current focus vector and the first information node.

Abstract: A processor may record a first location at an event with at least one person. The processor may monitor a plurality of actions of that at least one person at the first location. The processor may interpret at least one action of the at least one person that indicates a change of interest to a second location at the event. Based on the at least one action, the processor may determine the second location at the event. The processor may record the second location at the event.

Abstract: A computer program product for managing and rendering one or more information nodes relative to a current focus. The computer program product receives one or more principal topics from an analysis of the information nodes. The computer program product determines a topic vector from a similarity of a first information node to each of the principal topics and a map from the topic vector to a storage location of the first information node. The computer program product determines one or more current topics from a second information node that has been recently accessed by a user and a current focus vector from a similarity of the one or more current topics to the one or more principal topics. The computer program product renders the current focus vector and the first information node according to a rendering algorithm that is applied to the current focus vector and the first information node.

Abstract: A computer program product for managing and rendering one or more information nodes relative to a current focus. The computer program product receives one or more principal topics from an analysis of the information nodes. The computer program product determines a topic vector from a similarity of a first information node to each of the principal topics and a map from the topic vector to a storage location of the first information node. The computer program product determines one or more current topics from a second information node that has been recently accessed by a user and a current focus vector from a similarity of the one or more current topics to the one or more principal topics. The computer program product renders the current focus vector and the first information node according to a rendering algorithm that is applied to the current focus vector and the first information node.

Abstract: A method for managing and rendering one or more information nodes relative to a current focus. The method receives one or more principal topics from an analysis of the information nodes. The method determines a topic vector from a similarity of a first information node to each of the principal topics and a map from the topic vector to a storage location of the first information node. The method determines one or more current topics from a second information node that has been recently accessed by a user and a current focus vector from a similarity of the one or more current topics to the one or more principal topics. The method renders the current focus vector and the first information node according to a rendering algorithm that is applied to the current focus vector and the first information node.