Abstract:
A graphical interface module may provide a set of graphical presentations comprising at least: a Likelihood of Delivery chart showing a probability distribution of predicted delivery dates; a Delivery Date Risk Trend chart showing how the completion time for the project predicted according to the Likelihood of Delivery chart has changed over time; and a Burndown chart that shows at least work-items of planned work for the project. Each of the Likelihood of Delivery chart, the Delivery Date Risk Trend chart, and the Burndown chart has a timeline axis.
Abstract:
A method of providing a user interface with recipient status information, in one aspect, may comprise detecting a message (e.g., online message such as instant messaging, chat, etc.) being initiated by a first user to a second user; gathering information associated with the second user; analyzing the gathered information; predicting a state of the second user based on the analyzing; and determining a notification action based on the predicted state of the second user, the notification action notifying the first user of the second user's state; and presenting a notification comprising one or more of graphical, textual, auditory, or tactile indications or combinations thereof to the first user.
Abstract:
An unmanned aerial vehicle for determining geolocation exclusion zones of animals. The unmanned aerial vehicle includes a processor-based monitoring device to track geolocation information associated with an animal from the unmanned aerial vehicle, an identification device mounted on the unmanned aerial vehicle to identify the animal and to track a position of the animal over time, and a mapping device coupled to the monitoring device to determine locations where the animal has traversed and to identify where an encounter with the animal is reduced.
Abstract:
Systems and methods for dynamically managing figments are disclosed. A computer-implemented method includes: receiving, by a computing device, a question from a user; answering, by the computing device, the question using a first degree figment; classifying, by the computing device, the question based on topics; forwarding, by the computing device, the question to a set of second degree figments; receiving, by the computing device, answers to the question from the set of second degree figments; ranking, by the computing device, the answers received from the set of second degree figments; and providing, by the computing device, the ranked answers to the user.
Abstract:
A method, computer system, and/or computer program product dynamically adjusts an insurance policy parameter for a self-driving vehicle (SDV) operating in manual mode. One or more processors receive a copy of manual control signals from an SDV, where the SDV is in manual mode during a particular time period. The processor(s) also receive a copy of computer control signals generated by an SDV on-board computer on the SDV during the particular time period, and compare the manual control signals to the computer control signals. In response to the manual control signals matching the computer control signals within a predetermined range, the processor(s) adjust an insurance policy parameter for the SDV while the SDV is being controlled by the particular human operator.
Abstract:
A method, system, and/or computer program product controls movement and adjusts operations of an aerial drone. A drone camera observes an aerial maneuver physical gesture by a user. The aerial drone then performs an aerial maneuver that correlates to the aerial maneuver physical gesture. The drone camera observes the user performing a physical action. One or more processors associate the physical action with a particular type of activity. A drone on-board computer adjusts an operation of an aerial drone based on the particular type of activity.
Abstract:
A computer-implemented method, system, and/or computer program product controls a driving mode of a self-driving vehicle (SDV) when a driver receives a telecommunication message on a telecommunication device. An SDV on-board computer within the SDV detects that the SDV is currently being operated in manual mode by a human driver. The SDV on-board computer detects that a telecommunication device located within the SDV is receiving a telecommunication message. In response to detecting that the telecommunication device within the SDV is receiving the telecommunication message, the SDV on-board computer transfers control of the SDV to the SDV on-board computer in order to place the SDV in autonomous mode, where the SDV is in the autonomous mode when steering, braking, throttle control, and obstacle avoidance by the SDV are all controlled by the SDV on-board computer.
Abstract:
A processor-implemented method and/or computer program product selectively blocks a self-driving vehicle's access to a roadway. A vehicle interrogation hardware device receives an autonomous capability signal from an approaching self-driving vehicle. One or more processors compare the predefined roadway conditions to current roadway conditions of the access-controlled roadway. In response to the predefined roadway conditions matching the current roadway conditions of the access-controlled roadway within a predetermined range, the processor(s) determine whether the level of autonomous capability of the approaching self-driving vehicle is adequate to safely maneuver the approaching self-driving vehicle through the current roadway conditions of the access-controlled roadway. In response determining that the level of autonomous capability of the self-driving vehicle is not adequate to safely maneuver the approaching self-driving vehicle through the current roadway conditions of the access-controlled roadway, an automatic barricade controlling device positions an automatic barricade to block the approaching self-driving vehicle from accessing the access-controlled roadway.
Abstract:
A processor-implemented method, system, and/or computer program product control a driving mode of a self-driving vehicle (SDV). One or more processors detect that an SDV is being operated in manual mode by a human driver. The processor(s) determine that the human driver is unqualified to operate the SDV in manual mode, and then transfer control of the SDV to an SDV on-board computer in order to place the SDV in autonomous mode.
Abstract:
A method and/or computer program product controls a physical spacing between self-driving vehicles (SDVs). One or more processors receive a social network node graph. The social network node graph describes a graphical distance between a first node on the social network node graph and a second node on the social network node graph. The first node represents a first passenger in a first SDV; the second node represents a second passenger in a second SDV; and the graphical distance between the first node and the second node describes a relationship level in a social network between the first passenger and the second passenger. An SDV on-board computer on at least one of the first SDV and the second SDV adjusts a physical spacing between the first SDV and the second SDV proportional to the graphical distance between the first node and the second node.