Abstract: A computer-based communications system is provided. In aspects of the invention, the computer-based communications system is configured to adjust a time period for delaying a message from being sent by a user. A message is drafted by a user to be sent to a recipient. A selection is received for send the message to the recipient. A time period is adjusted for sending the message to the recipient based on user-centric considerations where the time period for delaying sending the message is not explicitly specified by the user. The message is delayed being sent for the time period. After the time period, the message is sent to the recipient.

Abstract: An unmanned aerial vehicle for aerial transportation of delivery items. The unmanned aerial vehicle includes an attachment device to fasten and unfasten one or more delivery items to the unmanned aerial vehicle, a motor to aerially transport the one or more delivery items along a delivery route, a sensor mounted on the unmanned aerial vehicle to detect at least one environmental variable during the delivery route, and an alert system to generate a status associated with the unmanned aerial vehicle along the delivery route to an observer when the environmental variable exceeds a predetermined threshold.

Abstract: Techniques for drone device control are provided. In one example, a computer-implemented method comprises establishing, by a plurality of drone devices respectively operatively coupled to processors and coordinating with one other, a defined region of a defined coordinate space of a geographic area, wherein the defined region is associated with an animal. The computer-implemented method also comprises monitoring, by the plurality of drone devices, a physical relationship between the animal and the defined region. The computer-implemented method can also comprise, in response to identifying that the physical relationship between the animal and the defined region fails to meet a criterion, performing, by the plurality of drone devices, a pattern of operations selected to alter the physical relationship between the animal and the defined region to satisfy the criterion.

Abstract: A method deploys a remotely-maneuverable rolling platform from a faulty self-driving vehicle (SDV). The method detects a driving problem severity level for the faulty self-driving vehicle (SDV), where the driving problem severity level describes an amount of danger that is posed to other vehicles by the faulty SDV, and assesses environmental conditions at the location of the faulty SDV. The method determines an opportune position for deploying one or more road safety flares by the faulty SDV based on the environmental conditions at the location of the faulty SDV and the driving problem severity level, and then deploys a remotely-maneuverable rolling platform, from the faulty SDV to the opportune position, based on the amount of danger that is posed to the other vehicles by the faulty SDV, where the one or more road safety flares are coupled to the remotely-maneuverable rolling platform.

Abstract: A moving target service receives path of locations of a moving target monitored by a navigation device. The moving target service calculates at least one optimized course for at least one user to follow to intersect with the moving target at one or more future locations predicted based on the path of the locations and based on at least one context record. The moving target service outputs the at least one optimized course to a display interface accessible to the at least one user for directing the user to navigate from a starting point to at least one of the one or more future locations.

Abstract: Using an imaging device of a user device associated with a public user, an image of an autonomous vehicle (AV) operating in an area is captured. The public user associated with the user device is other than an occupant or controller of the AV. Image processing of the image is performed to extract a set of visual characteristics of the AV. A visual characteristic in the set of visual characteristics is insufficient to uniquely identify the AV. From a set of AVs a subset of candidate AVs is selected where each candidate AV in the subset of candidate AVs matches within a tolerance at least one visual characteristic in the set of visual characteristics, the subset of candidate AVs including the AV. A stop command is sent to the AV, causing the AV to execute a stopping operation resulting in a change in a velocity of the AV.

Abstract: A context-sensitive soundscape is generated by receiving a first identifier for identifying a target cognitive state for a user, and a second identifier for identifying a user cohort for the user. A present context is determined for the user. A machine-learning procedure is performed to map the target cognitive state to a set of audio output characteristics based upon the identified user cohort and the determined present context. An audio output is generated to create the context-sensitive soundscape that includes the set of audio output characteristics.

Abstract: An artificial neural network trained to predict the availability of an unused duration of a parking space based on input features is executed. Input features may include at least a contextual situation associated with the second entity, a behavior factor associated with a first entity that has been using the parking space, geographical location and time, events occurring within a threshold distance from the parking space. The artificial neural network may be further trained to output a transfer affinity based on the predicted availability of an unused duration, the contextual situation associated with the second entity and the behavior factor associated with the first entity. Based at least on the transfer affinity, the second entity can be selected. The unused duration can be transferred to the second entity from the first entity. The transferring can also include storing a payment and associated computation as a blockchain node in a blockchain.

Abstract: A computer-implemented method controls a self-driving vehicle. One or more processors, based on a set of sensor readings from one or more passenger sensors within a self-driving vehicle (SDV), determine an identity of a current passenger in the SDV. The processor(s) establish a destination for the current passenger in the SDV based on the identity of the current passenger in the SDV, and receive computer executable instructions directing the SDV to travel to the destination for the current passenger in the SDV. The processor(s) then execute the computer executable instructions to cause the SDV to travel to the destination.

Abstract: A computer-based communications system is provided. In aspects of the invention, the computer-based communications system is configured to adjust a time period for delaying a message from being sent by a user. A message is drafted by a user to be sent to a recipient. A selection is received for send the message to the recipient. A time period is adjusted for sending the message to the recipient based on user-centric considerations where the time period for delaying sending the message is not explicitly specified by the user. The message is delayed being sent for the time period. After the time period, the message is sent to the recipient.

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: Methods and systems for crop grading and crop management. One or more images of crops are obtained and one or more crop related features are at least one of identified or extracted from the one or more images. A crop health status is determined based on the one or more crop related features, an environmental context, a growth stage of the crop, and a farm cohort by using a computerized deep learning system to perform an automated growth stage analysis. One or more actions are at least one of recommended, triggered, and performed.

Abstract: A method, system, and/or computer program product controls operations of an aerial drone within a predetermined airspace. One or more processors detects that the aerial drone has entered a predetermined airspace, and also determines a physical size of the aerial drone. In response to detecting that the aerial drone has entered the predetermined airspace, one or more processors directs the aerial drone to alter a velocity of the aerial drone based on its physical size.

Abstract: A volume and speech frequency level adjustment method, system, and computer program product include learning a characteristic of at least one of audio volume and speech frequency from a conversation, detecting a contextual characteristic of an ongoing conversation and an interaction of a user with a device, determining a cognitive state of the user in relation to the ongoing conversation as a function of at least one of the contextual characteristic of the volume or the speech frequency, and a user interaction pattern with a conversation device, and dynamically adjusting audio levels of the ongoing conversation for the user based on the function.

Abstract: An implantable device coupled with an integrated circuitry, is operable to receive signals representing a human body action. The implantable device may be further operable to authenticate the signals. Responsive to authenticating the signals, the implantable device may be further operable to perform a device action associated with the implantable device. The implantable device may include a medical device that detects physical conditions of a body.

Abstract: A computer-implemented method, system, and/or computer program product controls a driving mode of a self-driving vehicle (SDV). One or more processors compare a control processor competence level of an on-board SDV control processor in controlling the SDV to a human driver competence level of a human driver in controlling the SDV while the SDV encounters a current roadway condition which is a result of current weather conditions of the roadway on which the SDV is currently traveling. One or more processors then selectively assign control of the SDV to the SDV control processor or to the human driver while the SDV encounters the current roadway condition based on which of the control processor competence level and the human driver competence level is relatively higher to one another.

Abstract: A natural language processing system for analyzing speech includes a computer processing device configured to receive recorded speech of a person. The computer processing device constructs a baseline speech model of the person, the baseline speech model of the person including a property of speech based on a personal attribute of the person, compares current recorded speech of the person to the baseline speech model of the person to determine a deviation of the property of speech therebetween, and determines if the deviation of the property of speech meets a threshold of the property of speech that is defined for a disorder.

Abstract: A method, system, and/or computer program product controls a self-driving vehicle (SDV) based on a purchase transaction at a point of sale (POS) device. One or more processors detects a purchase transaction at a device for a product. In response to detecting the purchase transaction at the POS device, the processors(s) transmits instructions to the SDV to transport a passenger associated with the purchase transaction from a location of the POS device to a predetermined location.

Abstract: A method, system, and/or computer program product controls a self-driving vehicle based on a purchase transaction at a point of sale (POS) device. One or more processors detect a purchase transaction at the POS device. In response to detecting the purchase transaction at the POS device, the processor(s) transmit instructions to the SDV to pick up a passenger associated with the purchase transaction at a predetermined location.

Abstract: Techniques facilitating mitigation of dangerous activities are provided. In one example, a computer-implemented method can include detecting, by a system operatively coupled to a processor, a trigger event based on a determination that a security risk level satisfies a defined condition associated with the security risk level. The security risk level can be associated with an item of interest and a monitored behavior related to the item of interest. The computer-implemented method can also include implementing, by the system, an action that mitigates an impact of the security risk level. The action can be implemented as the trigger event is detected and the action can be determined based on the item of interest and the monitored behavior.