Abstract: A method for generating a singularity recommendation includes receiving structured and unstructured data for a user, where the structured and unstructured data for the user provide a first context for generating a singularity recommendation. The method, responsive to identifying a location for the user, determines ecosystem data based on the location for the user, where the ecosystem data provides a second context for generating the singularity recommendation. The method determines environmental data based on the location for the user, where the environmental data provides a second context for generating the singularity recommendation. The method generates the singularity recommendation based on the first context, the second context, and the third context directed to the user. The method displays the singularity recommendation in a user interface on a client device associated with the user.

Abstract: A method for generating a singularity recommendation includes receiving structured and unstructured data for a user, where the structured and unstructured data for the user provide a first context for generating a singularity recommendation. The method, responsive to identifying a location for the user, determines ecosystem data based on the location for the user, where the ecosystem data provides a second context for generating the singularity recommendation. The method determines environmental data based on the location for the user, where the environmental data provides a second context for generating the singularity recommendation. The method generates the singularity recommendation based on the first context, the second context, and the third context directed to the user. The method displays the singularity recommendation in a user interface on a client device associated with the user.

Abstract: The disclosure describes techniques for generating device recommendations. The techniques include registering a plurality of Internet of Things (IoT) devices in a social IoT network, where each device performs one or more tasks and the one or more tasks include a first task. The techniques include periodically receiving, with the social IoT network, a work profile from one or more of the registered devices. The work profile includes device information associated with the one or more device tasks performed by the respective registered device. The techniques include grouping devices performing the first task into groups of similar devices, identifying, based on the device information in the work profile received from one or more of the registered devices, at least one device from the group of devices for which recommendations are to be provided, generating the recommendations for the identified device, and providing the recommendations for the identified device.

Abstract: In an approach for chemical detection for a water source, a processor receives, from a network device of a plurality of network devices, data, wherein the data includes at least one of image data, video data, chemical sensor data, and biosensor data. A processor updates a predictive model with the data. A processor receives a table of possible chemical compositions from the predictive model. A processor determines to send an alert based on the table of possible chemical compositions. A processor sends the alert to a user device.

Abstract: Aspects provide for design template selectors, wherein processors are configured to determine a design pattern from a user input comprising a spatial arrangement of different discrete constituent design components, and determine that the design pattern input spatial arrangement of constituent components matches a portion of a selected one of a knowledge base plurality of completed design patterns that each comprise different fixed spatial arrangements of discrete constituent components within a threshold amount of confidence. Thus, aspects present the selected one of the knowledge base design patterns to the user as a suggested template for use in completing the design.

Abstract: Security system devices are configured to retrieve historic first sensor data acquired from a protected area in response to receiving a threat alarm notification from a peer security system that is related to an area monitored by the peer security system, wherein the protected area is different from and geographically separate from the area monitored by the peer security system. The system devise determines that a security threat is indicated for the protected area by assessing the retrieved selection of historic first sensor data as a function of a relation of the threat alarm notification from the peer security system to the protected area, wherein assessing the historic first sensor data without the function of the relation of the threat alarm notification from the peer security system to the protected area results in determining that the security threat is not indicated for the protected area.

Abstract: In an approach for chemical detection for a water source, a processor receives, from a network device of a plurality of network devices, data, wherein the data includes at least one of image data, video data, chemical sensor data, and biosensor data. A processor updates a predictive model with the data. A processor receives a table of possible chemical compositions from the predictive model. A processor determines to send an alert based on the table of possible chemical compositions. A processor sends the alert to a user device.

Abstract: The disclosure describes techniques for generating device recommendations. The techniques include registering a plurality of Internet of Things (IoT) devices in a social IoT network, where each device performs one or more tasks and the one or more tasks include a first task. The techniques include periodically receiving, with the social IoT network, a work profile from one or more of the registered devices. The work profile includes device information associated with the one or more device tasks performed by the respective registered device. The techniques include grouping devices performing the first task into groups of similar devices, identifying, based on the device information in the work profile received from one or more of the registered devices, at least one device from the group of devices for which recommendations are to be provided, generating the recommendations for the identified device, and providing the recommendations for the identified device.

Abstract: A method, computer system, and a computer program product for selecting a media playlist based on learning past behaviors of a user is provided. The present invention may include receiving a plurality of current user data. The present invention may then include receiving a plurality of current external conditions data. The present invention may also include enriching a plurality of current raw data associated with the plurality of current user data, the plurality of user reactions to the media selections and the plurality of current external conditions data. The present invention may further include determining the plurality of current user data exceeds a threshold. The present invention may also include, in response to determining the threshold is exceeded, creating a dataset. The present invention may then include retrieving a media playlist. The present invention may further include sending the retrieved media playlist to a media device.

Abstract: Security system devices are configured to retrieve historic first sensor data acquired from a protected area in response to receiving a threat alarm notification from a peer security system that is related to an area monitored by the peer security system, wherein the protected area is different from and geographically separate from the area monitored by the peer security system. The system devise determines that a security threat is indicated for the protected area by assessing the retrieved selection of historic first sensor data as a function of a relation of the threat alarm notification from the peer security system to the protected area, wherein assessing the historic first sensor data without the function of the relation of the threat alarm notification from the peer security system to the protected area results in determining that the security threat is not indicated for the protected area.

Abstract: Security system devices are configured to retrieve historic first sensor data acquired from a protected area in response to receiving a threat alarm notification from a peer security system that is related to an area monitored by the peer security system, wherein the protected area is different from and geographically separate from the area monitored by the peer security system. The system devise determines that a security threat is indicated for the protected area by assessing the retrieved selection of historic first sensor data as a function of a relation of the threat alarm notification from the peer security system to the protected area, wherein assessing the historic first sensor data without the function of the relation of the threat alarm notification from the peer security system to the protected area results in determining that the security threat is not indicated for the protected area.

Abstract: Security system devices are configured to retrieve historic first sensor data acquired from a protected area in response to receiving a threat alarm notification from a peer security system that is related to an area monitored by the peer security system, wherein the protected area is different from and geographically separate from the area monitored by the peer security system. The system devise determines that a security threat is indicated for the protected area by assessing the retrieved selection of historic first sensor data as a function of a relation of the threat alarm notification from the peer security system to the protected area, wherein assessing the historic first sensor data without the function of the relation of the threat alarm notification from the peer security system to the protected area results in determining that the security threat is not indicated for the protected area.

Abstract: A method, computer system, and a computer program product for selecting a media playlist based on learning past behaviors of a user is provided. The present invention may include receiving a plurality of current user data. The present invention may then include receiving a plurality of current external conditions data. The present invention may also include enriching a plurality of current raw data associated with the plurality of current user data, the plurality of user reactions to the media selections and the plurality of current external conditions data. The present invention may further include determining the plurality of current user data exceeds a threshold. The present invention may also include, in response to determining the threshold is exceeded, creating a dataset. The present invention may then include retrieving a media playlist. The present invention may further include sending the retrieved media playlist to a media device.

Abstract: Aspects provide for design template selectors, wherein processors are configured to determine a design pattern from a user input comprising a spatial arrangement of different discrete constituent design components, and determine that the design pattern input spatial arrangement of constituent components matches a portion of a selected one of a knowledge base plurality of completed design patterns that each comprise different fixed spatial arrangements of discrete constituent components within a threshold amount of confidence. Thus, aspects present the selected one of the knowledge base design patterns to the user as a suggested template for use in completing the design.

Abstract: Disclosed aspects relate to cognitive adaptations for well-being management in a living environment. A set of sensor-derived data for the living environment may be ingested. The ingestion of a set of sensor-derived data may occur using a set of micro-cognitive modules. The set of sensor-derived data may be analyzed using a machine learning technique. The set of sensor-derived data may be analyzed to detect an anomalous event related to the living environment. The anomalous event may be detected based on the set of sensor-derived data. An anomalous event response action may be performed in response to detecting the anomalous event.

Abstract: Disclosed aspects relate to cognitive adaptations for well-being management in a living environment. A set of sensor-derived data for the living environment may be ingested. The ingestion of a set of sensor-derived data may occur using a set of micro-cognitive modules. The set of sensor-derived data may be analyzed using a machine learning technique. The set of sensor-derived data may be analyzed to detect an anomalous event related to the living environment. The anomalous event may be detected based on the set of sensor-derived data. An anomalous event response action may be performed in response to detecting the anomalous event.

Abstract: An adaptive, automatically-reconfigurable, vehicle instrument display method and system are described that continuously looks for a specified physical action of a driver operating the vehicle and, upon determining that the specified physical action of the driver has occurred, automatically effects a change to at least one widget in the instrument panel display of the vehicle.

Abstract: An adaptive, automatically-reconfigurable, vehicle instrument display method and system are described that use information from multiple sensors located within the vehicle that monitor various aspects of a vehicle's operation and health to automatically modify presence and/or location of widgets in the vehicle's instrument display panel based upon circumstances or conditions as they occur or change.

Abstract: An adaptive, automatically-reconfigurable, vehicle instrument display method and system are described that continuously looks for a specified physical action of a driver operating the vehicle and, upon determining that the specified physical action of the driver has occurred, automatically effects a change to at least one widget in the instrument panel display of the vehicle.

Abstract: An adaptive, automatically-reconfigurable, vehicle instrument display method and system are described that use information from multiple sensors located within the vehicle that monitor various aspects of a vehicle's operation and health to automatically modify presence and/or location of widgets in the vehicle's instrument display panel based upon circumstances or conditions as they occur or change.