Abstract: Described herein is a system and method of processing data of a digital twins object model. Data associated with a node of the digital twins object model is parsed to identify metadata associated with the node. The data can comprise telemetry data received from an IoT device associated with the node. User-defined function(s) are determined that match the identified metadata. The data and metadata can be provided to the user-defined function(s). The determined user-defined function(s) are executed. Also described herein is a method of creating a user-defined function for processing data of a digital twins object model. Information regarding business logic is received from a user defining a user-defined function. Information regarding telemetry condition(s) to which the user-defined function applies is received defining a matcher. The user-defined function and matcher are stored as objects within a spatial intelligence graph associated with the digital twins object model.

Abstract: Computer-implemented functionality is described herein for assisting a user in interacting with an environment. In one implementation, the functionality operates by: determining that a particular user is within a prescribed proximity to an electronic sign, or will be in prescribed proximity to the electronic sign, based on sensor information provided by one or more sensors within the environment; determining an identity of the user; determining at least one destination of the user based at least on calendar information; providing directions to the destination(s), to provide unfiltered direction information; optionally filtering the unfiltered direction information with respect to restriction information (e.g., privacy information, security information, etc.), to produce filtered direction information; composing sign information based on the filtered direction information; and sending the sign information to the electronic sign for presentation by the sign.

Abstract: Configuring a device. A method includes identifying that a device has been connected to a control network. The method further includes, as a result, identifying characteristics of the device, including identifying at least one control or sensor coupled to the device. The method further includes, as a result, identifying an existing configuration template that applies to the device as identified, including identified characteristics. The method further includes configuring the device using the configuration template.

Abstract: A meeting insight computing system includes a meeting evaluation machine configured to collect quality parameters from meeting quality monitoring devices. The quality parameters each quantify meeting conditions during one or more previously-elapsed meetings and are usable to determine an overall quality score for each of the one or more previously-elapsed meetings. A graphical scheduling interface is configured to facilitate scheduling of an upcoming meeting at a designated meeting time, in a meeting location, and with one or more meeting participants. An insight generation machine is configured to report a meeting insight via the graphical scheduling interface. The meeting insight is based on the meeting time, the meeting location, the one or more meeting participants, and the quality parameters, and includes a recommendation to change one or more of the meeting time, meeting location, and meeting participants to improve a quality score of the upcoming meeting.

Abstract: A natural language query can be received at a main natural language processor inside a data protection compliance boundary in a computer system. The natural language query can be processed via the main natural language processor. The data from the query can be transmitted to a data protection computer component. It can be determined via the data protection component whether the data from the query includes protected data whose transmission to a computerized extension would violate a computer-readable data protection rule. The extension is outside the compliance boundary in the computer system and is configured to participate in responding to natural language queries received by the main natural language processor. In response to determining that the data from the query includes the protected data, transmission of the protected data from the main natural language processor to the extension as part of responding to the query can be inhibited.

Abstract: Controlling environmental conditions. A method includes using one or more sensors in a location, identifying an entity in the location. The method further includes identifying one or more roles for the entity. The method further includes based on the one or more roles for the entity, modifying environmental conditions in the location, by modifying one or more devices associated with the location.

Abstract: Controlling environmental conditions. A method includes using one or more sensors in a location, identifying an entity in the location. The method further includes identifying one or more roles for the entity. The method further includes based on the one or more roles for the entity, modifying environmental conditions in the location, by modifying one or more devices associated with the location.

Abstract: A technique is described herein for using computing technology to intelligently manage the consumption of a resource in a physical environment and/or controlling the physical environment in other ways. The technique maintains environment information that describes entities within the physical environment, together with the relationships among the entities. The technique leverages the environment information and collected sensor data to generate forecast data using one or more machine-trained models. The technique then leverages the environment information, sensor data, and forecast data to generate a control plan. The control plan provides a strategy for controlling the physical environment that satisfies a specified optimization objective. In one use case, the technique contributes to the efficient consumption of power provided by a distribution system by avoiding consumption of power in periods in which the distribution system is expected to experience high loads.

Abstract: A meeting insight computing system includes a meeting evaluation machine configured to collect quality parameters from meeting quality monitoring devices. The quality parameters each quantify meeting conditions during one or more previously-elapsed meetings and are usable to determine an overall quality score for each of the one or more previously-elapsed meetings. A graphical scheduling interface is configured to facilitate scheduling of an upcoming meeting at a designated meeting time, in a meeting location, and with one or more meeting participants. An insight generation machine is configured to report a meeting insight via the graphical scheduling interface. The meeting insight is based on the meeting time, the meeting location, the one or more meeting participants, and the quality parameters, and includes a recommendation to change one or more of the meeting time, meeting location, and meeting participants to improve a quality score of the upcoming meeting.

Abstract: Isolating resources between sub-entities. A method includes receiving data from a particular connected device. A memory storing a hierarchical graph that defines a topology for an entity is accessed. Branches or leaves in the graph include a node that represents a connected device, such as a sensor, controller, or computing system. Each connected device is configured to provide data or receive control signals. Each of the branches or leaves can be indicated as belonging to a particular sub-entity. A particular branch from the hierarchical graph having the particular connected device is identified using the graph. A sub-entity to which the particular branch belongs is identified. The method identifies that the particular sub-entity should be isolated from other sub entities. The data from the particular connected device is provided to a set of resources specifically allocated for the particular sub-entity.

Abstract: A meeting insight computing system includes a meeting evaluation machine configured to collect quality parameters from meeting quality monitoring devices. The quality parameters each quantify meeting conditions during one or more previously-elapsed meetings and are usable to determine an overall quality score for each of the one or more previously-elapsed meetings. A graphical scheduling interface is configured to facilitate scheduling of an upcoming meeting at a designated meeting time, in a meeting location, and with one or more meeting participants. An insight generation machine is configured to report a meeting insight via the graphical scheduling interface. The meeting insight is based on the meeting time, the meeting location, the one or more meeting participants, and the quality parameters, and includes a recommendation to change one or more of the meeting time, meeting location, and meeting participants to improve a quality score of the upcoming meeting.

Abstract: A technique is described herein for using computing technology to intelligently manage the consumption of a resource in a physical environment and/or controlling the physical environment in other ways. The technique maintains environment information that describes entities within the physical environment, together with the relationships among the entities. The technique leverages the environment information and collected sensor data to generate forecast data using one or more machine-trained models. The technique then leverages the environment information, sensor data, and forecast data to generate a control plan. The control plan provides a strategy for controlling the physical environment that satisfies a specified optimization objective. In one use case, the technique contributes to the efficient consumption of power provided by a distribution system by avoiding consumption of power in periods in which the distribution system is expected to experience high loads.

Abstract: Described herein is a system and method of processing data of a digital twins object model. Data associated with a node of the digital twins object model is parsed to identify metadata associated with the node. The data can comprise telemetry data received from an IoT device associated with the node. User-defined function(s) are determined that match the identified metadata. The data and metadata can be provided to the user-defined function(s). The determined user-defined function(s) are executed. Also described herein is a method of creating a user-defined function for processing data of a digital twins object model. Information regarding business logic is received from a user defining a user-defined function. Information regarding telemetry condition(s) to which the user-defined function applies is received defining a matcher. The user-defined function and matcher are stored as objects within a spatial intelligence graph associated with the digital twins object model.

Abstract: Computer-implemented functionality is described herein for assisting a user in interacting with an environment. In one implementation, the functionality operates by: determining that a particular user is within a prescribed proximity to an electronic sign, or will be in prescribed proximity to the electronic sign, based on sensor information provided by one or more sensors within the environment; determining an identity of the user; determining at least one destination of the user based at least on calendar information; providing directions to the destination(s), to provide unfiltered direction information; optionally filtering the unfiltered direction information with respect to restriction information (e.g., privacy information, security information, etc.), to produce filtered direction information; composing sign information based on the filtered direction information; and sending the sign information to the electronic sign for presentation by the sign.

Abstract: Controlling environmental conditions. A method includes using one or more sensors in a location, identifying an entity in the location. The method further includes identifying one or more roles for the entity. The method further includes based on the one or more roles for the entity, modifying environmental conditions in the location, by modifying one or more devices associated with the location.

Abstract: A wearable device is configured with various sensory devices that recurrently monitor and gather data for a physical environment surrounding a user to help locate and track real-world objects. The various heterogeneous sensory devices digitize objects and the physical world. Each sensory device is configured with a threshold data change, in which, when the data picked up by one or more sensory devices surpasses the threshold, a query is performed on each sensor graph or sensory device. The queried sensor graph data is stored within a node in a spatial graph, in which nodes are connected to each other using edges to create spatial relationships between objects and spaces. Objects can be uploaded into an object graph associated with the spatial graph, in which the objects are digitized with each of the available sensors. This digital information can be subsequently used to, for example, locate the object.

Abstract: A natural language query can be received at a main natural language processor inside a data protection compliance boundary in a computer system. The natural language query can be processed via the main natural language processor. The data from the query can be transmitted to a data protection computer component. It can be determined via the data protection component whether the data from the query includes protected data whose transmission to a computerized extension would violate a computer-readable data protection rule. The extension is outside the compliance boundary in the computer system and is configured to participate in responding to natural language queries received by the main natural language processor. In response to determining that the data from the query includes the protected data, transmission of the protected data from the main natural language processor to the extension as part of responding to the query can be inhibited.

Abstract: A natural language query can be processed via a main natural language processor. A request to produce an intent of the query can be dispatched from the main natural language processor to an extension natural language processor. An intent of the query can be generated via the extension natural language processor in response to the dispatched request, with the generating of the intent being performed independently of the main natural language processor. The intent of the natural language query can be passed from the extension natural language processor to the main natural language processor in response to the request to produce the intent of the query. A selection of a conversation query processor for responding to the intent can be produced via the main natural language processor. Additionally, an instruction to respond to the intent of the query can be passed to the selected conversation query processor.

Abstract: A computing system includes a physical space monitoring interface configured to receive status parameters from a plurality of physical space monitors, each of the physical space monitors configured to report a status parameter for one more locations, devices, or people associated with a physical space. An efficiency analysis machine analyzes the status parameters to determine at least one usage efficiency metric for the physical space and at least one physical space efficiency insight. An analytics interface graphically displays the usage efficiency metric and the physical space efficiency insight, the physical space efficiency insight including a recommendation to change a physical space usage policy affecting one or more locations, devices, or people associated with the physical space to improve the usage efficiency metric.

Abstract: A natural language query can be received at a main natural language processor inside a data protection compliance boundary in a computer system. The natural language query can be processed via the main natural language processor. The data from the query can be transmitted to a data protection computer component. It can be determined via the data protection component whether the data from the query includes protected data whose transmission to a computerized extension would violate a computer-readable data protection rule. The extension is outside the compliance boundary in the computer system and is configured to participate in responding to natural language queries received by the main natural language processor. In response to determining that the data from the query includes the protected data, transmission of the protected data from the main natural language processor to the extension as part of responding to the query can be inhibited.