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: 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: Discovering devices and device configurations. A method includes sending a request to a device to obtain a data value from the device. The method further includes, in response, receiving the data value from the device. The method further includes, based on the received data value, identifying one or more device identifications for the device. The method further includes, using the one or more identifications, sending commands for equipment potentially connected to the device. The method further includes, receiving one or more responses to the commands. The method further includes, based on the one or more responses, concretely identifying the device.

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: Discovering devices and device configurations. A method includes sending a request to a device to obtain a data value from the device. The method further includes, in response, receiving the data value from the device. The method further includes, based on the received data value, identifying one or more device identifications for the device. The method further includes, using the one or more identifications, sending commands for equipment potentially connected to the device. The method further includes, receiving one or more responses to the commands. The method further includes, based on the one or more responses, concretely identifying the device.

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: 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: Discovering devices and device configurations. A method includes sending a request to a device to obtain a data value from the device. The method further includes, in response, receiving the data value from the device. The method further includes, based on the received data value, identifying one or more device identifications for the device. The method further includes, using the one or more identifications, sending commands for equipment potentially connected to the device. The method further includes, receiving one or more responses to the commands. The method further includes, based on the one or more responses, concretely identifying the device.

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: Executing business logic for an entity of a relational structure having a plurality of entities includes obtaining data associated with a first entity of the plurality of entities of the relational structure. The obtained data at least partially causes actuation of a trigger. Based on actuation of the trigger, particular business logic associated with the trigger is identified. The business logic is executed for a second entity that is related to the first entity within the relational structure, by using the obtained data associated with the first entity as a parameter value for execution of the business logic for the second entity. A computing action is performed based on a result of executing the business logic for the second entity.