Abstract: Disclosed is a technique that can be performed by a server computer system. The technique can include obtaining data from each of multiple endpoint devices to form global data. The global data can be generated by the endpoint devices in accordance with local instructions in each of the endpoint devices. The technique further includes generating global instructions based on the global data and sending the global instructions to a particular endpoint device. The global instructions configure the particular endpoint device to perform a data analytic operation that analyzes events. The events can include raw data generated by a sensor of the particular endpoint device.

Abstract: Disclosed is a technique that can be performed by an electronic device. The electronic device can generate time-stamped events, extract training data from the time-stamped events, and send the training data over a network to a remote computer. The electronic device can receive model data generated by the remote computer from the training data by use of a machine learning process, update a local model of the electronic device based on the received model data, and generate an output by processing locally sourced data of the electronic device with the updated local model.

Abstract: A method to provide an interface for asset tee determination includes performing a search of data, the search including user-supplied criteria information, causing display of results of the search, receiving user input providing classifications for the results of the search, the classifications indicating asset identifier and asset parent identifier fields in the results of the search, identifying, based on the user input and the results of the search, a plurality of unique assets identifiers and corresponding asset parent identifiers, and automatically generating a computer representation of an asset hierarchy comprising an asset node for each asset identifier, an asset parent node for each asset parent identifier, and a representation of hierarchical relationships between asset nodes and asset parent nodes.

Abstract: An asset monitoring and reporting system (AMRS) implements an interface to establish an asset hierarchy to be monitored and reported against. The interface employs a search query of extant asset data from which definitional aspects of the asset hierarchy can be identified, and therefrom the interface automatically determines control information reflective of the asset hierarchy to direct the ongoing operation of the AMRS. The interface further allows for configuration of a metric definition for a metric of an asset node of the asset hierarchy, the metric representing a point in time or a period of time and derived from a metric-time search of machine data produced by or about the asset node and receives an identification of a metric determination specification for the metric definition, the metric determination specification comprising at least identification of a metric component and identification of a calculation operation to apply to the metric component.

Abstract: A system for providing remote control of assets is disclosed herein. The system provides secure communications with one or more assets and receive operational data from the one or more assets. The system provides a graphical interface that includes one or more icons, one or more indicators, and one or more user input interfaces. The system receives a user input via the one or more user input interfaces and transmit the user input to an asset associated with the one or more user input interfaces. The system detects changes to an operational characteristics of the asset and display the changes.

Abstract: A system for providing remote monitoring of assets is disclosed. The system provides secure communication with one or more assets and receive operational data from the one or more assets. The system generates a graphical user interface that be used for selection of inputs from the one or more assets and specification of conditions to be applied to inputs for generation of alerts. The system can receive a selection of one or more asset outputs and two or more conditions. The conditions are applied to the selection of one or more assets to generate alerts when at least one of the conditions is satisfied.

Abstract: Disclosed is a technique that can be performed by a server computer system. The technique can include executing a machine learning process to generate a machine learning model based on global data collected from one or more electronic devices, wherein the machine learning model is described by model data. The technique can further include encapsulating the model data in a markup language document. The technique can further include sending, over a network, the markup language document to at least one electronic device of the one or more electronic devices to cause the at least one electronic device to update a local device machine learning model.

Abstract: Disclosed is a technique that can be performed by a server computer system. The technique can include obtaining data from each of multiple endpoint devices to form global data. The global data can be generated by the endpoint devices in accordance with local instructions in each of the endpoint devices. The technique further includes generating global instructions based on the global data and sending the global instructions to a particular endpoint device. The global instructions configure the particular endpoint device to perform a data analytic operation that analyzes events. The events can include raw data generated by a sensor of the particular endpoint device.

Abstract: Disclosed is a technique that can be performed by a server computer system. The technique can include obtaining data from each of multiple endpoint devices to form global data. The global data can be generated by the endpoint devices in accordance with local instructions in each of the endpoint devices. The technique further includes generating global instructions based on the global data and sending the global instructions to a particular endpoint device. The global instructions configure the particular endpoint device to perform a data analytic operation that analyzes events. The events can include raw data generated by a sensor of the particular endpoint device.

Abstract: A method to provide an interface for asset tee determination includes performing a search of data, the search including user-supplied criteria information, causing display of results of the search, receiving user input providing classifications for the results of the search, the classifications indicating asset identifier and asset parent identifier fields in the results of the search, identifying, based on the user input and the results of the search, a plurality of unique assets identifiers and corresponding asset parent identifiers, and automatically generating a computer representation of an asset hierarchy comprising an asset node for each asset identifier, an asset parent node for each asset parent identifier, and a representation of hierarchical relationships between asset nodes and asset parent nodes.

Abstract: A system for providing remote monitoring of assets is disclosed. The system provides secure communication with one or more assets and receive operational data from the one or more assets. The system generates a graphical user interface that be used for selection of inputs from the one or more assets and specification of conditions to be applied to inputs for generation of alerts. The system can receive a selection of one or more asset outputs and two or more conditions. The conditions are applied to the selection of one or more assets to generate alerts when at least one of the conditions is satisfied.

Abstract: A system for providing remote control of assets is disclosed herein. The system provides secure communications with one or more assets and receive operational data from the one or more assets. The system provides a graphical interface that includes one or more icons, one or more indicators, and one or more user input interfaces. The system receives a user input via the one or more user input interfaces and transmit the user input to an asset associated with the one or more user input interfaces. The system detects changes to an operational characteristics of the asset and display the changes.

Abstract: An asset monitoring and reporting system (AMRS) implements an interface to establish an asset hierarchy to be monitored and reported against. The interface employs a search query of extant asset data from which definitional aspects of the asset hierarchy can be identified, and therefrom the interface automatically determines control information reflective of the asset hierarchy to direct the ongoing operation of the AMRS.

Abstract: An asset monitoring and reporting system (AMRS) implements an interface to establish an asset hierarchy to be monitored and reported against. The interface employs a search query of extant asset data from which definitional aspects of the asset hierarchy can be identified, and therefrom the interface automatically determines control information reflective of the asset hierarchy to direct the ongoing operation of the AMRS. The interface further receives an identification of one or more asset nodes of an asset hierarchy for inclusion in an asset group, receives an identification of a group metric definition of a group metric of the asset group, and reflects in computer storage an asset group definition comprising an association of each of the one or more asset nodes and an association of the group metric definition.

Abstract: Disclosed is a technique that can be performed by a server computer system. The technique can include executing a machine learning process to generate a machine learning model based on global data collected from one or more electronic devices, wherein the machine learning model is described by model data. The technique can further include encapsulating the model data in a markup language document. The technique can further include sending, over a network, the markup language document to at least one electronic device of the one or more electronic devices to cause the at least one electronic device to update a local device machine learning model.

Abstract: An example method of implementing a control interface for metric definition specification for asset-driven hierarchy includes: causing display of a user interface for configuring a metric definition for a metric of an asset node of the asset hierarchy; receiving, via the user interface, a metric determination specification comprising an identification of a metric component, an identification of an operation to apply to the metric component, and metric time factors corresponding to time-related aspects of the metric definition; and reflecting, in a computer storage, the metric definition comprising an association of the metric determination specification with the metric.

Abstract: An asset monitoring and reporting system (AMRS) implements an interface to establish an asset hierarchy to be monitored and reported against. The interface employs a search query of extant asset data from which definitional aspects of the asset hierarchy can be identified, and therefrom the interface automatically determines control information reflective of the asset hierarchy to direct the ongoing operation of the AMRS. The asset or component hierarchy may further inform operations related to the generation and display of a user interface presenting widgets that graphically depict information about one or more such components during AMRS operation.

Abstract: An asset monitoring and reporting system (AMRS) implements an interface to establish an asset hierarchy to be monitored and reported against. The interface employs a search query of extant asset data from which definitional aspects of the asset hierarchy can be identified, and therefrom the interface automatically determines control information reflective of the asset hierarchy to direct the ongoing operation of the AMRS. The interface further allows for configuration of a metric definition for a metric of an asset node of the asset hierarchy, the metric representing a point in time or a period of time and derived from a metric-time search of machine data produced by or about the asset node and receives an identification of a metric determination specification for the metric definition, the metric determination specification comprising at least identification of a metric component and identification of a calculation operation to apply to the metric component.

Abstract: An asset monitoring and reporting system (AMRS) implements an interface to establish an asset hierarchy to be monitored and reported against. The interface employs a search query of extant asset data from which definitional aspects of the asset hierarchy can be identified, and therefrom the interface automatically determines control information reflective of the asset hierarchy to direct the ongoing operation of the AMRS. The interface further allows for configuration of a metric definition for a metric of an asset node of the asset hierarchy, the metric representing a point in time or a period of time and derived from a metric-time search of machine data produced by or about the asset node and receives an identification of a metric determination specification for the metric definition, the metric determination specification comprising at least identification of a metric component and identification of a calculation operation to apply to the metric component.

Abstract: Disclosed is a technique that can be performed by an electronic device. The technique can include generating timestamped events, where the timestamped events include raw data generated by electronic device. The technique can further include obtaining results by performing a operation on the timestamped events, in accordance with instructions. The technique can further include sending the results or indicia thereof over a network to a server computer system, and receiving back new instructions generated by the server computer system based on the sent results. Lastly, the technique can include performing a new operation on timestamped events including raw data generated based by the electronic device, where the new operation can be performed in accordance with the new instructions to obtain new results.