Splunk Inc.

Samsara Inc.

Erick Anthony Dean

Brian Matthew Gilmore

Adam Jamison Oliner

Pradeep Baliganapalli Nagaraju

Jiahan Wang

Jindrich Dinga

Marvin Herville Green

James Robert Saunders

Noah Paul Gonzales

Jennifer T Nguyen

Youny Jing Kuang

Audrey Yun Li

Famien Aaron Koko

Steve Yu Zhang

Amanda Wang

Oscar Ulissez Garcia

Steven Vellon

A method of monitoring hierarchical asset groups includes the operations of: receiving a plurality of asset group configuration parameters comprising one or more association specifications, each association specification defining an association between an asset and a corresponding asset group of a plurality of asset groups of an asset hierarchy; receiving definitions of one or more asset group metrics, wherein each asset group metric of the one or more asset group metrics is derived from a search of machine data associated with a corresponding asset group; associating, with each asset group of the plurality of asset groups, a corresponding asset group metric of the one or more asset group metrics; generating one or more alert definitions associated with an asset group of the plurality of asset groups; monitoring, using the one or more asset group metrics, the asset hierarchy; and generating an alert based on the one or more alert definitions.

Monitoring hierarchical asset groups

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.

Server-side operations for edge analytics

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.

Data analytics in edge devices

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.

Monitoring system control interface for asset tree determination

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.

Monitoring asset hierarchies based on asset group metrics

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.

Remote asset monitoring and control

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.

Remote asset notification

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.

Transmitting machine learning models to edge devices for edge analytics

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.

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.

Asset group interface driven by search-derived asset tree hierarchy

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.

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Piedmont, CA, United States of America

Erick Anthony Dean