Abstract: A cloud agent facilitates collection of industrial data from one or more data sources on the plant floor and migration of the collected data to a cloud platform for storage and processing. Collection services associated with the cloud agent perform on-premise data collection of historical, live, and/or alarm data directly from industrial devices networked to the agent or from intermediate data concentrators that gather the data from the devices. Queue processing services executed by the cloud agent package the data into a data packet comprising header information that identifies a customer associated with the industrial enterprise, processing priority information, and other information that informs data processing services on the cloud platform how to process and/or direct the incoming data. The cloud agent then establishes a communication channel to the cloud platform and sends the data via the channel.

Abstract: A cloud human-machine interface (HMI) generation system converts an original HMI project to a web-compatible version of the HMI capable of storage and execution on a cloud platform or web server. The cloud HMI generation system parses HMI project files exported from the original HMI to identify graphical objects and their attributes, animations, data tags linked to the HMI, and other characteristics of the HMI. The system then generates scripts or function calls that reproduce the identified graphical objects and their associated animations, yielding a web-based HMI that emulates the original HMI project. The resulting cloud HMI can retrieve copies of the original industrial system data maintained on cloud-based storage, allowing the cloud HMI to display near real-time system data on a client device from any location.

Abstract: A cloud gateway device facilitates collection of industrial data from one or more data sources on the plant floor and migration of the collected data to a cloud platform for storage and processing. The cloud gateway device collects historical, live, and/or alarm data directly from industrial devices networked to the gateway device, formats and encapsulates the data with customer-specific header information, and sends the resulting data packets to a cloud platform for processing by cloud-level analytics services. To keep local memory requirements low, the cloud gateway device supports store-and-forward functionality in the event of a communication loss to the cloud platform, whereby the collected industrial data is redirected to an external data storage repository until communication to the cloud platform is reestablished.

Abstract: A cloud-based analytics system streams industrial data from customer facilities to a cloud platform as torrential data streams, and performs analytics on the data contained in the data streams based on a selected set of rules. The rules can be designed to diagnose current or potential issues, to monitor for alarm conditions, or to perform other types of analytics. One or more data pipelines migrate data from plant facilities to a data lake residing on the cloud platform. Data streams can be segregated according to customer, and can further be segregated according to plant facility, production area, or any other suitable classification. Each data stream has an associated manifest that identifies the set of rules to be used to process data in each data stream, allowing selected rules to be applied to each data stream in an ad hoc manner.

Abstract: Cloud-based data processing services facilitate collection and processing of industrial data in a cloud platform. On-premise data collection agents collect and pre-process industrial data from one or more data sources, including industrial devices, historians, etc. The agents apply a header to the data defining a hierarchical, customer-specific data model that can be leveraged in the cloud platform to suitably process the data. Cloud-side data process services receive the resulting data packets, assign the data to one or more priority queues, and invoke a manifest assembly corresponding to the data model defined by the header. The manifest assembly defines one or more operations to be performed on the received data, including specifying a final storage destination for the data, determining one or more metrics for an industrial system or process based on the received data, or other such operations.

Abstract: A cloud agent facilitates collection of industrial data from one or more data sources on the plant floor and migration of the collected data to a cloud platform for storage and processing. Collection services associated with the cloud agent perform on-premise data collection of historical, live, and/or alarm data directly from industrial devices networked to the agent or from intermediate data concentrators that gather the data from the devices. Queue processing services executed by the cloud agent package the data into a data packet comprising header information that identifies a customer associated with the industrial enterprise, processing priority information, and other information that informs data processing services on the cloud platform how to process and/or direct the incoming data. The cloud agent then establishes a communication channel to the cloud platform and sends the data via the channel.

Abstract: Authentication of cloud agents that collect and/or process industrial data facilitates secure communications with a cloud platform. An authentication component receives an authentication request from a cloud agent device residing at an industrial facility. The authentication component also authenticate the cloud agent device in response to the authentication request for a defined period of time based on an access key that uniquely identifies the cloud agent device residing at the industrial facility. A cloud data processing component receives, at a cloud platform, one or more data packets from the cloud agent device during the defined period of time and processes industrial data contained in the one or more data packets according processing instructions associated with the cloud platform.

Abstract: A cloud-based infrastructure facilitates gathering, transmitting, and remote storage of control and automation data using an agent-based communication channel. The infrastructure collects the industrial data from an industrial enterprise and intelligently sorts and organizes the acquired data based on selected criteria. Message queues can be configured on the cloud platform to segregate the industrial data according to priority, data type, or other criteria. Behavior assemblies stored in customer-specific manifests on the cloud platform define customer-specific preferences for processing data stored in the respective message queues. Web-based tools can deliver automated notifications to an end user device based on analysis of the stored data, and allow the user to remotely view the stored data.

Abstract: A cloud-based remote monitoring system and method monitor one or more industrial devices of an industrial facility, including a local data historian located to monitor one or more parameters from the industrial devices, and store parameters in a local storage associated with the data historian, as well as a cloud agent located at the industrial facility to collect data indicative of a past and/or a present state of the industrial devices from the data historian local storage according a manifest specific to the industrial facility. The cloud agent sends the collected data to a remote cloud platform according to the manifest, and dynamically reconfigures the cloud agent without interrupting the collecting and the sending.

Abstract: A cloud-based global alarm annunciation broker assist in locating and contacting suitable technical support personnel in response to detected alarm events at a plant facility. The system comprises a cloud-based framework that dynamically matches on-site alarm events to domain experts capable of addressing the alarm events. The framework uses an agent-based architecture to gather industrial data from data sources within the industrial environment, including time-series alarm data. The data is received at a cloud platform, where broker services perform a global search for suitable technical support resources in response to alarm events identified by the collected data. The brokering system can automatically generate service tickets and send notifications to both end users and system managers/supervisors, and can notify application-level experts about events and anomalies that emerge from the on-premise processes being monitored by the cloud-based broker system.

Abstract: A cloud-based remote monitoring system and method monitor an industrial facility. The industrial facility includes one or more industrial devices. A cloud agent located at the industrial facility is configured to, by at least one processor, collect data indicative of a past and/or a present state of the industrial devices according a manifest specific to the industrial facility. The cloud agent is further configured to send the collected data to a remote cloud platform according to the manifest dynamically reconfigure the cloud agent without interrupting the collecting and the sending. The cloud platform processes the sent data to facilitate remote monitoring of the industrial devices.

Abstract: A cloud-based global alarm annunciation broker assist in locating and contacting suitable technical support personnel in response to detected alarm events at a plant facility. The system comprises a cloud-based framework that dynamically matches on-site alarm events to domain experts capable of addressing the alarm events. The framework uses an agent-based architecture to gather industrial data from data sources within the industrial environment, including time-series alarm data. The data is received at a cloud platform, where broker services perform a global search for suitable technical support resources in response to alarm events identified by the collected data. The brokering system can automatically generate service tickets and send notifications to both end users and system managers/supervisors, and can notify application-level experts about events and anomalies that emerge from the on-premise processes being monitored by the cloud-based broker system.

Abstract: A cloud-based infrastructure facilitates gathering, transmitting, and remote storage of control and automation data using an agent-based communication channel. The infrastructure collects the industrial data from an industrial enterprise and intelligently sorts and organizes the acquired data based on selected criteria. Message queues can be configured on the cloud platform to segregate the industrial data according to priority, data type, or other criteria. Behavior assemblies stored in customer-specific manifests on the cloud platform define customer-specific preferences for processing data stored in the respective message queues. Web-based tools can deliver automated notifications to an end user device based on analysis of the stored data, and allow the user to remotely view the stored data.

Abstract: Cloud-aware industrial devices feed robust sets of data to a cloud-based data analyzer that executes as a service in a cloud platform. In addition to industrial data generated or collected by the industrial devices, the devices can provide device profile information to the cloud-based analyzer that identifies the device and relevant configuration information. The industrial devices can also provide customer data identifying an owner of the industrial devices, contact information for the owner, active service contracts, etc. The cloud-based data analyzer leverages this information to perform a variety of custom analytics on the data and generate reports or notifications catered to the particular industrial assets' optimal performance and business goals of the owner's industrial enterprise, as well as perform real-time decision making and control.

Abstract: A cloud-based infrastructure facilitates gathering, transmitting, and remote storage of control and automation data using an agent-based communication channel. The infrastructure collects the industrial data from an industrial enterprise and intelligently sorts and organizes the acquired data based on selected criteria. Message queues can be configured on the cloud platform to segregate the industrial data according to priority, data type, or other criteria. Behavior assemblies stored in customer-specific manifests on the cloud platform define customer-specific preferences for processing data stored in the respective message queues. Web-based tools can deliver automated notifications to an end user device based on analysis of the stored data, and allow the user to remotely view the stored data.

Abstract: Cloud-aware industrial devices feed robust sets of data to a cloud-based data analyzer that executes as a service in a cloud platform. In addition to industrial data generated or collected by the industrial devices, the devices can provide device profile information to the cloud-based analyzer that identifies the device and relevant configuration information. The industrial devices can also provide customer data identifying an owner of the industrial devices, contact information for the owner, active service contracts, etc. The cloud-based data analyzer leverages this information to perform a variety of custom analytics on the data and generate reports or notifications catered to the particular industrial assets' optimal performance and business goals of the owner's industrial enterprise, as well as perform real-time decision making and control.

Abstract: A cloud-based multi-tier cyber analytics system is provided for integration of cloud-side and on-premise analytics for industrial systems. The analytics system includes an emulation runtime engine that executes a virtualized controller on a cloud platform. The runtime engine serves as a core analytics component by providing a control-level analytics engine with application programming interfaces (APIs) that enable seamless interaction of distributed simulations, cloud level services, and hardware industrial controllers. A cloud-based framework integrates soft control, hard control, and simulation with cloud-level services, and includes components that facilitate near real-time data streaming from the plant floor to the cloud platform to yield an industrial Internet of Things (IoT).

Abstract: A cloud-based multi-tier cyber analytics system is provided for integration of cloud-side and on-premise analytics for industrial systems. The analytics system includes an emulation runtime engine that executes a virtualized controller on a cloud platform. The runtime engine serves as a core analytics component by providing a control-level analytics engine with application programming interfaces (APIs) that enable seamless interaction of distributed simulations, cloud level services, and hardware industrial controllers. A cloud-based framework integrates soft control, hard control, and simulation with cloud-level services, and includes components that facilitate near real-time data streaming from the plant floor to the cloud platform to yield an industrial Internet of Things (IoT).

Abstract: A cloud-based infrastructure facilitates gathering, transmitting, and remote storage of control and automation data using an agent-based communication channel. The infrastructure collects the industrial data from an industrial enterprise and intelligently sorts and organizes the acquired data based on selected criteria. Message queues can be configured on the cloud platform to segregate the industrial data according to priority, data type, or other criteria. Behavior assemblies stored in customer-specific manifests on the cloud platform define customer-specific preferences for processing data stored in the respective message queues. An agent-based analytics framework in the cloud platform performs desired analytics on the data using distributed parallel processing.

Abstract: A cloud-based infrastructure facilitates gathering, transmitting, and remote storage of control and automation data using an agent-based communication channel. The infrastructure collects the industrial data from an industrial enterprise and intelligently sorts and organizes the acquired data based on selected criteria. Message queues can be configured on the cloud platform to segregate the industrial data according to priority, data type, or other criteria. Behavior assemblies stored in customer-specific manifests on the cloud platform define customer-specific preferences for processing data stored in the respective message queues. An agent-based analytics framework in the cloud platform performs desired analytics on the data using distributed parallel processing.