Abstract: Approaches for determining a variational limit(s) of an operating parameter of an asset(s) are described. In one example, values of a first operating parameter of an asset(s) operating in a first operating condition may be obtained. The asset(s) may be deployed in one of an architectural level of an operational technology network, associated with an industrial control system (ICS). The values may be processed based on a predefined criteria associated with the asset. In one example, the predefined criteria may define one of a performant operational state and a non-performant operational state of the asset(s) during the first operating condition. Further, a variational limit(s) for the first operating parameter may be determined, wherein the variational limit(s) may be indicative of a range of values of the first operating parameter of the asset(s) as the asset(s) operates during the first operating condition.

Abstract: Devices, methods, and systems for standardizing proximity calculations are described herein. A method can include setting, by a computing device, a proximity attribute for each of a plurality of equipment relationship attributes for a user, receiving, by the computing device, a plurality of equipment items each having one of the plurality of equipment relationship attributes to another one of the plurality of equipment items, creating, by the computing device, a graph diagram including each of the plurality of equipment items coupled to one another by their respective equipment relationship attributes and the proximity attribute for their respective equipment relationship attributes, calculating, by the computing device using the graph diagram, a proximity between two of the plurality of equipment items, and providing, by the computing device, the calculated proximity to the user.

Abstract: Methods for mapping camera locations and fields of view (FOV) for video surveillance cameras in a facility. A mounted location and FOV are identified for each camera, where the FOV is defined by the mounted location, horizontal direction, vertical tilt, and optical specifications. A camera graph may be generated representing the cameras, with nodes identifying distances and directions between neighboring cameras. The graph is distributed to the cameras, enabling autonomous identification of neighbors. When an object of interest moves toward a neighboring camera's FOV, a peer-to-peer command is sent to track the object. Camera locations can be identified using mobile devices through manual map selection or WiFi/Bluetooth beacons. Camera directions can be determined using mobile device alignment with camera lenses or using camera IMU outputs for image stabilization.

Abstract: The present disclosure relates to a method for generating a unique signature of a data item of an enterprise. The method comprises identifying for the data item, a source data system, a target data system, and an associated data channel, where the source data system and the target data system belong to a plurality of data systems of the enterprise, and the associated data channel belongs to a plurality of data channels of the enterprise. The method further comprises accessing a system inventory of the enterprise, comprising details of the plurality of data systems of the enterprise, for retrieving a first set of information having a unique reference of the source data system of the data item. The method further comprises accessing a channel inventory of the enterprise, comprising details of the plurality of data channels of the enterprise, for retrieving a second set of information having a channel name, the unique reference of the source data system, and a unique reference of the target data system.

Abstract: A method and system for resolving the data lineage in integrated operation technology (OT)-Information technology system (IT) is provided. The techniques described herein provides a solution for connected industries by enabling an Artificial Intelligence (AI)/Machine learning model (ML) to automatically trace the flow of data and identify the errors in data and provide a visual representation of the flow of data from a source to destination. The AI/ML model can uncover the hidden patterns with the help of historical data and validation techniques and make decisions to provide useful insight to downstream OT systems for automating a workflow. The present disclosure focuses on the onboarding of various OT systems data with a defined data structure into a database for efficiently and quickly resolving the data lineage of connected systems. The analysis performed by the AI/ML model is used for diagnosis and deviation prediction from a pre-defined key performance indicator.

Abstract: An Account Booking Location (ABL) is computed from a login request to access an account of a user. The ABL corresponds to an asset of a partner entity that initiated the account. A UI element corresponding to the ABL is pushed from a repository to a cache for a UI rendering and a rendering service composes a rendering instruction using the cached data to cause a brand-specific UI to be rendered on a device of the user. When a second login request from a second user also corresponds to the ABL, the cached data is reused to compose a second rendering instruction such that the second rendering instruction causes the brand-specific UI to be rendered on a second device. When a control mechanism is configured to cause a feature to be rendered in an ABL agnostic manner, the rendering instruction is modified to include the feature on the brand-specific UI.

Abstract: A system and a method of determining asset context equivalence are described. The method includes collecting a first information related to an asset operating in an enterprise. The first information is collected from a first monitoring service running at a network level, and the first information includes tags assigned at network levels traversed by the first information. A Key Performance Indicator (KPI) value of the first monitoring service is determined using the first information. Upon deviation in KPI value, the asset associated with the first information is traced using the tags assigned at the network levels. A second monitoring service associated with the asset is identified, a second information is collected from the second monitoring service and used for performing a root cause analysis, to determine a cause of the deviation. An action related to the asset is taken to remediate the cause of the deviation in the KPI value.

Abstract: Devices, methods, and systems for variable alarm setpoints and priorities are described herein. A method can include receiving, by a computing device, process data from equipment at an industrial site over a period of time, calculating, by the computing device, a rate of change of a process variable associated with a process at the industrial site based on the process data, updating, by the computing device, the rate of change of the process variable with the calculated rate of change, storing the updated rate of change of the process variable in memory of the computing device, determining, by the computing device, an alarm priority, an unsafe level, or an alarm limit based on the updated rate of change, and transmitting the alarm priority, the unsafe level, or the alarm limit to an event and alarm system.

Abstract: A security camera is calibrated by capturing a video of a human moving about a scene. A motion detection algorithm is used to detect the human and a scene specific AI classifier model is trained. One or more AI models is applied to the video and an accuracy score for each of the AI models is determined. The AI model with the highest accuracy score is selected. Detected motion is classified as human or non-human using the scene specific AI classifier model and the selected best AI model. When the classification of the scene specific AI classifier model and the selected best AI model do not match, the selected best AI model is retrained at the remote server using a server hosted AI model as ground truth, and the retrained best AI Model is then sent from the remote server to the security camera for subsequent use.

Abstract: Techniques for performing root cause analysis for alarm events are described. In operation, an indication for performing root cause analysis corresponding to an alarm event for a first asset within an industrial facility is received. A second asset related to the first asset within the industrial facility is then identified based on a hierarchical relationship amongst a plurality of assets within the industrial facility, where the hierarchical relationship is indicative of operational inter-dependability amongst the plurality of assets within the industrial facility, and the hierarchical relationship is stored in a first database instance.

Abstract: Techniques for reconfiguring a data pipeline in a computing environment are described. In operation, a request for modifying a transformation standard of a first data pipeline is received, where the first data pipeline exists between a data ingestion system and a first database instance of a computing environment, and the first data pipeline transforms the data received from the data ingestion system in accordance with the transformation standard. A second data pipeline is then established in parallel to the first data pipeline, the second data pipeline is established between the data ingestion system and the first database instance in response to the request for modifying the transformation standard, and the second data pipeline processes the data received from the data ingestion system in accordance with a modified transformation standard. The second data pipeline is then initiated to transform the data received from the data ingestion system.

Abstract: Techniques for monitoring data synchronization among a plurality of data stores are described. In operation, a first statistic may be received for a first record set received over a first period of time at a first data store. A second statistic may then be obtained for the first record set received over the first period of time at a second data store. Based on the first statistic and the second statistic, a first intermediate state of synchronization may be ascertained between the first data store and the second data store. Further, a first metric associated with a second record set, received over a second period of time at the first data store, and a second metric associated with the second record set, received over the second period of time, may be determined. The determination may be based on the first intermediate state of synchronization. Based on the first metric and the second metric, a second intermediate state of synchronization between the first data store and the second data may be ascertained.

Abstract: Systems, apparatuses, methods, and computer program products for generating one or more monitoring operations are provided. For example, a method provided herein may include causing a component interface to be displayed on a user interface. In some embodiments, the component interface comprises one or more components of a computing application. In some embodiments, the method may include causing a modeling interface to be displayed on the user interface. In some embodiments, the method may include receiving a selection of at least one of the one or more components of the computing application. In some embodiments, the method may include causing an updated modeling interface to be displayed on the user interface. In some embodiments, the updated modeling interface comprises a computing application architecture model. In some embodiments, the method may include applying an analyzer scanning model to the computing application architecture model to generate the one or more monitoring operations.

Abstract: A security camera includes a video camera, one or more power ports and one or more data ports. At least one of the power ports receives power to power the video camera. At least one of the data ports transmits the video streams captured by the video camera onto a network. The security camera includes an in-built drone landing pad that has a drone power port and a drone data port. The drone power port can provide power to the drone and the drone data port can receive video data from the drone when the drone lands on the landing pad of the security camera.

Abstract: Techniques for monitoring data synchronization among a plurality of data stores are described. In operation, a first statistic may be received for a first record set received over a first period of time at a first data store. A second statistic may then be obtained for the first record set received over the first period of time at a second data store. Based on the first statistic and the second statistic, a first intermediate state of synchronization may be ascertained between the first data store and the second data store. Further, a first metric associated with a second record set, received over a second period of time at the first data store, and a second metric associated with the second record set, received over the second period of time, may be determined. The determination may be based on the first intermediate state of synchronization. Based on the first metric and the second metric, a second intermediate state of synchronization between the first data store and the second data may be ascertained.

Abstract: Computer-implemented methods, systems, computing devices, and/or the like are provided. The computer-implemented method may include identifying a raw representation of the source data and a processed representation of the source data; selecting a read mode for reading the raw representation of the source data and the processed representation of the source data; selecting a write mode for writing the raw representation of the source data and the processed representation of the source data, wherein the write mode is based at least in part on the read mode; selecting a process mode for processing the source data, wherein the process mode is based at least in part on the write mode; selecting a representation mode for representing the processed source data; and storing the raw representation of the source data and the processed representation of the source data based at least in part on the representation mode.

Abstract: Techniques for reconfiguring a data pipeline in a computing environment are described. In operation, a request for modifying a transformation standard of a first data pipeline is received, where the first data pipeline exists between a data ingestion system and a first database instance of a computing environment, and the first data pipeline transforms the data received from the data ingestion system in accordance with the transformation standard. A second data pipeline is then established in parallel to the first data pipeline, the second data pipeline is established between the data ingestion system and the first database instance in response to the request for modifying the transformation standard, and the second data pipeline processes the data received from the data ingestion system in accordance with a modified transformation standard. The second data pipeline is then initiated to transform the data received from the data ingestion system.

Abstract: Computer-implemented methods, systems, computing devices, and/or the like are provided. The computer-implemented method may include identifying a raw representation of the source data and a processed representation of the source data; selecting a read mode for reading the raw representation of the source data and the processed representation of the source data; selecting a write mode for writing the raw representation of the source data and the processed representation of the source data, wherein the write mode is based at least in part on the read mode; selecting a process mode for processing the source data, wherein the process mode is based at least in part on the write mode; selecting a representation mode for representing the processed source data; and storing the raw representation of the source data and the processed representation of the source data based at least in part on the representation mode.

Abstract: Systems, apparatuses, methods, and computer program products for generating one or more monitoring operations are provided. For example, a method provided herein may include causing a component interface to be displayed on a user interface. In some embodiments, the component interface comprises one or more components of a computing application. In some embodiments, the method may include causing a modeling interface to be displayed on the user interface. In some embodiments, the method may include receiving a selection of at least one of the one or more components of the computing application. In some embodiments, the method may include causing an updated modeling interface to be displayed on the user interface. In some embodiments, the updated modeling interface comprises a computing application architecture model. In some embodiments, the method may include applying an analyzer scanning model to the computing application architecture model to generate the one or more monitoring operations.

Abstract: A data ingestion system prevents data duplication during a data ingestion operation by determining whether a current instance of an ingestion pending indicator file associated with a data set is present at initialization of the data ingestion operation. Upon determining that no current instance of the ingestion pending indicator file is present, the system generates and stores a new ingestion pending indicator file and performs the data ingestion operation using current watermark data. Upon determining that the current instance of the ingestion pending indicator file is not present, the system generates corrected watermark data and performs the data ingestion operation with respect to the corrected watermark data. Upon completion of the data ingestion operation, the system deletes the current instance of the ingestion pending indicator file.