Common Data Pipeline With Metadata for Industrial Automation Context Sharing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Industrial automation systems face challenges in communicating data effectively to external devices due to varying communication protocols and lack of contextual information, leading to network congestion and inefficient data management.
Innovation Solution
A common data pipeline is implemented to organize and characterize data with metadata, enabling secure and uniform communication of data across networks, providing contextual information about the origin and hierarchical levels of industrial automation components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If data is transmitted without characterization and reorganization, then network bandwidth is conserved, but external devices cannot understand or effectively utilize the data due to lack of contextual information
Solution Approach 1:
The patent applies preliminary action by characterizing data with metadata and reorganizing it into standardized formats before transmission. The edge computing device adds contextual information, hierarchical levels, and component associations to data packets in advance, enabling external devices to immediately understand and utilize the data without requiring additional processing or clarification requests.
2Adaptability or versatility
If multiple communication protocols are supported for device compatibility, then adaptability improves, but system complexity increases
Solution Approach 1:
The patent introduces an intermediary layer (the edge computing device and common data pipeline) that translates between various industrial automation protocols and standardized external device protocols. This intermediary characterizes data with universal metadata standards and reorganizes it into common formats, enabling compatibility across different device types without requiring each device to support multiple complex protocols.
3Quantity of substance
If all raw data is transmitted to external devices, then data completeness is improved, but network congestion increases and data management efficiency decreases
Solution Approach 1:
The patent applies the extraction principle by selectively pulling out and transmitting only the most relevant data portions to external devices. The edge computing device analyzes incoming data streams, identifies significant events and anomalies, and extracts only those data points that external devices need for monitoring and analysis. This reduces network traffic while maintaining data completeness for external consumption.
Solution Approach 2:
The patent segments data into organized categories with hierarchical structure before transmission. Data is divided into logical groups (e.g., by component type, hierarchical level, or functional category) and tagged with metadata that enables efficient filtering and processing by external devices. This segmentation allows external devices to request or process only specific data subsets, improving overall data management efficiency.
Data Source
Figure 1~2
Figure 3
Figure 4
AI summary
A non-transitory computer-readable medium includes instructions that, when executed, cause one or more processors of a first electronic device to receive data generated by a plurality of components of an industrial automation system and characterize one or more portions of the data by applying metadata to the one or more portions of the data. The metadata enables a second electronic device receiving the data to determine one or more contexts of the one or more portions of the data. Furthermore, the computer-executable instructions, when executed, cause the one or more processors to rearrange an order of the one or more portions of the data and cause the characterized and rearranged data to be sent to the second electronic device