Master Edge Controller Data Preprocessing for Cloud Analysis
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Solution Overview
Problem
The high cost and resource-intensive data analysis in cloud platforms due to the need for extensive data search and processing of field data from multiple edge controllers in industrial IoT applications, particularly in large factories with multiple production lines.
Innovation Solution
A field data transmission method where a cloud platform determines a master edge controller for each apparatus operation indicator, which preprocesses and sends relevant field data centrally to the cloud platform, reducing the need for extensive data search and processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If all edge controllers upload field data to the cloud platform through a gateway, then the cloud platform can collect comprehensive field data from all production lines, but the cloud platform consumes considerable computing resources for data search and analysis, leading to high costs
Solution Approach 1:
The master edge controller performs preliminary actions by collecting field data from multiple edge controllers, performing data analysis locally to obtain apparatus operation indicators, and uploading only the analyzed results to the cloud platform. This preliminary data processing at the edge eliminates the need for the cloud platform to search and analyze raw field data from all edge controllers, significantly reducing cloud computing resource consumption while maintaining complete data collection capability.
2Measurement precision
If the cloud platform analyzes field data directly from all edge controllers, then accurate apparatus operation indicators can be obtained, but the data analysis cost and time consumption are high
Solution Approach 1:
The master edge controller performs preliminary data analysis to obtain apparatus operation indicators before uploading to the cloud platform. This preliminary action ensures that the cloud platform receives pre-processed, accurate operation indicators rather than raw field data, maintaining measurement precision while significantly reducing the time required for cloud-based data analysis.
3Loss of information
If each edge controller uploads all collected field data to the cloud platform, then complete operating state information is available, but the cloud platform requires extensive data search capabilities, increasing system complexity
Solution Approach 1:
The master edge controller performs preliminary data analysis and information extraction, converting comprehensive field data into structured apparatus operation indicators before transmission to the cloud platform. This preliminary action maintains complete operating state information while transforming the data into a format that eliminates the need for extensive cloud-based data search, thereby reducing system complexity.
Data Source
AI summary
A field data transmission method comprises: a cloud platform determining at least one first device operation index be obtained via data analysis. For each first device operation index, the cloud platform generates control information for the first device operation index. The control information is used to determine a primary edge controller from among at least one edge controller, wherein the primary edge controller is used to send first field data to the cloud platform, the first field data is used for data analysis by the cloud platform to obtain the first device operation index, and the first field data is obtained by the primary edge controller preprocessing second field data. The cloud platform sends each piece of control information to each edge controller, respectively. The cloud platform receives first field data from each primary edge controller, respectively.