Processing method for industrial internet identification analysis data

By optimizing industrial internet identifier resolution data processing through edge computing and blockchain technology, problems such as latency, resource waste, and insufficient security in traditional methods have been solved. This has enabled rapid response, secure and efficient data processing and cross-domain collaboration, and improved the depth of data analysis and system flexibility.

CN121967443APending Publication Date: 2026-05-01CHINA NAT INST OF STANDARDIZATION
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Patent Information

Application Number
CN202411522187.1
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-10-29
Publication Date
2026-05-01

AI Technical Summary

Technical Problem

Traditional industrial internet identifier resolution data processing methods suffer from problems such as data transmission and processing delays, resource waste, insufficient security, privacy risks, data silos, lack of innovation, inflexible systems, integration difficulties, insufficient in-depth analysis, and poor real-time performance.

Method used

By using edge computing to analyze data in real time, dynamically adjust data stream processing strategies, integrate multi-sensor data, create digital twins, conduct sentiment analysis, use blockchain to ensure data security, create cross-industry data sharing platforms, and optimize storage and resource allocation.

Benefits of technology

Reduce data transmission latency, improve response speed and resource utilization, enhance data security, promote cross-domain collaboration and innovation, reduce storage costs, improve the depth of data analysis and understanding of user feedback, and enhance system flexibility and overall work efficiency.

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Abstract

The invention discloses a processing method for industrial internet identification analysis data, and the method specifically comprises the following steps: 1, carrying out the data processing near a device or a sensor, reducing the delay and bandwidth consumption, analyzing the data in real time, generating feedback, achieving the real-time decision through edge calculation, reducing the dependence on a cloud end, and improving the response speed; 2, dynamically adjusting a data stream processing strategy according to a real-time analysis result, preferentially processing important data, reducing unnecessary data processing burden, processing the data by adopting an event-driven mode, and triggering corresponding processing logic based on a specific event; the data transmission delay is reduced, the response time is shortened, the real-time processing capability is improved, unnecessary calculation is reduced, and the resource utilization rate is improved; the data security is enhanced by adopting a block chain technology, and the non-tampering and traceability of the data are ensured; the decision quality is improved through self-adaptive data stream processing, and the strategy is dynamically adjusted through real-time data.
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