Integrated end-side large-scale intelligent edge computing system
By integrating a large-scale intelligent edge computing system, the problem of high hardware requirements at the edge in traditional road monitoring systems has been solved, achieving the effects of reducing configuration costs and improving data processing efficiency.
CN121963467APending Publication Date: 2026-05-01ANHUI INSTANT INTELLIGENT TECH CO LTD
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Patent Information
- Application Number
- CN202512026845.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-30
- Publication Date
- 2026-05-01
AI Technical Summary
Technical Problem
Traditional road monitoring systems have high hardware requirements at the edge, making it difficult to efficiently differentiate data processing functions, resulting in high configuration costs.
Method used
By adopting an integrated large-scale intelligent edge computing system, node monitoring data is acquired at the edge, and the data is classified and processed. The integrated end is used for data verification and integration, thereby reducing the configuration requirements of the edge end.
Benefits of technology
This approach achieves the goal of reducing the cost of edge hardware configuration while ensuring the ability to process large-scale road monitoring data, thereby improving data processing efficiency and resource utilization.
✦ Generated by Eureka AI based on patent content.
Abstract
The invention discloses an integrated end side large-scale intelligent edge computing system, and relates to the technical field of edge computing, and the system comprises a centralized control center which is in communication connection with an edge end and an integrated end; node monitoring data of the position of each edge node of a road are obtained through an edge end, the node monitoring data are classified, different task nodes are constructed according to different types of node monitoring data, and the task nodes are matched with data processing functions of the edge end. Therefore, the obtained different types of node monitoring data are distributed to the corresponding edge ends according to the matching results of the data types and the data processing functions of the edge ends, so that the edge ends do not need to have the data processing functions of all the data types, data processing of the large-scale edge ends can be completed, and the data processing efficiency is improved. The configuration requirements of the edge ends are reduced, and in large-scale road monitoring, the layout cost of the edge ends can be reduced to the maximum extent, and meanwhile, the data processing capacity of each edge end is ensured.
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