Multi-source data processing method, system and equipment oriented to city-level digital twinning

By generating intelligent data packets and dynamically deciding and generating computing paths on heterogeneous computing nodes, the problem of rigid computing resource scheduling and low resource utilization in the multi-source sensing data processing of city-level digital twins is solved, and low-latency and efficient data processing is achieved.

CN122152536APending Publication Date: 2026-06-05LIANBANG NETWORK TECH SERVICE NANTONG CO LTD
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Patent Information

Application Number
CN202610526245.0
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-04-21
Publication Date
2026-06-05

AI Technical Summary

Technical Problem

In existing city-level digital twin multi-source sensing data processing, there are problems such as rigid scheduling of computing resources and difficulty in balancing data processing latency and resource utilization.

Method used

Intelligent data packets are generated using multi-source sensing devices. The computing path is generated by dynamically deciding on heterogeneous computing nodes in the on-the-go computing network, data processing tasks are executed, and the data is mapped to the city's digital twin model in real time.

Benefits of technology

It enables flexible scheduling of computing resources, balancing low latency in data processing with high resource utilization.

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Abstract

The invention discloses a multi-source data processing method, system and device oriented to city-level digital twinning, and relates to the field related to data processing.The method comprises the steps that in response to an original data stream obtained from a multi-source sensing device, an intelligent data packet in which original sensing data and calculation task description information are packaged is generated; the intelligent data packet is injected into an in-transit computing network, and each heterogeneous computing node starting from an entrance edge node executes a dynamic decision of the computing node based on computing task description information and a real-time load of the node itself to generate a computing path; and executing a data processing task on the nodes of the calculation path, and mapping a result data packet to a corresponding entity state in the urban digital twin model in real time. The technical problems that in existing multi-source data processing, computing power resource scheduling is rigid, data processing time delay and the resource utilization rate are difficult to consider are solved, and the technical effects that computing power resources are flexibly scheduled, and low data processing time delay and the high resource utilization rate are considered are achieved.
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