Data processing method and device, equipment and storage medium

By extracting and processing data based on data list and global message queue in a multi-intelligent component system, converting it into one-dimensional vectors and fusing heterogeneous data, the complexity problem of multi-source heterogeneous data is solved, and efficient and accurate agent perception is achieved.

CN119691209APending Publication Date: 2025-03-25启元实验室
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Patent Information

Application Number
CN202411519467.7
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-10-29
Publication Date
2025-03-25

AI Technical Summary

Technical Problem

The complexity of multi-source heterogeneous data poses great challenges to data processing methods in related technologies, especially in multi-intelligent component systems with complex scenarios, many categories of components, large numbers and many component tasks.

Method used

By extracting data based on the data list and the global message queue, the data is converted into one-dimensional vectors and reorganized, the data order is adjusted and normalized is performed, vector data and image data are fused to obtain heterogeneous fusion data.

Benefits of technology

The effective fusion of multi-source heterogeneous data is realized, which ensures the efficiency and accuracy of the agent's perception process, and solves the complexity challenges of data processing methods in multi-intelligent component systems.

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Abstract

The invention relates to the technical field of data processing, and discloses a data processing method, device and equipment and a storage medium, and the method comprises the steps: carrying out the data extraction based on a data detail list and a global message queue, converting the extracted data into a one-dimensional vector, carrying out the recombination of the one-dimensional vector, and obtaining a recombination data group, the recombined data group is sent to a corresponding data processing module, and the data detail list comprises required data names and data types; the data sequence in the recombined data set is adjusted through a data processing module, normalization processing is conducted on heterogeneous data in the recombined data set after the sequence is adjusted, a preprocessed data set is obtained, and the preprocessed data set comprises vector data and image data; and fusing the vector data, and fusing the fused vector data and the image data to obtain heterogeneous fusion data. According to the method, fusion of multi-source heterogeneous data is realized, and high efficiency and accuracy of the intelligent agent in the sensing process are ensured.
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