Unmanned Vehicle Data Adaptation Layer for Cloud Processing
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Solution Overview
Problem
Data generated in different unmanned vehicle operating environments are in different formats, preventing cloud servers from consistently analyzing and processing data, which leads to inefficiencies and increased code development workloads.
Innovation Solution
A data processing method that acquires data and type information from unmanned vehicle operating environments, uses a pre-stored adaptation repository to apply data transformation logic, and transforms the data into a preset structure for consistent analysis and processing by the cloud server.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data from different unmanned vehicle operating environments are collected in their original formats, then the diversity of data sources is preserved, but the cloud server cannot consistently analyze and process the data
Solution Approach 1:
The patent introduces an adaptation layer as an intermediary component between diverse data sources and the cloud server. This adaptation layer contains adaptation code that transforms data from different operating environments into a unified format, enabling consistent processing while preserving support for multiple data sources. The adaptation layer acts as a mediator that resolves the format incompatibility without requiring changes to the original data sources or the cloud server processing logic.
Solution Approach 2:
The patent applies parameter changes by transforming the data format parameters through the adaptation layer. The adaptation code modifies the structural parameters of the data (such as field names, data types, and organization structure) to convert heterogeneous data formats into a standardized format that the cloud server can consistently process, while maintaining the ability to handle multiple source types.
2Reliability
If custom processing code is developed for each operating environment, then specific data processing requirements are met, but the code development workload increases significantly
Solution Approach 1:
The patent implements universality by creating a unified adaptation layer that handles multiple operating environments through a single standardized interface. Instead of developing separate processing code for each environment, the adaptation layer provides multi-functional capability to process data from various sources using common processing logic, significantly reducing the overall code development workload while maintaining reliable processing for each specific environment.
Solution Approach 2:
The patent applies preliminary action by pre-configuring the adaptation layer with adaptation code for different operating environments before data processing begins. The adaptation code is prepared in advance in the adaptation repository, so when data arrives from any operating environment, the appropriate transformation logic is already in place, eliminating the need for runtime code development or complex environment-specific processing logic.
3Manufacturing precision
If data transformation is performed for each data type, then processing accuracy is improved, but the processing time increases
Solution Approach 1:
The patent applies preliminary action by pre-configuring the adaptation layer with adaptation code for different operating environments before data processing begins. The adaptation code is prepared in advance in the adaptation repository, so when data arrives from any operating environment, the appropriate transformation logic is already in place, eliminating the need for runtime code development or complex environment-specific processing logic.
Solution Approach 2:
The patent uses copying by creating a standardized copy of the data structure through the adaptation layer. Instead of processing each unique data format individually with custom code, the system creates a unified copy of the data in the standard format, which then can be processed efficiently by the cloud server using consistent processing logic, reducing both time and complexity.
Data Source
AI summary
A data processing method based on an unmanned vehicle, the method including acquiring data generated in an unmanned vehicle operating environment of the unmanned vehicle and type information of the unmanned vehicle operating environment; acquiring a data transformation logic corresponding to the type information from a pre-stored adaption repository, which stores data transformation logics corresponding to different type information; and transforming a data structure of the data according to the data transformation logic corresponding to the type information to obtain data in compliance with a preset data structure. By transforming data generated in different unmanned vehicle operating environments into data in compliance with the preset data structure, the cloud server can be assisted in analyzing and consistently processing the data in compliance with the preset data structure after they have been transmitted to the cloud server, thus improving the data processing efficiency.