Intermediate Data Translation for Multi-Format Maintenance AI
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Solution Overview
Problem
Current machine learning and AI models face deployment difficulties due to varying input types, and existing translational approaches are inefficient in handling different formats of input data.
Innovation Solution
A system and method that involve a maintenance task input unit generating input data groups in various formats, with processors identifying the format of each group, preparing an intermediate representation, and modifying it to a common format for use in AI modeling for vehicle maintenance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If current translational approaches are used to handle different input formats, then deployment difficulties are avoided, but the efficiency of translating different types of inputs is poor
Solution Approach 1:
The patent introduces an intermediate representation format that serves as a mediator between diverse input data formats and the AI model's required matrix format. This intermediate format enables efficient translation by providing a standardized stepping stone that simplifies the conversion process while maintaining compatibility with various input types including images, text, and structured data.
2Ease of operation
If a common format is enforced for all input data, then AI model deployment is simplified, but the ability to handle diverse input types is reduced
Solution Approach 1:
The patent segments the data translation process into distinct stages: input reception in various formats, conversion to an intermediate representation, and final transformation to the AI model's matrix format. This segmentation allows each stage to handle specific format requirements independently, maintaining input flexibility while ensuring consistent model deployment through the standardized intermediate representation.
Data Source
AI summary
A system (e.g., a maintenance system) includes a maintenance task input unit and one or more processors. The maintenance task input unit is configured to generate plural input data groups corresponding to a maintenance task. Each of the input data groups is in a corresponding one of plural formats. The one or more processors are coupled to the maintenance task input unit and configured to obtain the plural input data groups from the maintenance task input unit. The one or more processors are configured to identify a particular format of the formats for each input data group, and to prepare an intermediate representation of the input representation based on the particular format that is identified. Also the one or more processors are configured to modify the intermediate representation to provide a model input having a common format. The one or more processors are configured to modify intermediate representations corresponding to each of the input data groups to the common format, and to provide the model input to a maintenance system artificial intelligence modeler that is configured to use the model input to at least one of develop or use a model using the model input for vehicle maintenance.