Image-Based Human-Powered Vehicle Component Detection
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Solution Overview
Problem
Current methods lack an efficient means for users to obtain information related to human-powered vehicles, such as components, specifications, and maintenance instructions, directly from images without requiring specialized diagnostic devices.
Innovation Solution
A detecting device equipped with a control unit that executes a machine learning model trained on human-powered vehicle data, allowing users to input images and receive identification information and confidence values for detected components, along with related information like specifications, installation methods, and recommendations, displayed as text or graphical data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a machine learning model is used to detect components from images, then information accessibility is improved, but device complexity increases
Solution Approach 1:
The patent uses an image as an intermediary between the user and the diagnostic system. Instead of requiring users to directly interact with complex diagnostic devices or provide detailed specifications, they simply capture an image of the component, which the system then processes to provide diagnostic information.
Solution Approach 2:
The system creates a digital copy (image) of the physical component and uses this copy for analysis. The image serves as a surrogate that captures all necessary visual information about the component without requiring the actual physical component to be present or measured directly.
2Measurement precision
If specialized diagnostic devices are required for component identification, then measurement precision is improved, but ease of operation deteriorates
Solution Approach 1:
The system performs self-service by automatically analyzing the captured image and identifying components without requiring user expertise or interaction with complex diagnostic tools. The machine learning model autonomously processes the image and provides diagnostic information.
Solution Approach 2:
The patent replaces traditional mechanical or electronic diagnostic devices with an image-based system. Instead of using specialized tools to physically measure or identify components, the system uses visual capture and machine learning algorithms to achieve the same diagnostic function.
3Loss of information
If comprehensive component information is provided, then information completeness is improved, but information processing complexity increases
Solution Approach 1:
The system segments the information provision process by first identifying the specific component in the image, then retrieving and presenting only the relevant information for that component. This avoids overwhelming the user with all possible component information simultaneously.
Solution Approach 2:
The system performs preliminary action by pre-processing and organizing component information in advance. When a component is identified in an image, the system can quickly retrieve and present the relevant pre-organized information without requiring complex real-time processing.
Data Source
AI summary
Provided are a detecting device, a detecting method, a generating method, and a computer-readable storage medium that allow the user to readily obtain information on an object related to a human-powered vehicle. The detecting device includes a control unit that detects an object related to a human-powered vehicle as a target object from a first image including at least a part of the human-powered vehicle, and outputs related information related to the target object.