Wine Label Recognition and Sound Mapping for Faster Selection
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Solution Overview
Problem
Existing wine cellar systems fail to recommend wines that match the user's current situation effectively, as they do not consider the characteristics of numerous wines stored and require manual lookup of wine characteristics.
Innovation Solution
An electronic apparatus equipped with a camera, processor, memory, and neural network models to identify wine characteristics from images or sounds, generating sounds corresponding to these characteristics, and adjusting rack positions or outputting recommendations based on user input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If the wine cellar stores numerous wines with various characteristics, then the wine selection variety increases, but it becomes difficult for users to identify and look up wine characteristics manually
Solution Approach 1:
The wine cellar system automatically identifies and provides wine characteristic information without requiring manual user lookup. The system uses image recognition to capture wine labels, automatically extracts characteristic information, and presents personalized recommendations based on user preferences and current context, making the system self-serve the information needs of users.
Solution Approach 2:
The patent replaces manual mechanical operations (physically searching through wines, manually reading labels, and looking up characteristics) with automated image recognition and AI-based information processing systems. The camera captures wine labels and the system automatically processes the information, substituting human manual work with automated computational processes.
2Measurement precision
If the system provides detailed wine characteristic information, then the accuracy of wine recommendations improves, but the complexity of the system increases
Solution Approach 1:
The wine cellar system integrates multiple functions into a single unified platform: image capture of wine labels, automatic recognition and extraction of characteristic information, user preference analysis, contextual situation assessment, and personalized recommendation generation. This multi-functional integration achieves high recommendation accuracy while managing system complexity through consolidation.
Solution Approach 2:
The system introduces an AI-based image recognition and information processing intermediary between the physical wine collection and the user. This intermediary automatically extracts characteristic information from wine labels and processes it through algorithms that consider user preferences and contextual factors, mediating between the large quantity of wine data and the user's information needs without requiring direct user interaction with the complexity.
3Measurement precision
If the system manually looks up wine characteristics, then the information accuracy is maintained, but the time required for wine selection increases
Solution Approach 1:
The system performs preliminary actions by pre-processing and storing characteristic information from wine labels during initial scanning and registration. When users make selections, the system has already captured and organized the relevant data, enabling instant retrieval and personalized recommendation generation without requiring time-consuming manual lookup during the actual selection moment.
Solution Approach 2:
The patent replaces the manual mechanical process of looking up wine characteristics with automated image recognition and digital information retrieval. The camera captures wine labels and the system automatically processes and retrieves characteristic information through computational algorithms, substituting human manual search operations with automated electronic processes that occur in real-time.
Data Source
AI summary
An electronic apparatus may include: a camera; memory storing instructions and at least one processor including processing circuitry. The instructions, when executed by the at least one processor individually or collectively, may cause the electronic apparatus to: obtain an image comprising an object, using the camera; identify characteristic information about the object; and generate a first sound corresponding to the object based on the characteristic information.