Image-Based Packed Meat Quality Classification for Online Sales
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Solution Overview
Problem
Existing technologies fail to classify and manage the quality of packed meat based on its invisible back side and internal quality using IoT technology and artificial intelligence, and do not allow for selling packed meat on the Internet based on actual product images.
Innovation Solution
A system and method that uses IoT technology and artificial intelligence to classify the quality of packed meat by analyzing front-surface images, calculate prices, and sell packed meat online based on 'As is' images through a web page or application, allowing consumers to make informed purchases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If quality classification of packed meat is performed based on visible front-surface images only, then the inspection process is simple and fast, but the classification accuracy is insufficient due to inability to assess invisible back side and internal quality
Solution Approach 1:
The patent creates virtual copies (3D models) of the packed meat product by photographing only the visible front surface. Image processing technology generates a complete 3D representation including the invisible back side, allowing quality assessment of the entire product without physically inspecting hidden areas. This copying approach maintains inspection simplicity while achieving comprehensive quality evaluation.
Solution Approach 2:
The patent replaces traditional mechanical inspection methods (which would require opening packs or manual examination) with optical and computational approaches. By using image capture devices combined with image processing algorithms, the system substitutes physical manipulation with digital analysis, achieving accurate quality classification without increasing operational complexity.
2Reliability
If traditional online selling methods are used without actual product images, then the platform operation is simple, but consumers cannot make informed purchases and receive legitimacy cannot be ensured
Solution Approach 1:
The patent performs quality classification and generates detailed product information (including virtual images of the complete product) before the online transaction takes place. This preliminary quality assessment ensures that consumers receive accurate information about the actual product they will receive, building trust and ensuring legitimacy before the purchase is completed.
Solution Approach 2:
The patent creates and provides virtual copies (3D models and images) of the actual packed meat product on the online platform. These digital representations allow consumers to view the complete product including hidden areas, making informed purchasing decisions and ensuring the product received matches what was advertised, thereby guaranteeing legitimacy.
3Measurement precision
If comprehensive quality information including invisible areas is obtained, then classification accuracy improves, but the inspection process becomes more complex and time-consuming
Solution Approach 1:
The patent replaces time-consuming manual inspection or physical examination of the entire product with automated image processing algorithms. The system rapidly generates 3D models and quality assessments from front-surface photographs alone, achieving comprehensive quality evaluation in a fraction of the time required for traditional inspection methods.
Solution Approach 2:
By creating virtual copies through computational algorithms rather than physical examination, the system obtains complete quality information including invisible areas instantly from a single photograph. This copying process eliminates the need for time-consuming manual inspection of each area of the product while maintaining high assessment accuracy.
Data Source
AI summary
A method, device, and system of classifying quality and selling packed meat based on an image are disclosed. The method of classifying quality and selling packed meat based on an image performed by a server includes acquiring an image of each of packed meats, storing each of the packed meats, classifying quality of each of the packed meats based on the image of each of packed meats, calculating a price of each of the packed meats based on the quality classification of each of the packed meats, displaying each of the packed meats by each meat, each part, and each grade on each user terminal, acquiring a purchase request for first packed meat selected by a first user through a first user terminal, determining a sale of the first packed meat, and shipping the first packed meat.