Image Recognition Commodity Proposal System
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Solution Overview
Problem
Conventional systems struggle to provide optimal commodity proposals to users as they cannot grasp commodities purchased from other companies, leading to difficulties in offering useful proposals.
Innovation Solution
A consumer item procurement support system that uses image recognition techniques to collect and register unpurchased commodity information, allowing users to select and register purchased items, thereby enhancing commodity proposals by incorporating data on items not originally from the company's inventory.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional systems use purchase history and behavior data to predict commodities, then commodity proposals can be made based on existing data, but the system cannot grasp commodities purchased from other companies
Solution Approach 1:
The patent introduces image recognition technology as an intermediary to capture commodity information from the user's environment (shopping carts, store shelves, etc.). This intermediary enables the system to access unpurchased commodity data from other companies without requiring direct integration with those companies' systems, thus resolving the information loss problem while managing complexity through a specialized technical module.
Solution Approach 2:
The patent replaces traditional mechanical data collection methods (relying on users to input purchase history) with automated image recognition technology. The system uses cameras and AI-based object recognition to automatically identify and register commodities in the user's environment, eliminating the need for manual data entry and expanding data collection capabilities to include items from other companies.
2Measurement precision
If the system collects comprehensive commodity data including unpurchased items, then commodity proposals become more accurate, but data collection becomes more difficult
Solution Approach 1:
The system enables self-service data collection by allowing the image recognition system to automatically capture and register commodity information from the user's shopping cart and environment without requiring active participation or input from the user. The system serves itself by autonomously detecting, recognizing, and storing commodity data, thereby achieving accurate measurements while reducing collection difficulty.
Solution Approach 2:
The patent substitutes manual data collection methods with automated image recognition technology. Instead of requiring users to manually input or select commodity information, the system uses computer vision and AI algorithms to automatically detect and identify commodities in images taken from the user's environment, significantly improving measurement precision while reducing collection difficulty.
Data Source
AI summary
A consumer item procurement support system capable of performing a more appropriate commodity proposal and the like is provided. The consumer item procurement support system includes an information processing server that communicates with a terminal of a customer, and manages a taken image of a commodity (consumer item) captured by the terminal of the customer, wherein the information processing server: executes a recognition process of the commodity (consumer item), based on the taken image of the commodity (consumer item) captured by the terminal of the customer; displays, on the terminal of the customer, one or more commodity candidates extracted as a result of execution of the recognition process; and determines an unpurchased commodity, by allowing the customer to select an actually purchased commodity from among the commodity candidates.