Intelligent refrigerator and information reminder method based on intelligent refrigerator
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Solution Overview
Problem
Existing intelligent refrigerators do not adequately consider user feelings and safety when managing stored articles, leading to potential misuse or consumption of unqualified or expired products.
Innovation Solution
An information reminding method for an intelligent refrigerator that collects article information during pick-up and placement events, matches it with a dangerous article database, and outputs reminders if the article is deemed unsuitable for use, including lists of negative, forbidden, or expired items, using data from commodity supervision and user health analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If article management functions are provided based on analysis of stored articles, then productivity is improved, but reliability deteriorates because user safety cannot be guaranteed
Solution Approach 1:
The system pre-establishes dangerous article information bases including negative commodity lists, forbidden article lists based on user health states, and expired article lists with predetermined storage life criteria. When articles are placed in the refrigerator, the system proactively compares them against these pre-established databases to issue warnings before harmful consumption occurs, thus ensuring user safety while maintaining management efficiency.
2Reliability
If comprehensive article information collection and matching is performed, then reliability is improved, but device complexity increases
Solution Approach 1:
The dangerous article information base is segmented into three distinct modules: negative commodity list (unqualified products), forbidden article list (health-specific restrictions), and expired article list (storage time violations). This segmentation allows the system to verify articles against multiple criteria independently, improving comprehensive safety verification while maintaining manageable system complexity through modular architecture.
3Reliability
If multiple lists of dangerous articles are maintained, then reliability is improved, but loss of information increases due to data management complexity
Solution Approach 1:
The system merges three separate dangerous article lists (negative commodities, forbidden articles, expired articles) into a unified dangerous article information base. This consolidation integrates multiple safety verification functions into a single database structure, enabling comprehensive safety coverage while reducing data management overhead through centralized storage and unified access protocols.
Data Source
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AI summary
Provided are an intelligent refrigerator and an information reminder method based on an intelligent refrigerator. The information reminder method comprises: acquiring an article pick-up and placement event of an intelligent refrigerator; when the article pick-up and placement event occurs, collecting information of an article, which has changed, in the intelligent refrigerator; carrying out data matching on the information of the article and a dangerous article information base, wherein the dangerous article information base pre-stores a list of articles which a user is recommended to stop using; and if a matching result is that the article, which has changed, is an article in the list of articles, outputting reminder information. When an article is in a list of articles which a user is recommended to stop using, the user is reminded in a timely manner to prevent potential safety hazards, e.g. misusing forbidden products or using unqualified products, thus providing a guarantee for improving the quality of life of the user.