Control method and control system for identifying items stored in an intelligent refrigerator
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Solution Overview
Problem
Existing intelligent refrigerators require large initial databases of item images and identifiers, which are costly and become inaccurate as new items emerge, reducing the effectiveness of item identification.
Innovation Solution
A control method and system that updates a network database in real-time based on user interactions, using image information from refrigerators to match and update item identifications, reducing the need for extensive initial data collection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a large initial database of item images and identifiers is pre-set before refrigerator shipment, then item identification accuracy is improved, but the cost of building and maintaining the database increases significantly
Solution Approach 1:
The system performs preliminary actions by pre-setting a basic database structure and framework before refrigerator shipment, but leaves the actual database content to be populated dynamically during usage. This allows the system to be ready for operation without requiring extensive manual database construction beforehand.
Solution Approach 2:
The refrigerator system automatically captures images of items stored within it using integrated cameras, and these images are automatically added to the database without requiring manual intervention. The system serves itself by continuously expanding its own database through normal operational usage.
2Measurement precision
If a comprehensive database is established before shipment to ensure high identification accuracy, then item recognition precision is improved, but the system becomes outdated as new heterogeneous items appear
Solution Approach 1:
The database transitions from a static pre-loaded structure to a dynamic system that continuously updates itself during refrigerator operation. The database adapts to new items automatically as they are stored, maintaining relevance and accuracy without requiring manual updates or reconfiguration.
Solution Approach 2:
The system implements feedback loops where captured images are continuously compared against the database, and when new item types are detected, the database is automatically updated. This feedback mechanism ensures the system learns from actual usage patterns and adapts to new heterogeneous items that appear over time.
3Measurement precision
If testers manually define and mark large amounts of ingredients before shipment, then identification accuracy is improved, but the time and labor required to build the database increases
Solution Approach 1:
The system eliminates manual database building by automatically capturing, processing, and storing images of items during normal refrigerator usage. The refrigerator performs the database construction task itself over time, completely removing the need for external testers to manually define and mark ingredients before shipment.
Solution Approach 2:
The manual mechanical process of testers physically examining, defining, and marking items is replaced by an automated optical system using cameras and image processing algorithms. The mechanical labor of manual database creation is substituted with automated digital capture and processing.
4Stability of the object's composition
If the database remains unchanged after refrigerator shipment, then system stability is maintained, but identification accuracy decreases as technology advances and new items appear
Solution Approach 1:
The database structure maintains stability through its automated update mechanism, where changes occur systematically through verified image capture and matching processes. The system transitions from static to dynamic operation, allowing controlled evolution of the database while maintaining overall system stability through consistent update protocols.
Data Source
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AI summary
Provided are an intelligent refrigerator and a control method and a control system thereof The control method comprises: receiving, via the network, image information of to-be-identified items sent by the refrigerator; searching the network database on the basis of the image information of the received to-be-recognized items and obtaining identification information matching with the image information of the received to-be-recognized items; and sending the identification information to the refrigerator through the network for displaying through a refrigerator display interface. With the control method and the control system for the intelligent refrigerator, it is possible to increase the amount of data stored in the network database by means of the data fed back by the refrigerator, thus ensuring the accuracy of the background food identification and further enhancing the user experience.