Refrigerator Camera-Based User Identification for Inventory Tracking
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Solution Overview
Problem
Users face difficulties in tracking items within a refrigerator appliance, particularly in identifying and quantifying stored items and determining consumption patterns, leading to unnecessary purchases and replenishments due to lack of accurate tracking features.
Innovation Solution
A refrigerator appliance equipped with a camera module and controller that captures images of the chilled chamber, analyzes user interactions, and assigns confidence scores to user profiles to record metadata, enabling automatic identification of users and items added or removed, thus facilitating inventory management and consumption tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If manual item input is required, then item tracking is possible, but user convenience deteriorates and operation complexity increases
Solution Approach 1:
The system performs automatic item tracking through image capture and analysis without requiring user intervention. The camera module continuously monitors the refrigerator interior, and the controller automatically processes images to detect added or removed items, eliminating the need for manual input while maintaining accurate tracking
Solution Approach 2:
The patent replaces manual mechanical input methods with an automated optical system. The camera module captures images and the controller uses image processing algorithms to automatically identify and track items, substituting the mechanical action of manual entry with an automated vision-based system
2Quantity of substance
If scales are used to estimate item quantity, then quantity estimation is possible, but measurement precision deteriorates and reliability decreases
Solution Approach 1:
The patent replaces scale-based mechanical measurement with an optical vision system. The camera module captures images of items, and the controller uses image analysis to detect and count items based on their visual characteristics, providing more precise quantity information without physical contact or weight-based estimation
Solution Approach 2:
The system creates visual copies of items through camera imaging. By capturing and analyzing images of items in the refrigerator, the system can identify and count items based on their visual appearance, providing accurate quantity information without physically interacting with the items through scales
3Adaptability or versatility
If multiple users interact with the refrigerator, then user diversity increases, but tracking accuracy deteriorates due to inability to identify specific users
Solution Approach 1:
The system applies different analysis methods to different regions of the captured images. By identifying which user appendage is interacting with which specific item based on spatial location and motion patterns, the system can accurately attribute item additions or removals to specific users even when multiple users are present
Solution Approach 2:
The system segments the image analysis process by separately detecting and tracking different user appendages. By dividing the overall tracking task into individual appendage tracking tasks, the system can identify which specific user is interacting with items, maintaining accurate user attribution in multi-user scenarios
Data Source
AI summary
A refrigerator appliance may include a cabinet, a door, a camera module, and a controller. The camera module may be mounted to the cabinet. The controller may be operably coupled to the camera module. The controller may be configured to initiate an operation routine. The operation routine may include initiating an image capture sequence at the camera module. The image capture sequence may include a two-dimensional image captured at the camera module. The operation routine may further include determining an appendage-occupied region within the two-dimensional image and analyzing the appendage-occupied region in response to determining the appendage-occupied region. The operation routine may still further include assigning a confidence score to a user profile stored in the controller based on analyzing the appendage-occupied region, comparing the assigned confidence score to a threshold score, and recording metadata regarding the two-dimensional image based on comparing the assigned confidence score.