System and method for tracking refrigerator inventory
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Solution Overview
Problem
Existing refrigerators with cameras struggle to accurately track inventory items when they are placed in locations that obscure the camera's view, leading to inaccurate recording of inventory.
Innovation Solution
A refrigerator system with multiple cameras positioned to capture images of items entering or leaving storage compartments, using a computing device to analyze these images and generate bounding boxes around objects of interest, determining their direction of movement based on changes in bounding box size, and updating inventory status accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single camera is positioned inside the refrigerator to monitor inventory, then the device complexity is reduced, but the measurement precision deteriorates when items obscure the camera's view
Solution Approach 1:
The system divides the monitoring task among multiple cameras positioned at different locations (door interior, shelf, ceiling). Each camera captures a specific zone, and the system segments the overall field of view into multiple coverage areas, ensuring that items anywhere in the refrigerator can be detected without requiring a single complex omnidirectional camera.
Solution Approach 2:
The patent transitions from a single-point monitoring approach to a multi-dimensional monitoring network. By placing cameras at various heights, angles, and locations (including the door interior and ceiling), the system creates a three-dimensional coverage map that eliminates blind spots and ensures items are captured from optimal angles regardless of their position.
2Measurement precision
If multiple cameras are positioned to capture all angles of the storage compartment, then the measurement precision improves, but the device complexity increases
Solution Approach 1:
The camera system is designed with multi-functionality where cameras serve dual purposes: capturing items during door opening/closing events and continuously monitoring storage compartments. The computing device processes images from multiple cameras using the same image analysis algorithms, creating a universal processing framework that handles data from any camera position without requiring separate processing pipelines.
Solution Approach 2:
The system performs preliminary actions by capturing images at critical moments (door opening, door closing) when inventory changes are most likely to occur. This event-triggered imaging approach prioritizes capturing items during transitions, reducing the need for continuous high-frequency imaging from all cameras simultaneously, thereby lowering processing complexity while maintaining tracking accuracy.
3Measurement precision
If images are captured continuously to track all item movements, then the measurement precision improves, but the loss of energy increases
Solution Approach 1:
The system implements periodic action by capturing images at specific intervals triggered by door events (opening and closing) rather than continuously. This event-driven periodic imaging captures all inventory changes that occur during door operations while avoiding unnecessary energy consumption during periods when the refrigerator is closed and inventory is stable.
Solution Approach 2:
The computing device uses feedback from image analysis to determine when inventory changes have occurred. By analyzing captured images for item presence, movement, and positioning, the system receives feedback about actual inventory status and adjusts its imaging and processing activities accordingly, avoiding energy waste on processing images when no inventory changes are detected.
Data Source
AI summary
A refrigerator system includes a main body, at least one camera and at least one computing device in operable connection with the camera(s). The camera(s) is/are positioned to have a field of view that includes an entrance opening leading to a storage compartment(s) and is/are configured to capture images of an item being loaded into or being removed from the storage compartment(s). The computing device(s) is/are configured to instruct the camera(s) to capture the images, to analyze the captured images and generate a bounding box around an object of interest in the captured images that contain the object of interest, and to assign a direction of movement for the object of interest being at least one of into, out of or internally within the refrigerated enclosure. The direction of movement is assigned based on changes in size of the bounding box around the object of interest among the analyzed images.