Hybrid Gravity-Image Item Identification for Vending Accuracy
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Solution Overview
Problem
Conventional vending machines based on cargo lane technology are limited in their ability to accurately identify and generate order information for items of various materials and shapes, as they rely solely on weight changes without image recognition, leading to potential errors in item identification.
Innovation Solution
A method and apparatus that utilize gravity sensing data in conjunction with image recognition to identify items taken from a shelf, associating the order information with the user's identity, and employing biometric or code-based identification to enhance accuracy, allowing for the detection of item weight and shape through a combination of gravity sensing and image processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional cargo lane technology is used for item identification, then the device complexity is reduced, but the measurement precision of item identification deteriorates
Solution Approach 1:
The patent combines gravity sensing technology with image recognition technology to create a hybrid identification system. The gravity sensor detects weight changes when items are placed or removed, while the image recognition component captures visual data of the items. By merging these two different sensing modalities, the system achieves more accurate item identification than either method could provide alone, resolving the contradiction between measurement precision and device complexity.
Solution Approach 2:
The system introduces an intermediary processing layer that correlates gravity sensing data with image recognition data. The gravity sensor provides temporal information about when items are added or removed, while the image recognition provides spatial and visual characteristics. The intermediary correlation process matches these data streams to accurately identify specific items, improving measurement precision without requiring a complete redesign of the entire system.
2Reliability
If solely weight change detection is used for item identification, then the device complexity is minimized, but the reliability of order information generation deteriorates
Solution Approach 1:
The patent merges gravity-based weight detection with visual image recognition to create a more reliable identification system. The gravity sensor continuously monitors weight changes to detect when items are placed or removed, while the image recognition system captures visual evidence of the items. By combining these two independent verification methods, the system achieves higher reliability in generating order information, as both methods must agree on the item identity.
Solution Approach 2:
The system implements feedback loops where gravity sensing data and image recognition data continuously cross-validate each other. When the gravity sensor detects a weight change, it triggers image capture, and the resulting image data is used to verify the item identity. This feedback mechanism ensures that order information is only generated when both sensing methods confirm the same item, significantly improving reliability.
3Measurement precision
If image recognition alone is used for item identification, then the measurement precision is improved, but the loss of time in processing increases
Solution Approach 1:
The system uses periodic gravity sensing measurements to trigger image recognition only when necessary. The gravity sensor continuously monitors weight at regular intervals, and only when a weight change is detected does the system activate the image recognition component. This periodic action pattern reduces the overall processing time compared to continuous image recognition, while maintaining high measurement precision through targeted image capture events.
Solution Approach 2:
The gravity sensing system performs preliminary detection of item placement or removal events before activating the more time-consuming image recognition process. By using the fast gravity sensor to pre-identify when identification is needed, the system avoids unnecessary image processing, thereby reducing overall processing time while maintaining accurate item identification through the subsequent image analysis.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach improves the accuracy of order information generation by correlating gravity sensing data with visual identification, enabling the recognition of items of diverse materials and shapes, thus enhancing the reliability and precision of the vending process.
Implementation Method 1
acquiring gravity sensing data of a shelf carrying an item; and identifying, in response to determining that the item on the shelf is taken based on the gravity sensing data
Data Source
AI summary
Embodiments of the present disclosure provide a method and apparatus for generating information, a device for human-computer interaction, and a computer readable medium. The method may include: acquiring gravity sensing data of a shelf carrying an item; and identifying, in response to determining that the item on the shelf is taken based on the gravity sensing data, the taken item based on the gravity sensing data and an acquired image of the taken item, and generating order information of the taken item.