Unmanned Store Checkout With AI Recognition and Product Alignment
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The existing product checkout process in stores is inefficient, leading to increased customer waiting times and operational costs due to manual barcode scanning, which causes congestion and requires additional manpower.
Innovation Solution
An unmanned store product checkout system utilizing artificial intelligence learning data, product alignment through rollers, and a combination of barcode and image scanners to enhance product recognition, along with a control unit to manage the transfer, alignment, and classification of products.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual barcode scanning is used for product checkout, then product identification can be performed, but customer waiting time increases and store congestion occurs
Solution Approach 1:
The patent replaces manual mechanical barcode scanning with an automated optical scanning system. The scan unit automatically captures barcode images and product images without requiring manual intervention, thereby maintaining accurate product identification while eliminating the time-consuming manual scanning process that causes customer waiting
Solution Approach 2:
The system implements self-service checkout by automatically performing product identification, image recognition, and checkout processing without requiring store employees. The automated system handles the entire checkout process, reducing customer waiting time while maintaining accurate product identification through multi-modal recognition
2Ease of operation
If manual product checkout is performed by employees, then products can be scanned and processed, but operational costs increase due to hiring additional staff
Solution Approach 1:
The patent implements a fully automated checkout system that performs product scanning, identification, and processing without human intervention. The system uses automatic product detection, barcode scanning, and image recognition to handle checkout operations, eliminating the need to hire additional employees while maintaining ease of operation
Solution Approach 2:
The patent replaces human employees with an automated system comprising scan units, processors, and control units. This substitution eliminates labor costs associated with hiring staff for product checkout while maintaining operational efficiency through automated product identification and processing
3Productivity
If product scanning is performed quickly, then customer waiting time decreases, but product recognition accuracy may be compromised
Solution Approach 1:
The patent divides the product recognition process into multiple independent stages: barcode scanning, image capture, AI-based image recognition, and verification. This segmentation allows each stage to operate at optimized speeds, with parallel processing of multiple products, thereby maintaining high checkout speed while ensuring accurate product recognition through multi-modal verification
Solution Approach 2:
The system performs preliminary actions by capturing both barcode images and product images simultaneously as products pass through the scanning area. The AI model pre-processes and analyzes these images in parallel, preparing recognition results before final verification, thereby maintaining high recognition accuracy without slowing down the checkout process
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A method and an apparatus for product checkout in an unmanned store are disclosed. The apparatus for product checkout in an unmanned store according to an embodiment of the present invention may comprise: a transfer unit for transferring a product; a first product recognition unit for recognizing that the product has been placed on the transfer unit; a height sensor for measuring the height of the product; a weight sensor for measuring the weight of the product; a scan unit for scanning a barcode and an image of the product transferred by the transfer unit; a processor for identifying what the product is, by using artificial intelligence learning data; a product alignment unit for aligning the product to increase a recognition rate of the product; a second product recognition unit for recognizing that the product has arrived at a third point; a product classification unit for classifying the product; and a control unit for controlling operations of the transfer unit, the product alignment unit, and the product classification unit.