AI Product Checkout Conveyor for Faster Unmanned Store Scanning
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The existing manual product checkout process in stores increases customer waiting time and operational costs due to the need for employee intervention, leading to congestion and inefficiencies.
Innovation Solution
An unmanned store product checkout system utilizing artificial intelligence and a product classification unit with conveyor belts to quickly and accurately identify products using barcode and image scanning, weight measurement, and classification into designated areas based on AI learning data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual product checkout is performed by employees scanning barcodes one by one, then product identification can be performed, but customer waiting time increases and store congestion increases
Solution Approach 1:
The checkout process is divided into multiple independent scanning zones (first scan unit, second scan unit) that operate simultaneously. Products are segmented and processed through different scanning stations in parallel, allowing multiple products to be identified at the same time rather than sequentially, thus reducing customer waiting time while maintaining identification accuracy.
Solution Approach 2:
The manual mechanical process of employees scanning barcodes is replaced with an automated optical scanning system. Multiple scan units with barcode scanners and image scanners automatically detect and identify products as they pass through the conveyor belt, eliminating the need for manual intervention and significantly reducing processing time.
2Measurement precision
If manual product checkout is performed by employees, then product classification can be performed, but operational costs increase due to hiring employees
Solution Approach 1:
The system performs self-service checkout by automatically identifying products through multiple scan units and classifying them using a control unit with AI algorithms. The conveyor belt system automatically guides products through the scanning and classification process without requiring employee intervention, eliminating labor costs while maintaining accurate product classification.
Solution Approach 2:
Manual employee-based classification is replaced with an automated control unit that receives data from multiple scan units and applies AI algorithms to classify products. The system automatically determines product categories and routing based on scanned information, eliminating the need for hired employees while preserving classification accuracy.
3Productivity
If automated checkout system with multiple scan units is implemented, then processing speed increases, but device complexity increases
Solution Approach 1:
The scan units are designed with multi-functionality, combining barcode scanners, image scanners, and weight sensors in a single integrated station. The control unit serves multiple purposes by processing data from different scan units, managing product classification, and controlling the conveyor belt system, thereby reducing overall system complexity despite increased processing capacity.
Solution Approach 2:
Multiple scanning functions (barcode scanning, image scanning, weight measurement) are merged into integrated scan units that operate simultaneously. The control unit consolidates data from all scan units and performs unified product identification and classification, simplifying the system architecture while maintaining high processing speed through parallel operation of multiple sensors.
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
Enables rapid and precise product checkout by increasing recognition rates and improving classification accuracy, reducing operational costs and customer wait times.
Implementation Method 1
a weight sensor installed at a lower one side of the first transfer unit, to measure a weight of the product
Implementation Method 2
a scan unit installed to be spaced apart from the first transfer unit toward the top as much as a preset distance, to scan a barcode and an image of the product transferred by the first transfer unit
Implementation Method 3
an image scanner for acquiring image information by scanning an image of the product
Data Source
Figure 1~2
Figure 3
Figure 4~5
AI summary
Disclosed are a method and an apparatus for product checkout in an unmanned store. The apparatus for product checkout in an unmanned store, according to an embodiment of the present invention, comprises: a first transfer unit that transfers a product; a first product recognition unit that recognizes that the product is placed on the first transfer unit; a weight sensor that measures the weight of the product; a scan unit that scans a barcode and an image of the product transferred by the first transfer unit; a processor that uses artificial intelligence learning data to identify what the product is, on the basis of the barcode and image of the product scanned by the scan unit and the weight of the product measured by the weight sensor; a product classification unit that classifies, on the basis of results of the identification of the product, the product so that the product is classified into a first area or a second area; a calculation unit that calculates a total price; a display unit that provides, to the user, the total price calculated by the calculation unit and a list of products; and a control unit that controls operations of the first transfer unit and the product classification unit.