Automatic payment system
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Solution Overview
Problem
Current point-of-sale systems require human intervention to read barcodes, leading to resource inefficiencies and challenges in store management, particularly in identifying thefts due to poor image quality and storage space limitations for high-quality image capture.
Innovation Solution
An automatic payment system incorporating cameras and ID sensors that recognize product IDs without human intervention, utilizing conveyer stages and sensors to capture images and generate payment information, allowing for high-quality image storage and efficient theft identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a camera captures high-quality images for accurate customer identification, then image quality improves, but storage space requirements increase
Solution Approach 1:
The system applies different image quality standards to different situations: high-quality images are captured only when theft or suspicious activity is detected, while normal shopping activities use lower quality images. This local differentiation of quality requirements resolves the contradiction by allocating storage resources only where high precision is actually needed.
Solution Approach 2:
The camera system dynamically changes image capture parameters (resolution, frame rate, quality settings) based on detected events. During normal operation, low-quality images are captured to minimize storage usage. When theft detection algorithms identify suspicious behavior, the system switches to high-quality image capture mode, thus adapting parameter quality to actual needs rather than maintaining constant high quality.
2Measurement precision
If a POS system uses barcode scanners for product recognition, then product identification accuracy improves, but human resource requirements increase
Solution Approach 1:
The system enables automatic product identification and payment processing without human intervention. The camera captures product images, the ID sensor automatically reads barcodes, and the controller processes payments autonomously. This self-service capability eliminates the need for cashiers to manually scan barcodes, thereby maintaining high identification accuracy while dramatically improving resource efficiency.
Solution Approach 2:
The patent replaces the mechanical manual scanning process with an automated optical and sensor-based system. Instead of human operators physically pointing barcode scanners at products, the system uses cameras to capture product images and ID sensors to automatically detect and read barcodes, substituting mechanical human action with automated technological systems.
3Reliability
If multiple ID sensors are deployed to detect product IDs at different conveyer stages, then product sensing reliability improves, but device complexity increases
Solution Approach 1:
The sensing system is divided into multiple independent ID sensors positioned at different stages of the conveyer belt. Each sensor is responsible for detecting products at its specific location, and the controller integrates information from all sensors. This segmentation allows the system to achieve high reliability through redundant detection opportunities while maintaining manageable complexity by assigning clear, localized functions to each sensor.
Solution Approach 2:
The system performs preliminary product detection at early conveyer stages before products reach the payment area. By detecting and recording product IDs in advance, the system ensures reliable data collection even if some sensors fail or miss readings. This preliminary action creates a buffer that enhances reliability while the modular sensor architecture keeps complexity controlled.
Data Source
AI summary
An automatic payment system includes: first and second conveyer stages arranged along a conveying route on which products are moved; a slope disposed between the first and second conveyer stages on the conveying route; at least one first ID sensor facing the first conveyer stage to sense IDs attached to the products when the products overlap the first conveyer stage; at least one second ID sensor facing the second conveyer stage to sense IDs attached to the products when the products overlap the second conveyer stage; and a bottom ID sensor facing the conveyer route under the slope.