POS Queue Wait Time Estimation Using Basket Count Detection
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Solution Overview
Problem
Existing technologies fail to accurately provide waiting time information for customers at checkout counters, leading to dissatisfaction due to unpredictable waiting times and neglecting the impact of merchandise quantity.
Innovation Solution
An information processing device and method that detects the number of shopping baskets and calculates a predicted waiting time for each POS device based on this data, incorporating image recognition to estimate merchandise quantity and adjust calculations accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If the number of people in queue is used to estimate waiting time, then the estimation is simple to implement, but the accuracy is low because it does not consider the amount of merchandise
Solution Approach 1:
The patent segments the queue estimation into two independent components: number of people detection and merchandise amount detection. By dividing the estimation task into separate detectable elements (people count and merchandise volume), the system achieves more accurate waiting time prediction while maintaining implementation feasibility through modular detection approaches.
Solution Approach 2:
The patent transitions from one-dimensional queue estimation (only number of people) to two-dimensional estimation by adding merchandise amount as a second dimension. This dimensional expansion allows the system to capture more factors affecting waiting time, significantly improving accuracy without proportionally increasing implementation complexity.
2Device complexity
If only the number of people in queue is detected, then the detection system is simple, but the waiting time information provided to customers is inaccurate
Solution Approach 1:
The patent merges two detection functions (people detection and merchandise detection) into a unified queue estimation system. By combining these detection capabilities, the system recovers the lost information about waiting time accuracy while managing overall system complexity through integrated processing of multiple data sources.
Solution Approach 2:
The detection system is designed with multi-functionality to perform both people detection and merchandise amount detection using similar imaging and processing technologies. This universal approach allows a single system to gather multiple types of queue information without proportionally increasing complexity, thereby reducing information loss.
3Ease of operation
If customers choose queues based on visual observation of queue length, then the selection process is simple, but the actual waiting time may be longer than expected
Solution Approach 1:
The patent implements feedback by providing customers with calculated waiting time information based on detected queue data (number of people and merchandise amount). This feedback loop allows customers to make informed decisions about queue selection, improving the reliability of waiting time predictions while maintaining ease of operation through clear information presentation.
Data Source
AI summary
This information processing device 10 is provided with a product quantity estimating unit 14 (detecting means) and a wait time estimating unit 18: the product quantity estimating unit 14 detects the number of shopping baskets held by people lined up at a product registration device (POS device); the wait time estimating unit 18 calculates a wait time prediction value for each product registration device on the basis of the number of shopping baskets; the product quantity estimating unit 14 detects the shopping baskets, and estimates the quantity of products held by each person lined up at each product registration device; the wait time estimating unit 18 calculates the wait time prediction value for each product registration device on the basis of the quantity of products held by each person lined up at each product registration device.