Checkout Queue Monitoring for Self-Service vs Staffed Guidance
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Solution Overview
Problem
Checkout waiting lines and customer confusion arise in retail stores with mixed self-service and staffed checkout devices, leading to stress and inefficiency.
Innovation Solution
A store monitoring device that uses cameras to identify customers and their items, determines checkout device types based on item quantity and waiting lines, and guides customers to appropriate devices through a display system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple types of checkout devices (self-service and staffed) are installed in the store, then checkout capacity and customer convenience are improved, but customer confusion and stress increase due to not knowing which device to use
Solution Approach 1:
The monitoring device acts as an intermediary between customers and checkout devices. It captures images of customers and their items, determines appropriate checkout device types, and provides guidance information to customers, eliminating the confusion of selecting among multiple device types
Solution Approach 2:
The system provides real-time feedback to customers by displaying guidance information on displays indicating which checkout device type is most suitable for their needs, based on analysis of their items and queue status
2Speed
If customers use self-service checkout devices, then checkout speed is improved, but checkout time increases when customers have large quantities of items requiring manual scanning
Solution Approach 1:
The monitoring device automatically performs the scanning and analysis function that would otherwise require manual intervention. It captures images of items, identifies products, determines quantities, and calculates total values without requiring store staff to manually scan each item
Solution Approach 2:
The system replaces manual mechanical scanning with automated optical recognition. Instead of staff physically scanning items with handheld scanners, the monitoring device uses cameras and image processing to automatically identify and count items
3Measurement precision
If store staff manually scan items at checkout, then checkout accuracy is improved, but labor costs and checkout time increase
Solution Approach 1:
The monitoring device performs the measurement and identification functions automatically. It captures images of items, recognizes product information, determines quantities, and calculates totals without requiring staff intervention for these tasks
Solution Approach 2:
The system substitutes manual visual inspection and mechanical scanning with automated optical recognition and image processing algorithms that rapidly identify and count items with high accuracy
Data Source
AI summary
A store monitoring device includes a memory that stores first information indicating self-service and staffed checkout devices, and a processor configured to: acquire from cameras first images of customers and containers or carts used thereby, second images of a checkout waiting area, identify a first customer and first items to be purchased thereby, determine whether the first customer is in the checkout waiting area, upon determining that the first customer is in the waiting area, determine whether a line is formed in the checkout waiting area, upon determining that a line is formed, determine a first quantity of the first items, when the first quantity is greater than or equal to a threshold, output first information for guiding the first customer to a staffed checkout device, and when the first quantity is less than the threshold, output second information for guiding the customer to a self-service checkout device.