Exception Handling Station for Automated Data Readers
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Automated checkout systems face delays due to misreads or non-reads of optical codes, known as exceptions, which can occur from damaged codes, obscured or misaligned barcodes, and variations in product sizes and packaging, especially in self-checkout systems where operators may not be familiar with the process.
Innovation Solution
An automated data reading system with an exception handling station that includes a conveying system, imagers, and an image processor to capture and compare visual recognition features of items, allowing unassisted exception handling by customers through image data analysis and display instructions for clearing exceptions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated data readers are used to read optical codes at checkout, then checkout speed and productivity are improved, but exceptions occur due to damaged codes, obscured barcodes, or misaligned items causing delays
Solution Approach 1:
The system creates a visual copy of the item through imaging at the exception handling station. Instead of relying solely on optical code reading, the system captures an image of the item and uses image recognition to identify it, providing an alternative pathway when the optical code fails to read properly.
Solution Approach 2:
The exception handling station acts as an intermediary between the automated data reader and the customer. It captures images of items that fail to be read, processes them through image recognition, and provides assistance to clear exceptions without requiring attendant intervention.
2Productivity
If self-checkout systems are used to reduce labor costs, then operational efficiency is improved, but customers may not be familiar with the process leading to more exceptions and delays
Solution Approach 1:
The exception handling station enables customers to service themselves when exceptions occur. The system automatically captures images, processes them through image recognition, and guides customers through clearing exceptions without requiring attendant assistance, maintaining the self-checkout model while reducing friction.
Solution Approach 2:
The system provides immediate feedback to customers when an exception occurs by displaying the captured image and guiding them through the clearing process. This real-time feedback loop helps customers understand what went wrong and how to fix it, improving their experience with self-checkout systems.
3Reliability
If multiple imaging stations are added to handle exceptions, then exception handling capability is improved, but device complexity increases
Solution Approach 1:
The exception handling station merges multiple functions into a single unit: it captures images of exception items, processes them through image recognition, displays results to customers, and guides them through clearing exceptions. This consolidation provides comprehensive exception handling without requiring multiple separate systems.
Data Source
AI summary
Disclosed are systems and methods for unassisted (i.e., customer controlled) exception handling in an automated data reader having a read zone. A first imager obtains a first image of an exception item in response to an exception generated in a read zone. An exception handling station receives the exception item, and a second imager located at the exception handling station obtains a second image of the exception item. An image processor receives the images, identities visual object recognition features from each image, and compares the features to determine whether the first and second images represent the same exception item. If so, the exception is cleared, and the item is added to a transaction list.