Luggage Sorting via OCR Text Recognition
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Solution Overview
Problem
Damaged luggage labels, which often occur during transportation, lead to increased labor costs and delays in sorting and categorization, as barcodes become illegible, necessitating manual reading and potential missed connections.
Innovation Solution
A method for sorting luggage using an identification element in plain text form, where at least one part of the information set is automatically acquired and recognized, and verified against a database, allowing for efficient and labor-saving processing, even with damaged labels, by using optical text recognition and a dynamic database.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If barcode reading is used for luggage sorting, then sorting speed is high, but the system becomes vulnerable to label damage and requires manual intervention
Solution Approach 1:
The patent creates a digital copy of the luggage label content through optical character recognition (OCR) technology. Instead of relying solely on the physical barcode, the system captures an image of the label, converts it to digital text data, and stores this as a backup copy. This digital copy can be processed even if the physical barcode is damaged, ensuring continuous operation without manual intervention.
Solution Approach 2:
The patent introduces an intermediary processing layer between the physical label and the sorting system. The OCR system acts as this intermediary by converting the visual label information into machine-processable data. This intermediary layer protects the main sorting process from label damage by providing an alternative data acquisition path that doesn't depend on barcode integrity.
2Reliability
If manual reading of damaged labels is performed, then sorting can continue, but labor costs increase and delays occur
Solution Approach 1:
The system performs self-service by automatically processing damaged labels through OCR technology without requiring human intervention. The automated system reads the label, extracts the data, and processes the sorting information independently, eliminating the need for manual reading. This self-service capability maintains sorting continuity while preserving high processing efficiency.
Solution Approach 2:
The system incorporates feedback mechanisms that continuously monitor label condition and automatically adjust processing methods. When damage is detected or anticipated, the system switches from barcode-based processing to OCR-based processing, ensuring continuous operation. This feedback-driven adaptation prevents delays by proactively handling damaged labels before they require manual intervention.
3Extent of automation
If barcode-based sorting is used, then automation is high, but the system lacks flexibility for damaged or alternative label formats
Solution Approach 1:
The patent implements a universal labeling system that can handle multiple label formats and conditions through a single integrated approach. The OCR system serves multiple functions: it reads standard barcodes, processes damaged labels, and accommodates various label layouts. This multi-functional capability maintains high automation while significantly improving adaptability to different label conditions and formats.
Solution Approach 2:
The system changes its operational parameters based on label condition. When a label is damaged or non-standard, the system switches from barcode parsing parameters to OCR recognition parameters. This dynamic parameter adjustment allows the automated system to adapt to different label formats and damage levels without losing automation capability, thereby improving both versatility and automated sorting capability.
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
This method enables fast and efficient sorting of luggage, reducing labor costs and delays, as it automatically verifies and matches the information set with database entries, even when barcodes are damaged, ensuring accurate and timely transportation.
Implementation Method 1
at least one part of the information set in the identification element is automatically acquired and also automatically recognized
Data Source
AI summary
Pieces of luggage are sorted which each carries an identification element with a set of information in the form of plaintext. In order to sort pieces of luggage efficiently, at least a portion of the set of information on the identification element is detected automatically and recognized automatically. During an examination, it is automatically verified whether the recognized portion of the set of information matches at least one set of data stored in a database.