Bag Tag Optical Character Recognition for Automated Data Entry
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Solution Overview
Problem
Current baggage handling systems are inefficient and costly, particularly for high-volume lodging entities like cruise ships, due to the need for manual processing of luggage tags and the challenges of employee availability and data entry errors, which can lead to increased operational costs and reduced revenue opportunities.
Innovation Solution
A method and system that utilize image processing to create a digital passenger information record from printed bag tags, allowing for the automatic retrieval of return flight information and the printing of new bag tags, reducing the need for manual data entry and minimizing the burden on personnel.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual processing of luggage tags is used, then personnel can handle baggage check-in, but operational costs increase and data entry errors occur
Solution Approach 1:
The patent replaces manual mechanical data entry processes with automated optical character recognition (OCR) technology. Image scanning devices capture bag tag information and automatically convert it to digital text, eliminating the need for personnel to manually type data. This substitution of mechanical/manual operations with automated optical recognition systems directly resolves the contradiction by improving both accuracy (eliminating human error) and efficiency (automating the process).
Solution Approach 2:
The system enables self-service baggage processing where passengers can print their own bag tags at kiosks without requiring counter personnel assistance. The automated OCR system then processes these self-printed tags, allowing the system to serve itself rather than relying on human operators for data entry. This self-service approach improves efficiency by freeing personnel from routine tasks while maintaining high accuracy through automated recognition.
2Productivity
If more employees are hired to handle baggage, then service capacity increases, but employee costs rise and availability challenges persist
Solution Approach 1:
The patent substitutes human workforce with automated imaging and OCR systems for baggage tag processing. Image scanning devices and automated text recognition replace the need for additional employees to handle increased service capacity. This mechanical substitution resolves the contradiction by scaling service capacity through automation rather than hiring, thereby avoiding increased employee costs and workforce management complexities.
Solution Approach 2:
The system changes the operational parameter from human labor capacity to automated processing capacity. By transitioning from employee-based service scaling to technology-based scaling, the system can handle variable volumes of baggage without the constraints of employee availability or the complexities of hiring and training additional staff.
3Ease of operation
If kiosk machines are used for self-printing bag tags, then counter personnel time is freed, but manual data entry is still required
Solution Approach 1:
The patent extends the mechanical substitution principle by replacing the remaining manual data entry step with automated OCR technology. Image scanning devices capture the printed bag tag information and automatically convert it to digital text, eliminating the need for personnel to manually transcribe data from passenger documents. This resolves the contradiction by maintaining passenger self-service benefits while simultaneously improving data processing efficiency through automation.
Solution Approach 2:
The system creates a continuous automated workflow where bag tag printing, imaging, and data extraction occur in seamless succession without requiring manual intervention between steps. The automated OCR system continuously processes images as they are captured, maintaining an uninterrupted flow of data processing that improves overall productivity while preserving ease of operation.
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 approach streamlines the baggage handling process, reducing costs and increasing efficiency by automating data entry and minimizing the time and resources required for luggage processing, enabling seamless check-in and handling of luggage items without the need for extensive human intervention.
Implementation Method 1
obtaining image data representative of at least one image of printed passenger information associated with an airline travel carrier on an originating hardcopy bag tag
Data Source
AI summary
Provided is a system and method of optical character recognition of a bag tag, the method including: a) obtaining, by at least one of at least one processor, image data representative of at least one image of printed passenger information associated with an airline travel carrier on an originating hardcopy bag tag or a printed instrument comprising at least a portion of the printed passenger information on the originating hardcopy bag tag to create a digital passenger information (DPI) data record linked to the airline travel carrier, wherein the originating hardcopy bag tag is issued for a luggage item of a passenger, and wherein the DPI data record comprises an International Air Transport Association (IATA) license plate number, a passenger name record (PNR) number, an airline code, an airline name, a name of the passenger, or any combination thereof; b) accessing, by at least one of the at least one processor, passenger return flight information from a computer system associated with the airline travel carrier, based on the DPI data record; and c) printing, by a printing device, a return leg travel IATA bag tag for a return flight associated with the passenger return flight information.