De-personalized Security Screening Image Transfer via AI Extraction
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Solution Overview
Problem
Current baggage handling systems are inefficient and costly, particularly in high-volume settings like cruise ships, where manual processes consume valuable resources and lead to data entry errors and increased costs.
Innovation Solution
The system displays a graphical user interface to register missing or mishandled luggage, accesses security screening images via a unique identifier, and validates the identifier to match the luggage with the passenger, using artificial intelligence to identify contents lists from security screening images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual baggage handling processes are used, then flexibility and adaptability are maintained, but human resource consumption increases and data entry errors occur
Solution Approach 1:
The system creates digital copies of baggage information through security screening images and extracts data from these images to create electronic baggage records. This eliminates manual data entry while maintaining accurate baggage information through automated image-to-data conversion processes.
Solution Approach 2:
The patent replaces manual mechanical processes (staff physically handling baggage tags and entering data) with automated optical and computational systems that capture images and extract information algorithmically, reducing human intervention while increasing processing efficiency.
2Productivity
If automated baggage handling systems are implemented, then productivity increases, but system complexity and initial costs increase
Solution Approach 1:
The security screening imaging system serves multiple functions: it captures images for security purposes and simultaneously provides data for baggage tracking and identification. This multi-functionality increases productivity without requiring separate dedicated systems for each purpose.
Solution Approach 2:
The system uses existing security screening infrastructure to automatically generate baggage tracking data, allowing the system to serve itself by extracting necessary information from images already captured for security reasons, eliminating the need for additional dedicated baggage scanning equipment.
3Measurement precision
If manual data entry is used for baggage tracking, then system simplicity is maintained, but data entry errors increase and accuracy decreases
Solution Approach 1:
The system replaces manual data entry with automated optical character recognition and image processing algorithms that extract baggage information from security screening images, eliminating human error while maintaining system accuracy through computational precision.
Solution Approach 2:
The system validates extracted data against existing baggage records and uses feedback loops to correct discrepancies, ensuring high accuracy in baggage identification while maintaining automated processing through iterative verification processes.
Data Source
AI summary
Embodiments include systems and methods to obtain an International Air Transport Association (IATA) license plate number of a checked luggage item of a passenger and queries a database for a primary identifier (PID) that is associated with a security screening image (SSI) of contents of the checked luggage item or a contents list (CL) derived from the SSI, based on the obtained IATA license plate number. The systems and methods de-personalize security screening image (SSI) file sharing data to comprise the PID and a hyperlink to the database or a secondary shared memory location to access the SSI or the CL. The system and method assemble a communication package that includes the SSI file sharing data. The communication package is devoid of personal identifiable information of the passenger. The systems and methods communicate the assembled communication package to an authorized computer workstation associated with a border-crossing country.