ML Luggage Tracking Using B-Type Messages for Non-Routine Routing
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Solution Overview
Problem
Current baggage handling processes in travel carriers are inefficient, costly, and resource-intensive, particularly for return flights from high-volume lodging entities like cruise ships, due to the need for manual data entry and printed bag tags, which consume human resources and can lead to errors, and the discarded printed tags lack integration with multi-mode travel systems.
Innovation Solution
A system and method that utilizes a tracking device attached to luggage to store and communicate security screening information, including pseudo IDs and passenger data, allowing for automated luggage tracking and remote check-in across different travel modes, reducing the need for rescreening and manual data entry by leveraging existing IATA-compatible data from discarded printed bag tags.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual data entry and printed bag tags are used for baggage handling, then security screening information can be captured, but human resources are consumed and errors occur
Solution Approach 1:
The patent replaces manual data entry and printed tag systems with an electronic tracking device that automatically stores and transmits security screening information. The mechanical process of printing and manually attaching tags is substituted with electronic data storage and wireless communication, eliminating human error and reducing labor requirements while maintaining security accuracy.
Solution Approach 2:
The tracking device on the luggage performs self-service by automatically storing security screening information and transmitting it to subsequent screening points. This eliminates the need for manual data entry personnel and allows the baggage system to manage its own information autonomously, improving efficiency while maintaining reliability.
2Loss of information
If printed bag tags are discarded after use, then resource waste occurs, but the tags contain valuable data that could be reused
Solution Approach 1:
The patent recovers the valuable data from what would otherwise be discarded printed tags by transferring it to a reusable electronic tracking device. The electronic device retains security screening information throughout the baggage journey, allowing the same data to be reused at multiple screening points without requiring additional printed tags, thus preventing both information loss and material waste.
Solution Approach 2:
The electronic tracking device serves multiple functions: it stores security screening information, transmits data to subsequent screening points, and eliminates the need for repeated printed tags. This multi-functional device replaces the single-use printed tag system, recovering information and reducing material consumption simultaneously.
3Reliability
If rescreening is performed at each travel mode transfer, then security standards are maintained, but processing time increases
Solution Approach 1:
The tracking device performs preliminary action by storing security screening information in advance during the first screening. This pre-captured data is then automatically transmitted to subsequent screening points, allowing secondary screenings to verify against existing data rather than performing full rescreening, thus maintaining security consistency while reducing processing time.
Solution Approach 2:
The system implements feedback by having the tracking device transmit previously captured security information to subsequent screening points. This feedback loop allows later screenings to compare against established data, maintaining security standards through verification while eliminating redundant full-screening processes that would consume time.
Data Source
AI summary
Various methods and systems for training and utilizing machine learning models for tracking a luggage item of a passenger are disclosed. Representative systems may include custom computer architecture for operating a machine learning model utilizing a plurality of reference indicator data sets obtained from a first B-Type message used to train the machine learning model to determine a routine route and a plurality of reference indicator data sets from a second B-Type message used to train the machine learning model to determine a non-routine route relative to the routine route. The model may match first travel information of a passenger name and an International Air Transport Association (IATA) license plate number for a luggage item of a passenger in a manifest with second travel information from a created B-Type message comprising a reference indicator representative of a non-routine routed luggage item and generate delivery instruction of the luggage item.