Lost Item Management System Using Image Recognition and Scoring
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Solution Overview
Problem
The air transport industry faces significant challenges in efficiently managing and reuniting lost items with passengers due to high volumes of lost property, unclear ownership processes, and the lack of a global database for found items, leading to increased liability, staff workload, and negative passenger experiences.
Innovation Solution
A lost item management system that uses image recognition to generate metadata for found and lost items, a scoring system to match items, and a cloud-based platform for registration and repatriation, enabling self-service portals for passengers and stakeholders, and integrating with delivery and payment modules for efficient item return.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual processes are used to manage lost property, then staff can handle item tracking and passenger enquiries, but operational costs and staff workload increase significantly
Solution Approach 1:
The patent replaces manual mechanical processes with automated digital systems. Image recognition technology automatically captures and processes images of lost items, extracting metadata without human intervention. The matching engine automatically compares item descriptions and images to identify potential matches, eliminating the need for staff to manually track and match items with passengers.
Solution Approach 2:
The system enables self-service functionality where passengers can independently report lost items through the platform, upload photos, and receive automated notifications when matches are found. This reduces the burden on staff who previously had to handle all passenger enquiries manually.
2Adaptability or versatility
If multiple stakeholders maintain separate databases for lost property, then each organization can manage its own records, but global matching capability is reduced
Solution Approach 1:
The patent creates a universal platform that allows multiple stakeholders (airlines, airports, ground handling companies) to access and contribute to a shared lost property database. The system maintains data from various sources while providing unified search and matching capabilities across all participants, enabling both local and global item recovery.
Solution Approach 2:
The system merges data from multiple separate stakeholder databases into a unified platform. By combining item records, images, and metadata from different sources into a single searchable database, the system enables comprehensive matching that spans across organizational boundaries while maintaining data integrity.
3Productivity
If automated image recognition is implemented, then matching speed and accuracy improve, but system complexity increases
Solution Approach 1:
The system performs preliminary actions by automatically capturing images of lost items at the point of discovery and immediately extracting metadata such as color, material, and distinctive features. This pre-processing of image data before the matching process begins reduces the computational burden during actual matching operations and speeds up the overall system response time.
4Reliability
If extensive item verification processes are used, then repatriation accuracy increases, but processing time increases
Solution Approach 1:
The system applies partial verification by first performing automated matching based on image recognition and metadata comparison. Only items with high-confidence matches proceed to full verification steps, while lower-confidence matches receive additional scrutiny. This selective approach maintains accuracy for clear matches while reducing processing time for ambiguous cases.
Data Source
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AI summary
A system and method for managing lost items is described. The system comprises an application that receives information associated with one or more found items, which includes an image of each found item, and item-related information associated with a lost item. An image processing module identifies metadata associated with each found item based on the image of each found item and the received information associated with each found item. A matching engine determines a score for each found item based on a comparison between the item-related information for the lost item and the metadata associated with each found item.