Package Routing by Matching Damaged Labels to Similar Parcels
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing package shipping systems struggle to accurately identify and route packages with damaged shipping labels, leading to inefficiencies and delays in delivery.
Innovation Solution
A method involving data processing and machine learning algorithms is employed to match packages with damaged labels to images of undamaged labels by analyzing package characteristics such as weight, color, dimensions, and expected delivery routes, using a sequential application of identification algorithms to narrow down potential matches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional automatic identification methods are used for packages, then the identification process is fast and simple, but packages with damaged labels cannot be identified
Solution Approach 1:
The patent introduces an intermediary identification system that bridges the gap between damaged labels and package routing. When automatic label scanning fails, the system uses intermediaries (packages with intact labels traveling similar routes) to infer the destination of damaged packages by comparing characteristics like package dimensions, weight, and route patterns, thereby maintaining identification reliability without requiring complex manual intervention
Solution Approach 2:
The system creates virtual copies of package data from intact packages that share similar characteristics with damaged packages. By copying routing information from matching intact packages, the system can assign destinations to damaged packages without directly reading their labels, thus preserving identification accuracy while avoiding the need for complex physical label repair or manual reading devices
2Measurement precision
If multiple identification algorithms are applied sequentially to match packages, then the matching accuracy improves, but the computational time and resources increase
Solution Approach 1:
The identification process is segmented into multiple stages with increasing complexity. First, simple filtering algorithms quickly eliminate obviously mismatched packages based on basic characteristics like destination zone or package type. Then, more sophisticated algorithms are applied only to the reduced subset of candidate packages. This segmentation maintains high matching accuracy while significantly reducing overall computational time by avoiding exhaustive comparison of all packages
Solution Approach 2:
The system applies identification algorithms partially rather than exhaustively to all packages. When a damaged package is identified, the system applies multiple algorithms to generate a ranked list of candidate matches, but stops after finding a sufficient number of high-confidence matches rather than evaluating all possible candidates. This partial action achieves adequate matching accuracy without the full computational cost of exhaustive analysis
3Reliability
If data from all packages in the shipping network is analyzed to identify damaged packages, then the identification completeness improves, but the data processing load increases
Solution Approach 1:
Instead of uniformly analyzing all package data across the entire network, the system applies different analysis depths to different packages based on local characteristics. Packages with intact labels receive minimal processing (simple scan), while packages suspected of having damaged labels (based on routing anomalies or physical condition sensors) receive more intensive analysis. This local differentiation ensures identification completeness for problematic packages while minimizing energy consumption on packages that don't require extensive analysis
Data Source
Figure 1
Figure 2A
Figure 2B
AI summary
Methods, systems, and computer-readable storage media for identification and routing of a first package within a shipping network that has a damaged shipping label is described. First data for the first package with the damaged label is obtained. Second data for a plurality of packages within the shipping network is obtained. A particular package from the plurality of packages that matches the first package is identified. The identification is performed by applying one or more identification algorithms to the first data and the second data. Applying the identification algorithms includes obtaining as output from each algorithm a subset of possible matches from among the plurality of packages, the possible matches including packages identified by the one or more identification algorithms as having one or more characteristics similar to the first package. Information from a label of the particular package is used to route the first package through the shipping network.