AI Packing Recommendation System for Package Optimization
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Solution Overview
Problem
Individuals face challenges in selecting the appropriate package type and packing items efficiently for shipment, leading to wasted space, increased shipping costs, and potential damage to items during transit.
Innovation Solution
A method utilizing artificial intelligence, involving machine learning models to process images of items and reference items, and rules-based models to generate recommendations for package types and filler materials based on item dimensions and fragility predictions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of substance
If manual packing selection is used, then individuals can choose package types, but it leads to wasted space, increased shipping costs, and potential item damage
Solution Approach 1:
The system enables self-service by automatically determining optimal package types and filler material requirements through image processing and AI analysis, eliminating the need for manual measurement and selection while minimizing wasted space
Solution Approach 2:
The patent replaces manual mechanical measurement and decision-making with an automated digital system that uses image processing, machine learning models, and rules-based algorithms to determine packing recommendations
2Loss of energy
If manual packing selection is used, then individuals can choose package types, but shipping costs increase
Solution Approach 1:
The system automatically optimizes shipping cost by selecting the most appropriate package type based on item dimensions and carrier requirements, eliminating manual intervention while reducing energy loss in the form of shipping costs
Solution Approach 2:
The system incorporates feedback loops where packing recommendations are generated, evaluated against carrier dimensional weight policies, and refined to minimize shipping costs while maintaining proper item protection
3Reliability
If manual packing selection is used, then individuals can choose package types, but item safety during shipping is compromised
Solution Approach 1:
The system automatically determines item fragility characteristics through image analysis and texture detection, then recommends appropriate filler materials and package types to ensure item safety without requiring manual assessment
Solution Approach 2:
The system proactively identifies fragile items through AI analysis and pre-recommends appropriate filler materials and packaging configurations before shipping, ensuring item protection is built into the packing process from the start
4Ease of operation
If AI image processing is used to determine item dimensions, then packing recommendations are simplified, but processing complexity increases
Solution Approach 1:
The patent introduces an intermediary layer of bounding box generation and dimension calculation that translates complex AI image processing results into simple, actionable packing recommendations, shielding users from the underlying system complexity
Solution Approach 2:
The system creates simplified representations (bounding boxes) of complex image data, copying only the essential dimensional information needed for packing decisions while discarding unnecessary visual complexity
Data Source
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AI summary
In general, various embodiments of the present disclosure provide systems, methods, apparatuses, and technologies, and/or the like for providing novel artificial intelligence (AI) functionality for generating a recommendation on packing an item or combination of items.