User Tracking Data Lookup for Self-Checkout Item Identification
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Solution Overview
Problem
Self-service retail systems, such as self-checkout, face inaccuracies and high computing resource requirements due to their inability to distinguish between similar items and reliance on manual user input, especially in environments with minimal employee oversight.
Innovation Solution
A method that uses user interaction and movement tracking information, collected through cameras, beacons, or user devices, to identify items selected by users, filter, and sort lookup results, reducing the need for intensive computing and manual input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If vision-based systems are used to automatically identify items, then automation level improves, but computing resource requirements increase substantially
Solution Approach 1:
The patent introduces tracking information as an intermediary data source that bridges user actions and item identification. Instead of directly using resource-intensive vision systems, the system uses tracking data (principle 24) to infer item selection, significantly reducing computing requirements while maintaining automation.
Solution Approach 2:
The patent replaces the mechanical/vision-based item identification system with an information-based tracking system. By substituting camera-based vision processing with tracking data analysis, the system achieves automation with far lower computational overhead.
2Use of energy by moving object
If manual user input is used to identify items, then computing resource requirements decrease, but accuracy decreases due to inability to distinguish similar items
Solution Approach 1:
The patent implements feedback by continuously monitoring tracking information and using it to refine item identification. The system feedback loops between tracking data and item selection, improving accuracy without requiring manual input or heavy computing resources.
Solution Approach 2:
The patent performs preliminary tracking and analysis of user movements before final item identification occurs. By preliminarily processing tracking information to predict item selection, the system achieves accurate identification with minimal computing resources at the moment of lookup.
3Extent of automation
If vision-based systems are used to identify items, then automation improves, but system complexity increases
Solution Approach 1:
The patent extracts the essential function of item identification from the complex vision system and implements it separately using tracking information. By taking out the core identification logic and decoupling it from vision processing, the system achieves automation with reduced complexity.
4Device complexity
If existing lookup systems are used without user context, then system simplicity is maintained, but lookup accuracy decreases
Solution Approach 1:
The patent performs preliminary analysis of tracking information to determine likely item selections before the lookup occurs. This preliminary action provides contextual accuracy without complicating the lookup system itself, maintaining simplicity while improving precision.
Data Source
AI summary
The present disclosure provides techniques for curating search results. A first request to look up an identifier for an item is received from a first user, and first tracking information corresponding to movements of the first user in a physical space is retrieved. At least one item associated with the first user while moving in the physical space is identified from the first tracking information. A first identifier of the at least one item is determined, and the first identifier is provide to the first user.