Self-Checkout Conveyor Capture With Deferred Item Invoicing
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Solution Overview
Problem
Conventional point of sale systems face challenges in efficiently processing self-checkout transactions, particularly in accurately recognizing and invoicing items, leading to operational inefficiencies and increased labor costs due to the need for manual intervention in identifying unrecognized items.
Innovation Solution
A point of sale system and method that utilizes a conveyor system with item recognition and invoicing capabilities, where items are scanned by sensing devices, with a remote analysis process for items not initially recognized, allowing for automated or manual identification and deferred invoicing, reducing operational costs by leveling workload across locations and leveraging lower labor costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional point of sale systems process self-checkout transactions with immediate item recognition and invoicing, then transaction speed is maintained, but accuracy of item identification decreases and manual intervention increases
Solution Approach 1:
The system performs preliminary capture of item information (images, barcodes, weights) during the transaction, but delays the recognition and invoicing steps until later when expert analysis is available. This allows accurate identification without blocking the customer transaction flow.
Solution Approach 2:
The transaction processing is segmented into separate phases: immediate capture phase (during checkout), deferred recognition phase (remote analysis), and delayed invoicing phase. This segmentation allows each phase to be optimized independently for speed and accuracy.
2Quantity of substance
If remote analysis is performed for unrecognized items, then labor costs are reduced by leveraging lower cost locations, but transaction completion time increases
Solution Approach 1:
Item information is captured preliminarily during the fast checkout process, storing data locally. The actual recognition and invoicing are deferred to remote locations with lower labor costs, eliminating the need for immediate on-site manual intervention.
Solution Approach 2:
A remote analysis system acts as an intermediary between the point of sale and the customer. The system receives captured item data, performs recognition at lower-cost remote locations, and returns results, decoupling the time-sensitive checkout from the time-consuming recognition process.
3Productivity
If automated item recognition is implemented at the point of sale, then operational efficiency increases, but reliability of recognition decreases requiring manual correction
Solution Approach 1:
The system introduces a remote expert analysis intermediary that receives automated recognition results and corrects errors. This multi-layer approach maintains automated processing speed while improving reliability through human expertise when needed.
Solution Approach 2:
The system implements feedback loops where unrecognized or misrecognized items are flagged and sent for remote analysis. The results feed back into the system to improve future automated recognition accuracy and provide correction data for invoicing.
Data Source
AI summary
A novel and useful mechanism and method for processing transactions on a point of sale system comprising of a conveyor system which continuously moves when one ore more items or items are resting on the conveyor system, and a sensing system to capture the information necessary to identify the items on the conveyor. When all items are correctly recognized by the sensing devices, the customer is charged for the items and an invoice is printed. In the event all the items are not correctly recognized the captured information is forwarded to a remote location for automated recognition processing and manual identification, if necessary. Once all the items are successfully identified, the customer is charged for the purchase and an invoice is processed and sent to the customer.