POS Scanner Reconciliation Module for Dual Barcode Data
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Solution Overview
Problem
Point of sale scanners face challenges in accurately processing products with both conventional and Digimarc Barcodes, as they may convey different data, potentially leading to double-charging customers when both are read simultaneously.
Innovation Solution
A scanner system captures multiple frames per second, decodes each frame, and uses a reconciliation module to compare payloads against a cached list to determine semantic equivalence, outputting only the first payload if equivalent payloads are detected within a defined time window to prevent double-reporting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a product includes both conventional barcode and Digimarc Barcode indicia, then scanning flexibility and robustness are improved, but the risk of double-charging and data inconsistency increases
Solution Approach 1:
The system performs preliminary actions by capturing multiple frames before decoding, building a temporal buffer of scanned data. This allows the reconciliation module to compare payloads across frames and identify duplicates before final processing, preventing double-charging while maintaining robust scanning capability
Solution Approach 2:
The reconciliation module acts as an intermediary between the barcode decoding process and the final transaction processing. It receives payloads from multiple decoding operations, compares them for semantic equivalence, and filters duplicates before the data reaches the transaction system, thereby preventing harmful double-charging effects
2Loss of information
If multiple barcodes with different data are read simultaneously, then data completeness is improved, but data consistency and accuracy deteriorate
Solution Approach 1:
The system implements feedback through the reconciliation module, which continuously monitors decoded payloads and compares them against previously captured frames. When semantic equivalence is detected, the system provides feedback by suppressing duplicate payloads, ensuring data consistency while maintaining completeness of unique information
Solution Approach 2:
The system dynamically adjusts its processing based on temporal context. By capturing frames over time and using a sliding window approach, the system adapts to varying scan conditions and payload sequences, maintaining both data completeness and accuracy through dynamic filtering rather than static rejection
Data Source
AI summary
In an illustrative system, a point-of-sale scanner is equipped to respond to multiple different symbologies printed on a single product. The scanner captures many frames per second, as products are swiped through a viewing volume. Each frame is decoded, yielding one or more payloads. A reconciliation module compares each newly-decoded payload against a list of payloads previously output by the module, to determine if the current payload is semantically-equivalent to a previously-output payload. If so, the previously-output payload is output again, in lieu of the just-decoded payload. If no equivalent is found, the current payload is output and added to the list for comparison against future payloads. A great number of other features and arrangements are also detailed.