Settlement Terminal Reading Control to Prevent Unintended Card Scans
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Solution Overview
Problem
Multi-settlement-type terminals often unintentionally read cards using unintended reading options, causing customer confusion and potentially affecting reward points due to incorrect reading functions.
Innovation Solution
A settlement terminal with a control unit that forecasts the intended reading unit based on customer actions, using machine learning models to analyze images of the customer operating the terminal, and cancels the ready state of non-intended reading units.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If multiple reading units are provided in a ready state for customer convenience, then the ease of operation is improved, but unintended readings occur causing customer confusion
Solution Approach 1:
The control unit forecasts which reading unit the customer will use before the actual reading occurs, and pre-cancels the ready state of other reading units. This preliminary action prevents unintended readings before they can happen, resolving the contradiction between maintaining multiple ready units for convenience and preventing customer confusion from unintended readings.
2Productivity
If multiple reading units remain in ready state, then settlement speed is maintained, but reward point allocation accuracy deteriorates
Solution Approach 1:
The system performs preliminary forecasting of the intended reading unit and proactively cancels ready states of non-intended units before the reading transaction occurs. This ensures that only the correct reading unit remains active, guaranteeing accurate reward point allocation based on the intended reading function while maintaining settlement speed through automated rapid state changes.
Data Source
AI summary
According to one embodiment, a settlement terminal includes a control unit which forecasts which one of the plurality of reading units will be used to perform settlement using a credit card, identifies which reading units are presently in a ready state, then cancels or turns off the ready state of the reading units other than the forecasted one. In general, the forecast may be provided by analysis of a picture of the customer at the settlement terminal holding the credit card prior to operation of the settlement terminal. The control unit may implement machine learning, such as a neural network for analysis of the picture and providing of the forecast.