首页|Patent Issued for Scanner swipe guidance system (USPTO 11928660)

Patent Issued for Scanner swipe guidance system (USPTO 11928660)

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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Toshiba Global Commerce Solutions Hold ings Corporation (Tokyo, Japan) has been issued patent number 11928660, accordin g to news reporting originating out of Alexandria, Virginia, by NewsRx editors. The patent's inventors are Griep, Suzanne M. (Apex, NC, US), Hawk, James I. (Mor risville, NC, US), Hogan, Patricia S. (Raleigh, NC, US). This patent was filed on March 18, 2022 and was published online on March 12, 20 24. From the background information supplied by the inventors, news correspondents o btained the following quote: “Conventionally, when a customer uses a self-servic e kiosk and an error occurs causes an item to not be successfully scanned, the c ustomer attempts to re-scan an item. However, on many occasions, the item is con tinually not successfully scanned, as there is an issue that the customer is not solving when re-scanning the item. For example, a scanner may be dirty or obstr ucted in some way. When this occurs, the item cannot be successfully scanned. Ho wever, a customer may not know the scanner is dirty, leading the customer to con tinue to run the item over the scanner and never being successful in adding it t o customer's transaction. As another example, a customer may not be scanning in a zone which the scanner can read. The customer may be scanning the item too hig h or too low, and the scanner is not capable of reading the bar code. The custom er will continue to pass the item in the same path previously taken over the sca nner, attempting to add the item to the transaction. However, if the same path i s used, the item will never be added to the transaction. These situations lead t o increased frustration and delay in the checkout process.”

BusinessCyborgsEmerging TechnologiesMachine LearningToshiba Global Commerce Solutions Holdings Corporation

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Mar.28)