{"id":88212,"date":"2025-02-20T10:42:31","date_gmt":"2025-02-20T02:42:31","guid":{"rendered":"https:\/\/solomon-3d.mesvr.tw\/?p=88212"},"modified":"2025-02-20T11:11:16","modified_gmt":"2025-02-20T03:11:16","slug":"automated-self-checkout-using-ai","status":"publish","type":"post","link":"https:\/\/solomon-3d.mesvr.tw\/de\/anwenderberichte\/automated-self-checkout-using-ai\/","title":{"rendered":"Automatisierter Self-Checkout mit KI"},"content":{"rendered":"
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<\/span>\"iced
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META-aiviFallstudie<\/span><\/h2>\n\n\n\n
Einzelhandel<\/a> | Lebensmittel und Getr\u00e4nke<\/a><\/div>\n<\/div><\/div>\n\n\n\n
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Automatisierter Self-Checkout mit KI<\/h1><\/div><\/div>\n\n\n\n
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Kunde<\/h2>\n\n\n\n

Der Kunde ist eine internationale Kette von Donut-L\u00e4den, die urspr\u00fcnglich in den USA gegr\u00fcndet wurde.<\/p>\n<\/div>\n<\/div>\n <\/div><\/div>\n\n\n\n

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Fall<\/h2>\n\n\n\n
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Verbesserung des Bezahlvorgangs im Einzelhandel<\/h3>\n\n\n\n

Als Reaktion auf die wachsende Nachfrage nach nahtlosen Einkaufserlebnissen im Gesch\u00e4ft wollte der Kunde einen automatisierten Self-Checkout-Prozess einf\u00fchren. Herk\u00f6mmliche manuelle Checkout-Prozesse f\u00fchren oft zu langen Warteschlangen, was sich negativ auf das Kundenerlebnis auswirkt. Durch die Automatisierung dieses Prozesses wollte der Einzelh\u00e4ndler die Effizienz steigern und das Einkaufserlebnis im Gesch\u00e4ft verbessern, indem er die Wartezeiten f\u00fcr die Kunden minimierte.<\/p>\n<\/div>\n<\/div>\n\n\n\n

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\"iced<\/div>\n<\/div>\n<\/div>\n <\/div><\/div>\n\n\n\n
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Herausforderung<\/h2>\n\n\n\n
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\u00dcberwinden von Checkout-Einschr\u00e4nkungen<\/h3>\n\n\n\n

Die Unterscheidung zwischen verschiedenen Donuts und Geb\u00e4ckst\u00fccken ist aufgrund ihres \u00e4hnlichen Aussehens und unterschiedlichen Preises eine Herausforderung, was zu l\u00e4ngeren Kassenzeiten f\u00fchrt. Die Automatisierung des Kassenvorgangs f\u00fcr diese Artikel wird zus\u00e4tzlich dadurch erschwert, dass keine scannbaren Barcodes vorhanden sind, die f\u00fcr herk\u00f6mmliche Self-Checkout-Methoden unerl\u00e4sslich sind. Ohne eindeutige Artikelidentifikation ist die Automatisierung des Scannens und Bezahlens unpraktisch, was den Kassenvorgang noch komplexer macht.<\/p>\n<\/div>\n<\/div>\n <\/div><\/div>\n\n\n\n

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L\u00f6sung<\/h2>\n\n\n\n
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Automatisierter Self-Checkout mit META-aivi<\/h3>\n\n\n\n

Die KI-Technologie META-aivi<\/a> automatisiert das Self-Checkout, indem sie fortschrittliche Klassifizierungs- und Z\u00e4hlalgorithmen verwendet, um auf dem Tablett platzierte Artikel schnell zu erkennen und so den Checkout-Prozess zu optimieren. Das System gew\u00e4hrleistet eine pr\u00e4zise Produktidentifikation und Preisauszeichnung ohne Barcodes oder Kassierer. Durch die Integration in das vorhandene POS-System des Gesch\u00e4fts steigert META-aivi die Effizienz des Einzelhandels, verk\u00fcrzt Wartezeiten, vereinfacht den Checkout und verbessert das Kundenerlebnis.<\/p>\n\n\n\n

<\/div>\n\n\n<\/div>\n<\/div>\n <\/div><\/div>\n\n\n\n
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Ergebnis<\/h2>\n\n\n\n
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<\/path><\/svg>100% Berechnungsgenauigkeit<\/span><\/div>
<\/path><\/svg>Erh\u00f6hter Kundendurchsatz<\/span><\/div>
<\/path><\/svg>Minimiertes Risiko einer Kreuzkontamination<\/span><\/div><\/div>\n<\/div>\n<\/div>\n <\/div><\/div>","protected":false},"excerpt":{"rendered":"

Eine internationale Donut-Kette verbessert die Effizienz an den Kassen durch automatisierte Self-Checkout-Systeme auf Basis k\u00fcnstlicher Intelligenz, verk\u00fcrzt so die Wartezeiten der Kunden und verbessert den Ladenbetrieb.<\/p>","protected":false},"author":36,"featured_media":78158,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_gspb_post_css":"#gspb_heading-id-gsbp-5f6009ef-2b72{font-size:60px;line-height:100px;text-align:center!important;color:var(--gs-colorone);margin-top:50px}#gspb_heading-id-gsbp-5f6009ef-2b72 .gsap-g-line{text-align:center!important}#gspb_heading-id-gsbp-5f6009ef-2b72 .gspb_heading_subtitle,#gspb_subheading-id-gsbp-5f6009ef-2b72{display:block;line-height:22px;margin-top:5px;font-size:30px;color:var(--wp--preset--color--white, 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