Novel retail shrinkage/theft prevention approach for scan-&-go self checkout
Novel retail shrinkage/theft prevention approach for scan-&-go self checkout
批准号:
10055849
负责人:
金额:
$35.27万
依托单位:
依托单位国家:
英国
项目类别:
Collaborative R&D
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --
中文摘要
随着社会日益数字化和自动化,自助扫描和自助结账等解决方案越来越受欢迎。他们给顾客选择的自由和更好的服务,同时,店主可以节省成本。但在这一切的背后,自动扫描带来了一个巨大的挑战:盗窃造成的萎缩。由于担心收缩,全球最大的零售商最近的部署要么放缓,要么完全放弃。市场上的解决方案不能满足需求。这些都有其局限性,例如闭路电视需要工作人员的持续监督才能立即发现盗窃,RFID标签和电子物品监控(EAS)标签并不适用于所有产品,也没有大规模部署。许多商店试图通过部署更多员工进行更多的购物篮检查来解决这个问题,最终带来了更多的摩擦和成本。MishiPay允许购物者用智能手机扫描并支付购物费用,而不是浪费时间在收银台排队。有了MishiPay的技术,购物者已经可以用自己的手机扫描商品上的条形码,用多种支付方式付款,然后简单地离开商店。该项目将开展研究,以比目前的方法更有效地解决收缩问题。我们将创建一个计算机视觉(CV)模型,扫描闭路电视的镜头,可以确定客户正在扫描的物品数量,并与MishiPay应用程序篮子进行交叉检查。该技术将在商店进行试验,以评估其有效性。
英文摘要
With an increasingly digital and automated society, solutions like self-scanning and self-checkouts at stores have become increasingly popular. They give customers freedom of choice and better service whilst at the same time, store owners can save cost. But behind all this, there is one big challenge that comes with self-scanning: shrinkage due to theft. Recent deployments by the world's largest retailers have either slowed down or completely been abandoned due to shrinkage concerns. Solutions that are on the market do not satisfy the need. These have their limitations, e.g. CCTV needs constant supervision by staff to pick up theft immediately, RFID tags and Electronic Article Surveillance (EAS) labels do not fit on all products and have not been deployed at scale. Many stores have tried to solve this problem by deploying more staff to do more basket checks eventually bringing more friction and cost.MishiPay empowers shoppers to scan and pay for their shopping with their smartphones, rather than wasting time queuing at the checkout. With MishiPay's technology, shoppers can already use their own phone to scan the barcode on items and pay for them using a wide variety of payment methods, then simply leave the store.This project will conduct research to address the shrinkage problem far more effectively than current methods. We will create a computer vision (CV) model that scans footage from CCTV and can determine how many items a customer is scanning and cross check that with the MishiPay App basket. The technology will be trialled in store to evaluate its effectiveness.
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