自动购物车:一次一辆车减少排长队

Kuntal Gorai, S. V S C Santosh, Skanda S, Vijay Murugan A S, Prajwala Tr
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引用次数: 0

摘要

每个人都有过在购物车里排长队结账的经历。有了这个产品,研究工作的目的是减少购物者排队的时间。我们的自动购物车可以减少称重和计费用户想要购买的物品所需的时间和体力劳动。本文开发了一个内置重量传感器的购物车来测量产品的负载,以及一个具有深度学习模型(MobileNetV2和EfficientNetV2)的android应用程序来对所需的商品进行分类。这些模型是在一个有51个类的定制数据集上训练的。手机摄像头用于捕捉产品的图像。模型是用来对这个项目进行分类的。一旦物品被分类,物品的重量就会从称重传感器中得到。执行数据库分析以获得该项目的价格。有了这些详细信息,用户购物完毕就会立即生成账单,而不用排很长的队。
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Automated Shopping Cart: Reducing Long Queues One Cart At A Time
Everyone has experienced waiting in long queues to get their items billed at a shopping cart. With this product, the proposed research work intends to reduce the time spent by shoppers in queues. Our automated shopping cart can reduce the time and manual labor required for weighing and billing the items a user wishes to buy. This article has developed a shopping cart with weight sensors built into the cart to measure the load of the product, and an android application with deep learning models(MobileNetV2 and EfficientNetV2) to classify the required item. The models were trained on a custom-built dataset with 51 classes. The mobile phone camera is used to capture an image of the product. The models are used to classify this item. Once the item is classified, the weight of the item is obtained from the load cells. A database analysis is performed to obtain the price of the item. With these details, the bill is generated as soon as the user is done with shopping without waiting in long queues.
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