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Revamping Supermarkets With AI and RSSi*

机译:用AI和RSSI改造超市*

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摘要

Super markets are mushrooming in every city as shopping has became a daily activity. An average person goes to shopping 1.6 times in a week and spends approximately 40 minuets there per visit. This sums up to around 60 hours every year. Around 15 of the time spent in the supermarkets is wasted due long billing queues and weighting for the turn. On public holidays and special discount days, there will be a significant upsurge in the number of customers. With the present system it sometimes becomes difficult to manage the rush. The traditional way of shopping in which people put the articles in the shopping cart and wait in the long queues at the billing counter is being followed pretty much since the opening of first supermarket. This paper proposes a feasible and cost effective method to save time and reduce queues at the billing counters with Artificial Intelligence. The goal is to design a shopping cart which uses AI and IoT to scan the product as soon as it is kept in the cart. People have been already developing these carts using RFIDs for years but the proposed project isn’t just about RFIDs. It is a complete evolution of a shopping cart altogether using TensorFlow’s object detection. This will save time and make shopping easier and better. It’ll also help stores to make more profits and help the customers save money at the same time.
机译:随着购物成为日常活动,所有城市都在蘑菇蘑菇。普通人在一周内购物1.6次,每次访问大约花费约40米。这笔总和每年左右约60小时。在超市中花费的15次浪费大约15次浪费了长期的计费队列和转弯加权。在公众假期和特殊折扣日,客户数量将存在显着的巨大。随着目前的系统,有时变得难以管理匆忙。传统的购物方式,其中人们将物品放在购物车中并在结算柜台的长队中等待,自第一个超市开放以来。本文提出了一种可行且具有成本效益的方法,以节省时间并减少具有人工智能的计费计数器的队列。目标是设计一种购物车,它一旦保存在购物车中,就可以使用AI和IoT扫描产品。多年来,人们已经使用RFID开发了这些推车,但拟议的项目不仅仅是RFID。使用Tensorflow的对象检测,它是一个完整的购物车的进展。这将节省时间,使购物更容易,更好。它还可以帮助商店制作更多利润,并帮助客户同时节省资金。

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