“Stealing is buying,” Steve Gu, CEO of startup AiFi, said in an inter-view with The AI Podcast recently, discussing the technology behind grab-and-go stores.So far, Amazon Go is the only successful commercial deployment, but the the parameters of success are tightly controlled.The chances of someone shoplifting is minimized when you control who enters the store, and automatically charge them.Amazon already has an established base of Prime members. All the Go stores so far have been restricted to members, with other retail operations like the Kindle store, which is open to general public, still relying on a manual checkout process.Smaller bodegas, convenience stores, and even several established supermarkets have to build that membership base from scratch.Steve Gu hinted in the aforementioned podcast that there could be a “grab-and-go” section for people willing to download the app, and a separate checkout line for those who don’t want to.It’s not clear how a store’s infrastructure would support both, but potentially, app users could scan once to enter, and once to exit — unlike current process where you only scan your phone once, while entering — ensuring non-app users leave through a separate check-out line.That still leaves the issue of point-of-sale inventory shrinkage like incorrectly billed items or POS theft. China’s Yitu Technology and Toshiba, with its intelligent camera for checkout, are some companies separately working on POS shrinkage.The complexity of preventing theft depends on the size and scale of operations, and type of products on the shelves.Amazon Go stores are only about 1,800 to 3,000 sq. ft, and use hundreds of cameras covering nearly every inch of ceiling space. In comparison, traditional supermarkets can be 40,000 sq. ft. or more.Go, which uses weight sensors on shelves in addition to cameras for visual recognition, currently only offers a limited selection of items, like prepared and packaged meal kits.
25Some things to consider are how floor space will be utilized, especially in densely packed supermarkets, to ensure cameras are optimally placed to track people and items. Loose vegetables and other produce that are billed per pound would presumably rely on sensor tech, but multiple shoppers picking items simultaneously from the same carton would not work with sensors alone. Even pre-packaged or diced vegetables have slight variations in price from one package to another.Apparel too is particularly hard for computer vision systems to track. Identifying the size (S/M/L) and tracking clothes that are easily folded and tucked away are some of the pain points.While startup AiFi promises to utilize existing store infrastructure and a combination of sensors and cameras, Standard Cognition claims to completely do away with sensors, relying solely on machine vision.
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- Spring '19
- Hassan Kasfy