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Is Video a Threat to RFID?

Amazon Go is using video, which has great potential to work with RFID—but here's why the technology cannot replace radio frequency identification.
By Mark Roberti

Another question I have is in regard to the cameras' resolution. What happens, for instance, if someone picks up a product that looks very similar to another item, but one is low in sodium and the other is not? Can the cameras distinguish between the two? What if the consumer puts the low-sodium product down in the area where the regular products are stored? Will the system alert the staff that it's in the wrong place? Will the system know when someone buys the low-sodium product, even if it was placed in the same area as the regular version? If not, the system won't help with inventory management.

I have some other questions about the system. How well can it determine the number of items on a shelf? It should be able to alert personnel when a shelf is empty, but can it alert them to replenish when there are only three items left, so that the shelves will never be out of stock?

I have long believed that video would be used to identify bananas, watermelons and other low-priced products that can't easily be tagged with RFID or are too inexpensive to warrant a tag. I think RFID could be used on cases of low-cost goods, and video on the individual units. But video has great limitations. It can't tell you there are only 23 sweaters inside a box that arrives at a store, and not 24. Video can't tell you that a wall of jeans is missing jeans with a 32-inch waist and a 30-inch inseam. It can't tell you that there are no mediums on the rounder with pink shirts, or that a certain size of car tire is not available on the shelf.

These items are too similar for video to distinguish. Since it makes sense to tag these goods at the source and track them through the supply chain, it's going to be far easier to put tags in labels at the point of manufacture and place readers at dock doors than it is to situate video cameras around all the shelves throughout a warehouse.

Still, the Amazon Go system is a major leap forward in retail, as customers don't need to wait online. That's fantastic, and I think it might work well in supermarkets and grocery stores, where the value of the items is cheap and the product packaging is clearly differentiated. Amazon deserves a lot of credit for this breakthrough. Its unique store may jumpstart innovation in retail and finally get retailers to think about the real problem with brick-and-mortar retailing: namely, that shoppers don't find what they are looking for—and, when they do, they need to wait on a line to pay for it.

Mark Roberti is the founder and editor of RFID Journal. If you would like to comment on this article, click on the link below. To read more of Mark's opinions, visit the RFID Journal Blog or the Editor's Note archive.

USER COMMENTS

Ray Adams 2018-02-08 11:45:20 AM
Great article Mark. After seeing a video about Amazon Go, I was sure that RFID was definitely at work making all of the shopping experience possible. Although it was indicated that cameras were in use, the details of tracking product movement just had to be via RFID. I am really shocked to hear they are not using such a proven and mature technology to support this process. As you indicated, cameras can only see so much. One has to wonder, how much "machine learning" tweaking needs to happen whenever a flaw is discovered.
Ben Wild 2018-02-11 05:41:40 PM
Thanks Mark for the great article. I think with cameras coming down in price and machine learning improving every year, camera only based tracking is definitely a threat to RFID for item level tracking in stores. One way that Amazon is making the problem a bit easier to solve is by basically placing large bar codes on each item so that cameras can see them from a distance. I believe that the only physical advantage that RFID has is that radio works in non line of sight situations where as photons don't. But that can be overcome. For example, a camera system can know how many items are on the shelf by counting the number of items that were placed on the shelf minus the number of items that were removed.

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