Amazon Go’s Technology in Computer Vision and RFID
Amazon Go is a chain of convenience stores operated by the online retailer Amazon. The store itself is cashless, cashierless, and is utilizing advanced technologies, such as computer vision, deep learning algorithms, calibration where each camera has its own location, object recognition, pose analyzation, and activity analysis. Amazon vision wanted to create a market where it requires 0 human resources to operate, therefore people can just go into the store, pick what they want, and just walk out of the store. Clearly this market was quite new to the surrounding and even the world. This computer vision technology was used in some other things such as cars for the sensor, cctv for the person and object recognition, and the newest thing is the trending Camera Glasses, which it can record anything including the voices.
The preparations required by customers are relatively straightforward, first they only need to download the Amazon Go application, go to the nearest shop, then scan the barcode in their phones, which Amazon provided. After the customers scanned their own barcode, they can enter the store,and they can pick whatever they want. The computer vision system captures high-resolution images and utilizes deep learning models to identify and categorize each product accurately. The payment will be done by your electronic wallets that you have registered before, it will automatically cut your money balance. No need to wait in line, just take and walk out. Personalized shopping allows customers to personalized their own shopping list, which the computers track via the customer’s shopping behavior. It can be improved by the algorithms, when a customer has their own schedule of shopping, Amazon Go can provide what they want.
Customers usually can walk inside the store after they scanned their barcode in their Amazon Go’s application, and after they get into the store, every camera and RFID can detect anything they packed and put into their basket. There are lots of technologies that Amazon Go’s using and it’s called RFID and computer vision, person detection, object recognition, and the others are using deep learning algorithms for each customer’s phone. Especially RFID, we all know that RFID it uses radio wave length to track locations, it contains a small antena and a chip that the system can detect everytime it moves or grabbed.The cameras, each of it has its own location and it sends a signal to each customer’s phone what they picked and how much money it is. As we continue to see advancements in computer vision technology, Amazon Go showed a great example on how technology can be used in everyday needs. All of the data are transferred to the computer, then is processed in real-time using machine learning algorithms. Auto-pricing and price optimization are used to dynamically adjust each item’s prices based on various factors, such as brands, demands, and other market conditions. The other machine learning that is quite important is fraud detection, this machine is employed to identify potentially fraudulent activities, such as when customers take or steal an item. These actions can be taken care of by fraud detection, why? Because it has already predicted it will happen, then when the customer walks out of the store, it will still cut their balance. Every items that the customer picked, contains a small chip on their package and this is how Amazon Go can predict and prevent fraud.
In conclusion, Amazon Go provides the advanced offline market for each place. Customers can now go inside of a store then pick whatever they want and go out with their shopping basket. Overall, Amazon Go’s technology infrastructure has the potential to transform the retail landscape by providing a seamless and efficient shopping experience. As technology continues to advance, the scalability also goes higher for each installation, but in this case Amazon Go can make the technology more accessible to a wider range of retailers. This has improved customer experience, because ‘Just Walk Out’ shopping experience eliminates the need of cashiers, lines, and made the shopping experience in an offline store more efficient.
References
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