Cognitive prediction of shopping cart contents by analyzing customer movement patterns (P)
Publication Date: 2017-May-29
The IP.com Prior Art Database
TITLE: Cognitive prediction of shopping cart contents by analyzing customer movement patterns At modern retails stores it is important to have as much information as possible on contents of customer cart when he/she approaches checkout. For most goods it's not a big problem - we have barcodes. But certain types of goods are hard to tell apart from one another and also it's impossible to put barcode on them. This includes, but is not limited to vegetables, fruit, baker's goods etc. We propose a method to boost certainty about user having or not having given gods in his shopping cart.
We propose to use customer location tracking information combined with shop layout information to narrow down possible goods in shopping cart or exclude certain goods (in reality this will not be complete exclusions, as someone could hand in a product for customer). Let's use a simple embodiment to show how system works. Assume that shop offers 3 kinds of apples, each having slightly different price (and shop also wants to monitor inventory). Those apples are also hard to tell apart from one another by the checkout assistants. To allow easy recognition those apples are placed such that customer movement tracking technology shop uses (wifi(MAC)/bluetooth/cameras etc.) can, without any problem tell that customer was in close proximity to one of those places. During checkout, system sees customer has some apples in his cart and performs analysis - usually location data will reveal where (close to wh...