ShopEye

Abstract

Smart retail stores open new possibilities for enabling a variety of physical analytics, such as users' shopping trajectories and preferences for certain items. This paper aims to excavate three kinds of relations in physical stores, i.e. user-item, user-user and item-item, which provide abundant information for enhancing users' shopping experiences and boosting retailers' sales. We present ShopEye, a hybrid RFID and smartwatch system to delve into these relations in an implicit and non-intrusive manner. The intuition is that inertial sensors embedded in smartwatches and RFID tags attached to items can capture the user behaviors and the item motions, respectively. ShopEye first pairs users with corresponding items according to correlations between inertial signals and RFID signals, and then incorporates these pairs with the motion behaviors of users to further profile user-user and item-item relations. We have tested the system extensively in our lab environment which mimics the real retail store. Experimental results demonstrate the effectiveness and robustness of ShopEye in excavating these relations.