ShopSense:Customer Localization in Multi-Person Scenario With Passive RFID Tags
Pei Wang, Bin Guo, Zhu Wang, Zhiwen Yu
Abstract
Indoor localization serves as the basis of sensing and understanding human behaviors and further providing personalized services in many scenarios, such as retail stores, warehouses and libraries. However, existing indoor localization technologies cannot fulfill the requirement of such scenarios due to incapable of identifying different persons, severe object occlusion when there are multiple persons, or privacy concerns. On the basis of wide deployment of RFID tags in such scenarios, in this paper we develop a RFID-based localization system, i.e., ShopSense, which is not only able to accurately localize multiple people simultaneously but also differentiate them even when there are a lot of obstacles in the environment. Extensive experiments demonstrate that ShopSense can locate the shopping cart at a median tracking error of 20 cm and can locate the customer’s location with a median tracking error of 25 cm.