Digital Twin of Retail Stores with RFID Tags Localization

In this work, we integrate digital twin technology with RFID localization to achieve real-time monitoring of physical items in a large-scale complex environment, such as warehouses and retail stores. To map the item-level realities into a digital environment, we proposed a sensor fusion technique that merges a 3D map created by RGB-D and tracking cameras with real-time RFID tag location estimation derived from our novel Bayesian filter approach. Unlike mainstream localization methods, which rely on phase or RSSI measurements, our proposed method leverages a fixed RF transmission power model. This approach extends localization capabilities to all existing RFID devices, offering a significant advancement over conventional techniques. As a result, the proposed method transforms any RFID device into a digital twin scanner with the support of RGB-D cameras. To evaluate the performance of the proposed method, we prototype the system with commercial off-the-shelf (COTS) equipment in two representative retail scenarios. The overall performance of the system is demonstrated in a mock retail apparel store covering an area of 207 m
²
, while the quantitative experimental results are examined in a small-scale testbed to showcase the accuracy of item-level tag localization.