Revolving Scanning on Tagged Objects: 3D Structure Detection of Logistics Packages via RFID Systems

Abstract

Nowadays, detecting and evaluating the internal structure of packages becomes a crucial task for logistics systems to guarantee reliability and security. However, prior solutions such as X-ray diffraction and WiFi-based detection are not suitable for this purpose. X-ray-based methods usually require manual analysis or image processing algorithms with high complexity, while WiFi-based solutions may fail to detect complex structures due to the significant error of the RF-signal features. In this article, we propose RF-Detector, a low-cost RFID solution for performing three-dimensional (3D) structure detection of items contained in the packages, including the item orientations and relative locations. We thoroughly investigate a brand-new sensing model for RFID-based 3D structure detection, i.e., revolving scanning. We propose not only the fundamental revolving model but also a novel calibration method for the undesired deployments. We have implemented a prototype system to evaluate the performance of RF-Detector. Extensive evaluations in real settings show the effectiveness of RF-Detector, achieving very high accuracy of the internal 3D structure detection.