Modern logistics systems face increasing difficulty in identifying counterfeit products, fraudulent returns, and hazardous items concealed within packages, yet current package screening methods remain too slow, expensive, and impractical for widespread use. This paper presents TagLabel, an RFID based system that determines both the orientation and contents of packages using low cost passive UHF tags. By analyzing how materials change RSSI and phase, the system identifies the contents of a package without opening it. Using orientation inferred from phase differences, tag occlusion, and antenna gain patterns, the system selects the tag with the greatest occlusion for accurate material sensing. We evaluate two and three tag configurations, and show that both can deliver high orientation and material sensing performance through the use of machine learning classifiers, even in realistic RF environments. When combined into a unified pipeline, TagLabel achieves more than 80 percent accuracy across all package orientations. Because it requires only standard RFID hardware and offers fast scanning times, this approach provides a practical way to enhance package inspection and improve automation in logistics operations.

翻译：现代物流系统在识别假冒产品、欺诈性退货以及隐藏在包裹内的危险物品方面面临日益严峻的挑战，而现有的包裹筛查方法仍存在速度慢、成本高且难以大规模应用的局限性。本文提出TagLabel，一种基于RFID的低成本无源超高频标签系统，可同时确定包裹的朝向与内容物。通过分析材料对接收信号强度指示（RSSI）和相位的影响，系统无需拆封即可识别包裹内物品。利用相位差推断的朝向信息、标签遮挡效应及天线增益模式，系统选择遮挡最显著的标签以实现精确的材料感知。我们评估了双标签与三标签配置，结果表明即使在真实射频环境中，结合机器学习分类器，两种配置均能实现高精度的朝向与材料感知性能。在集成统一处理流程后，TagLabel在所有包裹朝向上均达到超过80%的准确率。由于仅需标准RFID硬件且具备快速扫描能力，该方法为提升包裹检测效率和推动物流作业自动化提供了实用解决方案。