Identifying an object's spatial direction (or orientation) plays a fundamental role in a variety of applications, such as automatic assembly, indoor navigation, and robot driving. In this paper, we design a fine-grained direction finding system called Tag-Compass that attaches a single tag to an object (whose size may be small) and identifies the tagged object's orientation by determining the spatial direction of the tag. We exploit the polarization properties of the RF waves used in the communications between an RFID reader and the tag on the object. Polarization mismatch between the tag and the reader's antenna affects the received signal strength at the reader. From the measured signal strength values, we are able to deduce the tag's direction through a series of transformations and deviation minimization. We propose a system design for Tag-Compass and implement a prototype. We evaluate the performance of TagCompass through extensive experiments using the prototype. The experimental results show that Tag-Compass provides accurate direction estimates with a median error of just 2.5° when the tag's position is known and a median error of 3.8° when the tag's position is unknown.

Shelf scanning is one of the most important processes for inventory management in a library. It helps the librarians and library users discover the miss-shelved books and pinpoint where they are, improving the quality of service. By traditional means, however, manually checking each bookshelf suffers from extremely intensive labor and long scanning delay. Although some existing RFID-enabled approaches have been proposed, they suffer from either high-cost infrastructure or complicated system deployment, forming a great barrier to commercial adoption. In light of this, we in this paper propose a smart system called RF-Scanner that can perform the shelf scanning automatically by combining the robot technology and the RFID technology. The former is used for replacing the librarians and liberating them from intensively manual labor. The later is installed on the robot and moves with the robot to scan the on-the-shelf books. We formulate two important issues concerned by librarians, the book localization and the lying-down book detection, and give the sophisticated solutions to them. Besides, we implement RF-Scanner and put it into practical use in our school library. Long-term experiments and studies show that RF-Scanner provides fine-grained book localization with a mean error of just 1.3 cm and accurate detection accuracy of lying-down books with a mean error of 6%.

Radio Frequency Identification (RFID) brings a revolutionary change in a range of applications by automatically monitoring and tracking products. With the proliferation of RFID-enabled applications, multiple readers are needed for ensuring the full coverage of numerous RFID tags. In this paper, we focus on the tag distribution problem in multi-reader RFID systems. The problem is to fast identify the tag set beneath each reader, which is a fundamental premise of efficient product inventory and management. Only with such tag set information can we localize specific tags in a reader and expedite the tag query information collection. As an RFID system usually contains a large number of tags and multiple readers, the traditional solution to identify tags by individual readers is highly time inefficient. We propose an Inference-Based protocol (IB) that identifies the tag distribution based on information inference rules and the aggregated physical signals to improve operational efficiency. In our protocol, three kinds of inference rules based on internal information reported by a single reader, external information shared by multiple readers, and history information retained by the system are fully exploited to infer tag distribution. With these rules, all readers can cooperatively work together and quickly obtain the tag distribution in the system. We also build a prototype RFID system using the USRP-based reader and WISP programmable tags, and then implement the IB protocol. The experimental results and extended simulations show that IB outperforms the state-of-the-art protocols.