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Gesture recognition has emerged recently as a promising application in our daily lives. Owing to low cost, prevalent availability, and structural simplicity, RFID shall become a popular technology for gesture recognition. However, the performance of existing RFID-based gesture recognition systems is constrained by unfavorable intrusiveness to users, requiring users to attach tags on their bodies. To overcome this, we propose GRfid, a novel device-free gesture recognition system based on phase information output by COTS RFID devices. Our work stems from the key insight that the RFID phase information is capable of capturing the spatial features of various gestures with low-cost commodity hardware. In GRfid, after data are collected by hardware, we process the data by a sequence of functional blocks, namely data preprocessing, gesture detection, profiles training, and gesture recognition, all of which are well-designed to achieve high performance in gesture recognition. We have implemented GRfid with a commercial RFID reader and multiple tags, and conducted extensive experiments in different scenarios to evaluate its performance. The results demonstrate that GRfid can achieve an average recognition accuracy of $96.5$ and $92.8$ percent in the identical-position and diverse-positions scenario, respectively. Moreover, experiment results show that GRfid is robust against environmental interference and tag orientations. [ABSTRACT FROM AUTHOR]

In traditional radio-based localization methods, the target object has to carry a transmitter (e.g., active RFID), a receiver (e.g., 802.11\times detector), or a transceiver (e.g., sensor node). However, in some applications, such as safe guard systems, it is not possible to meet this precondition. In this paper, we propose a model of signal dynamics to allow the tracking of a transceiver-free object. Based on radio signal strength indicator (RSSI), which is readily available in wireless communication, three centralized tracking algorithms, and one distributed tracking algorithm are proposed to eliminate noise behaviors and improve accuracy. The midpoint and intersection algorithms can be applied to track a single object without calibration, while the best-cover algorithm has higher tracking accuracy but requires calibration. The probabilistic cover algorithm is based on distributed dynamic clustering. It can dramatically improve the localization accuracy when multiple objects are present. Our experimental test-bed is a grid sensor array based on MICA2 sensor nodes. The experimental results show that the localization accuracy for single object can reach about 0.8 m and for multiple objects is about 1 m. [ABSTRACT FROM AUTHOR]

The growing importance of operations such as identification, location sensing, and object tracking has led to increasing interests in contactless Radio Frequency Identification (RFID) systems. Enjoying the low cost of RFID tags, modern RFID systems tend to be deployed for large-scale mobile objects. Both the theoretical and experimental results suggest that when tags are in large numbers, most existing collision arbitration protocols do not satisfy the scalability and time-efficiency requirements of many applications. To address this problem, we propose Adaptively Splitting-based Arbitration Protocol (ASAP), a scheme that provides efficient RFID identification for both small and large deployment of RFID tags, in terms of time and energy cost. Theoretical analysis and simulation evaluation show that the performance of ASAP is better than most existing collision-arbitration solutions and the time efficiency is close to the theoretically optimal values. [ABSTRACT FROM AUTHOR]

RFID technologies are gaining much attention as they are attractive solutions to many applications. Localization based on active RFID technologies provides a much needed added-value to further expand the application domain. LANDMARC was the first attempt using active RFID for indoor location sensing with satisfactory results. However, the LANDMARC approach suffers from two drawbacks. First, it does not work well in a closed area with severe radio signal multi-path effects. Second, to further improve the localization accuracy, more reference tags are required which is costly and may trigger the RF interference phenomenon. The proposed VIRE approach can overcome the above drawbacks without any additional cost. Based on the concept of virtual reference tags, a proximity map is maintained by each reader. An elimination algorithm is used to eliminate those unlikely locations to reduce the estimation error. Our experimental results show that the new method consistently enhances the precision of indoor localization from 17 to 73 percent over the LANDMARC approach at different tag locations in different environments. [ABSTRACT FROM AUTHOR]

The objective of private authentication for Radio Frequency Identification (RFID) systems is to allow valid readers to explicitly authenticate their dominated tags without leaking the private information of tags. In previous designs, the RFID tags issue encrypted authentication messages to the RFID reader, and the reader searches the key space to identify the tags. Without key updating, those schemes are vulnerable to many active attacks, especially the compromising attack. We propose a strong and lightweight RFID private authentication protocol, SPA. By designing a novel key updating method, we achieve the forward secrecy in SPA with an efficient key search algorithm. We also show that, compared with existing designs, (SPA) is able to effectively defend against both passive and active attacks, including compromising attacks. Through prototype implementation, we demonstrate that SPA is practical and scalable for current RFID infrastructures. [ABSTRACT FROM AUTHOR]

RFID tag identification is a crucial problem in UHF RFID systems. Traditional tag identification algorithms can be classified into two categories, ALOHA-based and tree-based. Both of them are inefficient due to the incidental high coordination cost. In this paper, we bring CSMA into UHF RFID systems to enhance tag read rate by reducing coordination cost. However, it is not straightforward due to the simple hardware design of passive RFID tags, which is unable to sense the transmissions or collisions of other tags. To tackle this challenge, we propose receiver-based CSMA (RCSMA) in this paper. In RCSMA, the reader notifies the tags channel condition. According to different sensing results of reader's notifications, the tags take corresponding actions, e.g., random back off. RCSMA does not require special RFID tag hardware design. An absorbing Markov chain model is presented to analyze the performance of RCSMA and shown to be consistent with the simulation results. Compared with optimized ALOHA-based algorithms and optimized tree-based algorithms, RCSMA can enhance the tag read rate by 30-70 percent under different reader and tag data rates. [ABSTRACT FROM AUTHOR]

RFID has been gaining popularity due to its variety of applications, such as inventory control and localization. One important issue in RFID system is tag identification. In RFID systems, the tag randomly selects a slot to send a Random Number (RN) packet to contend for identification. Collision happens when multiple tags select the same slot, which makes the RN packet undecodable and thus reduces the channel utilization. In this paper, we redesign the RN pattern to make the collided RNs decodable. By leveraging the collision slots, the system performance can be dramatically enhanced. This novel scheme is called DDC, which is able to directly decode the collisions without exact knowledge of collided RNs. In the DDC scheme, we modify the RN generator in RFID tag and add a collision decoding scheme for RFID reader. We implement DDC in GNU Radio and USRP2 based testbed to verify its feasibility. Both theoretical analysis and testbed experiment show that DDC achieves 40 percent tag read rate gain compared with traditional RFID protocol. [ABSTRACT FROM PUBLISHER]

Counting the number of RFID tags (cardinality) is a fundamental problem for large-scale RFID systems. Not only does it satisfy some real application requirements, it also acts as an important aid for RFID identification. Due to the extremely long processing time, slotted ALOHA-based or tree-based arbitration protocols are often impractical for many applications, because tags are usually attached to moving objects and they may have left the readers interrogation region before being counted. Recently, estimation schemes have been proposed to count the approximate number of tags. Most of them, however, suffer from two scalability problems: time inefficiency and multiple-reading. Without resolving these problems, large-scale RFID systems cannot easily apply the estimation scheme as well as the corresponding identification. In this paper, we present the Lottery Frame (LoF) estimation scheme, which can achieve high accuracy, low latency, and scalability. LoF estimates the tag numbers by utilizing the collision information. We show the significant advantages, e.g., high accuracy, short processing time, and low overhead, of the proposed LoF scheme through analysis and simulations. [ABSTRACT FROM AUTHOR]