GRfid: A Device-Free RFID-Based Gesture Recognition System

Zou, Yongpan; Xiao, Jiang; Han, Jinsong; Wu, Kaishun; Li, Yun; Ni, Lei

doi:10.1109/tmc.2016.2549518

Cited by 144 publications

(57 citation statements)

References 23 publications

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“…However, sensor nodes [26][27][28][29][30][31][32][33][34][35][36][37][38][39][40] more easily fail to work than traditional network nodes due to being battery-powered. Therefore, it is a challenge to maintain high quality and low energy consumption in WSN applications.…”

Section: Discussionmentioning

confidence: 99%

ANCR—An Adaptive Network Coding Routing Scheme for WSNs with Different-Success-Rate Links

Xiang

Wang

et al. 2017

Applied Sciences

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Abstract:As the underlying infrastructure of the Internet of Things (IoT), wireless sensor networks (WSNs) have been widely used in many applications. Network coding is a technique in WSNs to combine multiple channels of data in one transmission, wherever possible, to save node's energy as well as increase the network throughput. So far most works on network coding are based on two assumptions to determine coding opportunities: (1) All the links in the network have the same transmission success rate; (2) Each link is bidirectional, and has the same transmission success rate on both ways. However, these assumptions may not be true in many actual WSNs-the wireless links among nodes are often subject to all kinds of disturbance, obstruction, etc., and may transmit with different success rates. This paper proposes a new routing strategy, named Adaptive Network Coding Routing (ANCR). ANCR firstly establishes a routing path with the traditional network coding routing (NCR), and then applies the neighborhood search algorithm to adaptively determine nodes' coding opportunities based on the links' transmission success rates, with the target of reducing the total number of transmission. The simulation results show that, in WSNs with different-success-rate links, ANCR can reduce the network delay by about 50%, and increase the network throughput by about 67%, compared with the traditional NCR.

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Section: Discussionmentioning

confidence: 99%

ANCR—An Adaptive Network Coding Routing Scheme for WSNs with Different-Success-Rate Links

Xiang

Wang

et al. 2017

Applied Sciences

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“…Sun et al [16] studied the mobile usage prediction problem using feature comparison analysis. To realize a dynamic home screen application, Shin et al [17] built a prediction model [18,19] for the usage of apps in mobile context. Zhu et al [20] studied service usage patterns from the perspective of users and proposed an application usage prediction method.…”

Section: Related Workmentioning

confidence: 99%

Exploring the Evolution of New Mobile Services

Chen

Yao

Jin

et al. 2017

Scientific Programming

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The emergence and widespread use of mobile Internet technology has led to many different kinds of new mobile communications services, such as WeChat. Users could have more choices when attempting to satisfy their communications needs. The ability to predict the way in which users will use new mobile communications services is extremely valuable to mobile communications service providers. In this work, we propose a method for predicting how a user will use a new mobile service. Our scheme is inspired by the evolutionary game theory. With large-scale real world datasets collected from mobile service providers, we first extract the benefit-related features for users who were starting to use a new mobile service. Then we design our training and prediction methods for predicting potential users. We evaluate our scheme using experiments with large-scale real data. The results show that our approach can predict users' future behavior with satisfying accuracy.

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“…It is fairly essential yet challenging when taking the accuracy and instantaneity into account. As a matter of fact, there are many proven segmentation techniques such as KL divergence [6], foreground detection [24], Modified Varri Method [30] and so on. In this paper, we devise a FSM based action detection algorithm exploiting the distinction of signal features.…”

Section: Action Detectormentioning

confidence: 99%

“…ShopMiner [24] harnesses the unique spatial-temporal correlations of time-series phase readings from backscatter signals of passive RFID tags to detect and record comprehensive shopping behaviors. GRfid [30] can recognize six device-free gestures by capturing the spatial phase features of various gestures. However, all of them are built on onerous training or prestored profiles, which is quite time-consuming and labor-tensive.…”

Section: Activity and Gesture Recognitionmentioning

confidence: 99%

See 1 more Smart Citation

TagController

Ding

Zhang

et al. 2017

Proceedings of the 14th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services

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Innovative Human Machine Interface technologies are fundamentally reshaping the way people live, entertain and work. Passive RFID tags, benefiting from its wireless, inexpensive and battery-free sensing ability, are gradually being applied in new-style interaction interfaces, ranging from virtual touch screen to 3D mouse. This paper presents TagController, a universal wireless and battery-free remote controller with two types of interactive actions. The key insight is that the fine-grained phase information extracted from RF signals is capable of perceiving various actions. TagController can recognize 10 actions without any training or prestored profiles by executing a sequence of functional components, i.e. preprocessor, action detector and action recognizer. We have implemented TagController with COTS RFID devices and conducted substantial experiments in different scenarios. The results demonstrate that TagController can achieve an average recognition accuracy of 95.8% and 94.3% in the scenarios of one and two remote controllers, respectively, which promises its feasibility and robustness. CCS CONCEPTS• Human-centered computing → Ubiquitous and mobile computing systems and tools; KEYWORDS Battery-free remote controller, action recognition, COTS RFID ACM Reference format:

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GRfid: A Device-Free RFID-Based Gesture Recognition System

Cited by 144 publications

References 23 publications

ANCR—An Adaptive Network Coding Routing Scheme for WSNs with Different-Success-Rate Links

ANCR—An Adaptive Network Coding Routing Scheme for WSNs with Different-Success-Rate Links

Exploring the Evolution of New Mobile Services

TagController

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