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IEEE International Conference on rfid Technology and Applications (IEEE rfid-TA)

作者： Sun, Wei Ohio State Univ Dept Comp Sci & Engn Columbus OH 43210 USA

ISBN: (纸本)9781665426572

commodity passive rfid system has been widely used for sensing, localization, gesture recognition and tracking due to its low cost and ubiquity. However, the orientation of rfid tag's body to the reader's directional antenna could significantly affect the sensing performance. In this paper, we will theoretically analyse the impact of orientation in rfid-based sensing. Then, we will propose a signal ratio based algorithm to mitigate the impact of orientation in rfid-based sensing.

关键词： commodity passive rfid system rfid Sensing Orientation-Aware

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RFitness: Enabling Smart Yoga Mat for Fitness Posture Detection with commodity passive rfids 15

RFitness: Enabling Smart Yoga Mat for Fitness Posture Detect...

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IEEE International Conference on rfid (rfid)

作者： Sun, Wei Ohio State Univ Dept Comp Sci & Engn Columbus OH 43210 USA

ISBN: (纸本)9781665440905

Yoga is popular in our daily lives for body fitness practice. We can practice yoga on a specific mat for body fitness. It's important to have the smart yoga mat, which can adjust the surrounding environment based on user's physical activities on the yoga mat. For example, we can adjust the ambient light, music and temperature based on the yoga practitioner's pose on the yoga mat. In this paper, we present RFitness, a system that can detect the fitness posture on the yoga mat. To do so, we can attach multiple commodity passive rfid tags on the yoga mat, such that the different fitness postures can affect different rfid tags. Based on the signal strength readings from all the tags, we can estimate the yoga fitness posture using the model-driven deep neural networks. We implement the prototype of RFitness using commodity passive rfid tags and USRP reader. Our extensive experiments show that RFitness can achieve the median accuracy of 0.96.

关键词： Smart Yoga Mat Fitness Posture Detection commodity passive rfid system Deep Convolutional Neural Network

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Towards Parallel Decoding with Compressive Sensing in Multi-Reader Large-Scale rfid system 15

Towards Parallel Decoding with Compressive Sensing in Multi-...

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IEEE International Conference on rfid (rfid)

作者： Sun, Wei Ohio State Univ Dept Comp Sci & Engn Columbus OH 43210 USA

ISBN: (纸本)9781665440905

The commodity passive rfid system employs slotted ALOHA protocol to interrogate the tags within the reader's communication range. So, at each time slot, there is only one rfid tag communicating with the reader. This degrades the network throughput, especially in large-scale rfid deployments such as warehouses. Recently, parallel decoding techniques are proposed, which can only read less than ten tags at each time slot. So, it is not applicable for warehouse applications, where there are thousands of rfid tags. In this paper, we propose to achieve parallel decoding with compressive sensing technique for multi-reader large-scale rfid system. Since it is difficult to decode the collisions from multiple tags at one reader, we distributively deploy multiple readers. However, we have to consider the inter-reader interference. Even though there are thousands of tags deployed in the large warehouse, they may not backscatter the signals at each time slot simultaneously due to the heterogeneity. Therefore, this sparsity property of backscattering signals can allow us to leverage compressive sensing to decode multiple tags simultaneously with multiple readers. Our simulation results reveal that compressive sensing can efficiently achieve parallel decoding in multi-reader large-scale rfid system.

关键词： commodity passive rfid system Parallel Decoding Multi-Reader Large-Scale rfid system Compressive Sensing

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Short: Liquid thickness sensing with backscattered signals for dysphagia

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Smart Health 2023年 28卷

作者： Sun, Wei Chansarkar, Ishaan Srinivasan, Kannan The Ohio State University 2015 Neil Ave Columbus 43210 OH United States Cornell University Ithaca 14850 NY United States

Dysphagia patients have difficulty swallowing liquids. So, liquid thickness needs to be carefully controlled for dysphagia patients by adding thickening powder to the drink, which can reduce some serious complications such as aspiration pneumonia and frailty. In this paper, we propose RF-Thick, a system that can ubiquitously sense the thickened liquids using commodity passive rfid tags to predict the consecutive liquid thickness level. We discover the sublinear relationship between the differential amplitude obtained from rfid tags and the liquid thickness level. We build a regression model based on this discovery to sense the thickened liquids. To eliminate the impact of different liquid types on thickened liquid sensing, we use the differential amplitude of backscattered signals from rfid tags. To mitigate the multipath effect in dynamic environments (e.g., people moving around), we propose the twin-tag framework consisting of one sensing tag and one reference tag to leverage the differential amplitude for the thickened liquid sensing. We evaluate the performance of RF-Thick across different liquid types (e.g., water, coffee, and tea) and different environments (e.g., office room, classroom, and corridor) with or without people moving around. The experimental results show a good performance of RF-Thick for the thickened liquid sensing. © 2023 Elsevier Inc.

关键词： commodity passive rfid system Dysphagia Liquid thickness sensing

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