Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.最新文献_第9页

TransFloor: Transparent Floor Localization for Crowdsourcing Instant Delivery TransFloor:面向众包即时交付的透明地板定位

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. Pub Date : 2022-01-01 DOI: 10.1145/3569470

Zhiqing Xie, Haiyong Luo, Xiaotian Zhang, Hao Xiong, Fang Zhao, Zhaohui Li, Qi Ye, Bojie Rong, Jiuchong Gao

{"title":"TransFloor: Transparent Floor Localization for Crowdsourcing Instant Delivery","authors":"Zhiqing Xie, Haiyong Luo, Xiaotian Zhang, Hao Xiong, Fang Zhao, Zhaohui Li, Qi Ye, Bojie Rong, Jiuchong Gao","doi":"10.1145/3569470","DOIUrl":"https://doi.org/10.1145/3569470","url":null,"abstract":"Smart on-demand delivery services require accurate indoor localization to enhance the system-human synergy experience of couriers in complex multi-story malls and platform construction. Floor localization is an essential part of indoor positioning, which can provide floor/altitude data support for upper-level 3D indoor navigation services (e.g., delivery route planning) to improve delivery efficiency and optimize order dispatching strategies. We argue that due to label dependence and device dependence, the existing floor localization methods cannot be flexibly deployed on a large scale in numerous multi-story malls across the country, nor can they apply to all couriers/users on the platform. This paper proposes a novel self-evolving and user-transparent floor localization system named TransFloor , based on crowdsourcing delivery data (e.g., order status and sensors data) without additional label investment and specialized equipment constraints. TransFloor consists of an unsupervised barometer-based module– IOD-TKPD and an NLP-inspired Wi-Fi-based module– Wifi2Vec , and Self-Labeling is a perfect bridge between both to completely achieve label-free and device-independent floor positioning. In addition, TransFloor is designed as a lightweight plugin embedded into the platform without refactoring the existing architecture, and it has been deployed nationwide to adaptively launch real-time accurate 3D/floor positioning services for numerous crowdsourcing couriers. We evaluate TransFloor on real-world records from an instant delivery platform (involving 672,282 orders, 7,390 couriers, and 6,206","PeriodicalId":20463,"journal":{"name":"Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.","volume":"144 1","pages":"189:1-189:30"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80413889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

VULoc: Accurate UWB Localization for Countless Targets without Synchronization VULoc:无同步的无数目标精确超宽带定位

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. Pub Date : 2022-01-01 DOI: 10.1145/3550286

Jing Yang, Baishun Dong, Jiliang Wang

{"title":"VULoc: Accurate UWB Localization for Countless Targets without Synchronization","authors":"Jing Yang, Baishun Dong, Jiliang Wang","doi":"10.1145/3550286","DOIUrl":"https://doi.org/10.1145/3550286","url":null,"abstract":"Ultra-WideBand (UWB) localization has shown promising prospects in both academia and industry. However, accurate UWB localization for a large number of tags (i.e., targets) is still an open problem. Existing works usually require tedious time synchronization and labor-intensive calibrations. We present VULoc, an accurate UWB localization system with high scalability for an unlimited number of targets, which significantly reduces synchronization and calibration overhead. The key idea of VULoc is an accurate localization method based on passive reception without time synchronization. Specifically, we propose a novel virtual -Two Way Ranging (V-TWR) method to enable accurate localization for an unlimited number of tags. We theoretically analyze the performance of our method and show its superiority. We leverage redundant ranging packets among anchors with known positions to infer a range mapping for auto-calibration, which eliminates the ranging bias arising from the hardware and multipath issues. We finally design an anchor scheduling algorithm, which estimates reception quality for adaptive anchor selection to minimize the influence of NLOS. We implement VULoc with DW1000 chips and extensively evaluate its performance in various environments. The results show that VULoc can achieve accurate localization with a median error of 10.5 cm and 90% error of 15.7 cm, reducing the error of ATLAS (an open-source TDOA-based UWB localization system) by 57.6% while supporting countless targets with no synchronization and low calibration overhead.","PeriodicalId":20463,"journal":{"name":"Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.","volume":"3 1","pages":"148:1-148:25"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82541267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

PrinType: Text Entry via Fingerprint Recognition PrinType:通过指纹识别的文本输入

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. Pub Date : 2022-01-01 DOI: 10.1145/3569491

Zongjian Liu, Jieling He, Jianjiang Feng, Jie Zhou

引用次数: 0

DiverSense: Maximizing Wi-Fi Sensing Range Leveraging Signal Diversity DiverSense:利用信号分集最大化Wi-Fi传感范围

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. Pub Date : 2022-01-01 DOI: 10.1145/3536393

LI YANG

{"title":"DiverSense: Maximizing Wi-Fi Sensing Range Leveraging Signal Diversity","authors":"LI YANG","doi":"10.1145/3536393","DOIUrl":"https://doi.org/10.1145/3536393","url":null,"abstract":"The ubiquity of Wi-Fi infrastructure has facilitated the development of a range of Wi-Fi based sensing applications. Wi-Fi sensing relies on weak signal reflections from the human target and thus only supports a limited sensing range, which significantly hinders the real-world deployment of the proposed sensing systems. To extend the sensing range, traditional algorithms focus on suppressing the noise introduced by the imperfect Wi-Fi hardware. This paper picks a different direction and proposes to enhance the quality of the sensing signal by fully exploiting the signal diversity provided by the Wi-Fi hardware. We propose DiverSense, a system that combines sensing signal received from all subcarriers and all antennas in the array, to fully utilize the spatial and frequency diversity. To guarantee the diversity gain after signal combining, we also propose a time-diversity based signal alignment algorithm to align the phase of the multiple received sensing signals. We implement the proposed methods in a respiration monitoring system using commodity Wi-Fi devices and evaluate the performance in diverse environments. Extensive experimental results demonstrate that DiverSense is able to accurately monitor the human respiration even when the sensing signal is under noise floor, and therefore boosts sensing range to 40 meters , which is a 3 × improvement over the current state-of-the-art. DiverSense also works robustly under NLoS scenarios, e.g. , DiverSense is able to accurately monitor respiration even when the human and the Wi-Fi transceivers are separated by two concrete walls with wooden doors. between transceivers and the distance between transceivers is 11m. We close the door during the experiment. We ask the subject to sit in Room A (S1, S3, S4, S5) and breath normally. Results show that the mean absolute error is 0.15bpm, 0.09bpm, 0.16bpm, 0.22bpm, respectively. We then move Tx to T5 and there are","PeriodicalId":20463,"journal":{"name":"Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.","volume":"55 1","pages":"94:1-94:28"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84460485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

AEROKEY: Using Ambient Electromagnetic Radiation for Secure and Usable Wireless Device Authentication AEROKEY:使用环境电磁辐射进行安全可用的无线设备认证

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. Pub Date : 2022-01-01 DOI: 10.1145/3517254

Kyuin Lee, Yucheng Yang, Omkar Prabhune, Aishwarya Lekshmi Chithra, Jack West, Kassem Fawaz, Neil Klingensmith, Suman Banerjee, Younghyun Kim

{"title":"AEROKEY: Using Ambient Electromagnetic Radiation for Secure and Usable Wireless Device Authentication","authors":"Kyuin Lee, Yucheng Yang, Omkar Prabhune, Aishwarya Lekshmi Chithra, Jack West, Kassem Fawaz, Neil Klingensmith, Suman Banerjee, Younghyun Kim","doi":"10.1145/3517254","DOIUrl":"https://doi.org/10.1145/3517254","url":null,"abstract":"Wireless connectivity is becoming common in increasingly diverse personal devices, enabling various interoperation- and Internet-based applications and services. More and more interconnected devices are simultaneously operated by a single user with short-lived connections, making usable device authentication methods imperative to ensure both high security and seamless user experience. Unfortunately, current authentication methods that heavily require human involvement, in addition to form factor and mobility constraints, make this balance hard to achieve, often forcing users to choose between security and convenience. In this work, we present a novel over-the-air device authentication scheme named AeroKey that achieves both high security and high usability. With virtually no hardware overhead, AeroKey leverages ubiquitously observable ambient electromagnetic radiation to autonomously generate spatiotemporally unique secret that can be derived only by devices that are closely located to each other. Devices can make use of this unique secret to form the basis of a symmetric key, making the authentication procedure more practical, secure and usable with no active human involvement. We propose and implement essential techniques to overcome challenges in realizing AeroKey on low-cost microcontroller units, such as poor time synchronization, lack of precision analog front-end, and inconsistent sampling rates. Our real-world experiments demonstrate reliable authentication as well as its robustness against various realistic adversaries with low equal-error rates of 3.4% or less and usable authentication time of as low as 24 s. .","PeriodicalId":20463,"journal":{"name":"Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.","volume":"23 1","pages":"20:1-20:29"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82197084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

WiNE: Monitoring Microwave Oven Leakage to Estimate Food Nutrients and Calorie 葡萄酒:监测微波炉泄漏以估计食物的营养和热量

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. Pub Date : 2022-01-01 DOI: 10.1145/3550313

A. Banerjee, K. Srinivasan

{"title":"WiNE: Monitoring Microwave Oven Leakage to Estimate Food Nutrients and Calorie","authors":"A. Banerjee, K. Srinivasan","doi":"10.1145/3550313","DOIUrl":"https://doi.org/10.1145/3550313","url":null,"abstract":"Food analytic and estimation of food nutrients have an increasing demand in recent years to monitor and control food intake and calorie consumption by individuals. Microwave ovens have recently replaced conventional cooking methods due to efficient and quick heating and cooking techniques. Users estimate the food nutrient composition by using some lookup information for each of the food’s ingredients or by using applications that map the picture of the food to their pre-defined dataset. These techniques are often time-consuming and not in real-time and thus can result in low accuracy. In this paper, we present WiNE , a system that introduces a new technique to estimate food nutrient composition and calorie content in real-time using microwave radiation. Our system monitors microwave oven leakage in the time and frequency domains and estimates the percentage of nutrients (carbohydrate, fat, protein, and water) present in the food. To evaluate the real-world performance of WiNE, we build a prototype using software-defined radios and conducted experiments on various food items using household microwave ovens. WiNE can estimate the food nutrient composition with a mean absolute error of ≤ 5% and the calorie content of the food with a high correlation of ∼ 0.97. and time-frequency domains.","PeriodicalId":20463,"journal":{"name":"Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.","volume":"8 1","pages":"99:1-99:24"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88768100","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

MicroFluID: A Multi-Chip RFID Tag for Interaction Sensing Based on Microfluidic Switches 微流体:一种基于微流体开关的交互传感多芯片RFID标签

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. Pub Date : 2022-01-01 DOI: 10.1145/3550296

Wei Sun, Yuwen Chen, Yanjun Chen, Xiaopeng Zhang, Simon Zhan, Yixin Li, Jie Wu, Teng Han, Haipeng Mi, Jingxian Wang, Feng Tian, Xing-Dong Yang

引用次数: 0

Sensurfaces: A Novel Approach for Embedded Touch Sensing on Everyday Surfaces Sensurfaces:一种在日常表面上嵌入触摸传感的新方法

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. Pub Date : 2022-01-01 DOI: 10.1145/3534616

Brice Parilusyan, M. Teyssier, Valentin Martinez-Missir, Clément Duhart, Marcos Serrano

引用次数: 6

UltraSpeech: Speech Enhancement by Interaction between Ultrasound and Speech 超声语音:通过超声和语音的相互作用来增强语音

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. Pub Date : 2022-01-01 DOI: 10.1145/3550303

H. Ding, Yizhan Wang, Hao Li, Cui Zhao, Ge Wang, Wei Xi, Jizhong Zhao

引用次数: 1

NeuralGait: Assessing Brain Health Using Your Smartphone neural步态:用智能手机评估大脑健康

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. Pub Date : 2022-01-01 DOI: 10.1145/3569476

Huining Li, Huan Chen, Chenhan Xu, Zhengxiong Li, Han-Zhe Zhang, Xiaoye Qian, Dongmei Li, Ming-chun Huang, Wenyao Xu

{"title":"NeuralGait: Assessing Brain Health Using Your Smartphone","authors":"Huining Li, Huan Chen, Chenhan Xu, Zhengxiong Li, Han-Zhe Zhang, Xiaoye Qian, Dongmei Li, Ming-chun Huang, Wenyao Xu","doi":"10.1145/3569476","DOIUrl":"https://doi.org/10.1145/3569476","url":null,"abstract":"Brain health attracts more recent attention as the population ages. Smartphone-based gait sensing and analysis can help identify the risks of brain diseases in daily life for prevention. Existing gait analysis approaches mainly hand-craft temporal gait features or developing CNN-based feature extractors, but they are either prone to lose some inconspicuous pathological information or are only dedicated to a single brain disease screening. We discover that the relationship between gait segments can be used as a principle and generic indicator to quantify multiple pathological patterns. In this paper, we propose NeuralGait , a pervasive smartphone-cloud system that passively captures and analyzes principle gait segments relationship for brain health assessment. On the smartphone end, inertial gait data are collected while putting the smartphone in the pants pocket. We then craft local temporal-frequent gait domain features and develop a self-attention-based gait segment relationship encoder. Afterward, the domain features and relation features are fed to a scalable RiskNet in the cloud for brain health assessment. We also design a pathological hot update protocol to efficiently add new brain diseases in the RiskNet. NeuralGait is practical as it provides brain health assessment with no burden in daily life. In the experiment, we recruit 988 healthy people and 417 patients with a single or combination of PD, TBI, and stroke, and evaluate the brain health assessment using a set of specifically designed metrics including global accuracy, exact accuracy, sensitivity, and false alarm rate. We also demonstrate the generalization (e.g., analysis of feature effectiveness and model efficiency) and inclusiveness of NeuralGait . CCS Concepts: • Human-centered computing → Ubiquitous and mobile computing systems and tools ; • Applied computing → Life and medical sciences .","PeriodicalId":20463,"journal":{"name":"Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.","volume":"90 1","pages":"169:1-169:28"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79178732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1