Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies最新文献_第4页

TextureSight 纹理视图

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Pub Date : 2024-01-12 DOI: 10.1145/3631413

Xue Wang, Yang Zhang

引用次数: 0

LiqDetector LiqDetector

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Pub Date : 2024-01-12 DOI: 10.1145/3631443

Zhu Wang, Yifan Guo, Zhihui Ren, Wenchao Song, Zhuo Sun, Chaoxiong Chen, Bin Guo, Zhiwen Yu

{"title":"LiqDetector","authors":"Zhu Wang, Yifan Guo, Zhihui Ren, Wenchao Song, Zhuo Sun, Chaoxiong Chen, Bin Guo, Zhiwen Yu","doi":"10.1145/3631443","DOIUrl":"https://doi.org/10.1145/3631443","url":null,"abstract":"With the advancement of wireless sensing technologies, RF-based contact-less liquid detection attracts more and more attention. Compared with other RF devices, the mmWave radar has the advantages of large bandwidth and low cost. While existing radar-based liquid detection systems demonstrate promising performance, they still have a shortcoming that in the detection result depends on container-related factors (e.g., container placement, container caliber, and container material). In this paper, to enable container-independent liquid detection with a COTS mmWave radar, we propose a dual-reflection model by exploring reflections from different interfaces of the liquid container. Specifically, we design a pair of amplitude ratios based on the signals reflected from different interfaces, and theoretically demonstrate how the refractive index of liquids can be estimated by eliminating the container's impact. To validate the proposed approach, we implement a liquid detection system LiqDetector. Experimental results show that LiqDetector achieves cross-container estimation of the liquid's refractive index with a mean absolute percentage error (MAPE) of about 4.4%. Moreover, the classification accuracies for 6 different liquids and alcohol with different strengths (even a difference of 1%) exceed 96% and 95%, respectively. To the best of our knowledge, this is the first study that achieves container-independent liquid detection based on the COTS mmWave radar by leveraging only one pair of Tx-Rx antennas.","PeriodicalId":20553,"journal":{"name":"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies","volume":"12 29","pages":"1 - 24"},"PeriodicalIF":0.0,"publicationDate":"2024-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139437681","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

Scribe 抄写员

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Pub Date : 2024-01-12 DOI: 10.1145/3631411

Yang Bai, Irtaza Shahid, Harshvardhan Takawale, Nirupam Roy

{"title":"Scribe","authors":"Yang Bai, Irtaza Shahid, Harshvardhan Takawale, Nirupam Roy","doi":"10.1145/3631411","DOIUrl":"https://doi.org/10.1145/3631411","url":null,"abstract":"This paper presents the design and implementation of Scribe, a comprehensive voice processing and handwriting interface for voice assistants. Distinct from prior works, Scribe is a precise tracking interface that can co-exist with the voice interface on low sampling rate voice assistants. Scribe can be used for 3D free-form drawing, writing, and motion tracking for gaming. Taking handwriting as a specific application, it can also capture natural strokes and the individualized style of writing while occupying only a single frequency. The core technique includes an accurate acoustic ranging method called Cross Frequency Continuous Wave (CFCW) sonar, enabling voice assistants to use ultrasound as a ranging signal while using the regular microphone system of voice assistants as a receiver. We also design a new optimization algorithm that only requires a single frequency for time difference of arrival. Scribe prototype achieves 73 μm of median error for 1D ranging and 1.4 mm of median error in 3D tracking of an acoustic beacon using the microphone array used in voice assistants. Our implementation of an in-air handwriting interface achieves 94.1% accuracy with automatic handwriting-to-text software, similar to writing on paper (96.6%). At the same time, the error rate of voice-based user authentication only increases from 6.26% to 8.28%.","PeriodicalId":20553,"journal":{"name":"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies","volume":"3 3","pages":"1 - 31"},"PeriodicalIF":0.0,"publicationDate":"2024-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139437899","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

PmTrack PmTrack

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Pub Date : 2024-01-12 DOI: 10.1145/3631433

Hankai Liu, Xiulong Liu, Xin Xie, Xinyu Tong, Keqiu Li

{"title":"PmTrack","authors":"Hankai Liu, Xiulong Liu, Xin Xie, Xinyu Tong, Keqiu Li","doi":"10.1145/3631433","DOIUrl":"https://doi.org/10.1145/3631433","url":null,"abstract":"The difficulty in obtaining targets' identity poses a significant obstacle to the pursuit of personalized and customized millimeter-wave (mmWave) sensing. Existing solutions that learn individual differences from signal features have limitations in practical applications. This paper presents a Personalized mmWave-based human Tracking system, PmTrack, by introducing inertial measurement units (IMUs) as identity indicators. Widely available in portable devices such as smartwatches and smartphones, IMUs utilize existing wireless networks for data uploading of identity and data, and are therefore able to assist in radar target identification in a lightweight manner with little deployment and carrying burden for users. PmTrack innovatively adopts orientation as the matching feature, thus well overcoming the data heterogeneity between radar and IMU while avoiding the effect of cumulative errors. In the implementation of PmTrack, we propose a comprehensive set of optimization methods in detection enhancement, interference suppression, continuity maintenance, and trajectory correction, which successfully solved a series of practical problems caused by the three major challenges of weak reflection, point cloud overlap, and body-bounce ghost in multi-person tracking. In addition, an orientation correction method is proposed to overcome the IMU gimbal lock. Extensive experimental results demonstrate that PmTrack achieves an identification accuracy of 98% and 95% with five people in the hall and meeting room, respectively.","PeriodicalId":20553,"journal":{"name":"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies","volume":"3 8","pages":"1 - 30"},"PeriodicalIF":0.0,"publicationDate":"2024-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139437972","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

AdaStreamLite AdaStreamLite

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Pub Date : 2024-01-12 DOI: 10.1145/3631460

Yuheng Wei, Jie Xiong, Hui Liu, Yingtao Yu, Jiangtao Pan, Junzhao Du

{"title":"AdaStreamLite","authors":"Yuheng Wei, Jie Xiong, Hui Liu, Yingtao Yu, Jiangtao Pan, Junzhao Du","doi":"10.1145/3631460","DOIUrl":"https://doi.org/10.1145/3631460","url":null,"abstract":"Streaming speech recognition aims to transcribe speech to text in a streaming manner, providing real-time speech interaction for smartphone users. However, it is not trivial to develop a high-performance streaming speech recognition system purely running on mobile platforms, due to the complex real-world acoustic environments and the limited computational resources of smartphones. Most existing solutions lack the generalization to unseen environments and have difficulty to work with streaming speech. In this paper, we design AdaStreamLite, an environment-adaptive streaming speech recognition tool for smartphones. AdaStreamLite interacts with its surroundings to capture the characteristics of the current acoustic environment to improve the robustness against ambient noise in a lightweight manner. We design an environment representation extractor to model acoustic environments with compact feature vectors, and construct a representation lookup table to improve the generalization of AdaStreamLite to unseen environments. We train our system using large speech datasets publicly available covering different languages. We conduct experiments in a large range of real acoustic environments with different smartphones. The results show that AdaStreamLite outperforms the state-of-the-art methods in terms of recognition accuracy, computational resource consumption and robustness against unseen environments.","PeriodicalId":20553,"journal":{"name":"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies","volume":"11 22","pages":"1 - 29"},"PeriodicalIF":0.0,"publicationDate":"2024-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139437854","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

JoulesEye 焦耳之眼

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Pub Date : 2024-01-12 DOI: 10.1145/3631422

Rishiraj Adhikary, M. Sadeh, N. Batra, Mayank Goel

引用次数: 0

Aragorn 阿拉贡

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Pub Date : 2024-01-12 DOI: 10.1145/3631406

Harish Venugopalan, Z. Din, Trevor Carpenter, Jason Lowe-Power, Samuel T. King, Zubair Shafiq

{"title":"Aragorn","authors":"Harish Venugopalan, Z. Din, Trevor Carpenter, Jason Lowe-Power, Samuel T. King, Zubair Shafiq","doi":"10.1145/3631406","DOIUrl":"https://doi.org/10.1145/3631406","url":null,"abstract":"Mobile app developers often rely on cameras to implement rich features. However, giving apps unfettered access to the mobile camera poses a privacy threat when camera frames capture sensitive information that is not needed for the app's functionality. To mitigate this threat, we present Aragorn, a novel privacy-enhancing mobile camera system that provides fine grained control over what information can be present in camera frames before apps can access them. Aragorn automatically sanitizes camera frames by detecting regions that are essential to an app's functionality and blocking out everything else to protect privacy while retaining app utility. Aragorn can cater to a wide range of camera apps and incorporates knowledge distillation and crowdsourcing to extend robust support to previously unsupported apps. In our evaluations, we see that, with no degradation in utility, Aragorn detects credit cards with 89% accuracy and faces with 100% accuracy in context of credit card scanning and face recognition respectively. We show that Aragorn's implementation in the Android camera subsystem only suffers an average drop of 0.01 frames per second in frame rate. Our evaluations show that the overhead incurred by Aragorn to system performance is reasonable.","PeriodicalId":20553,"journal":{"name":"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies","volume":"4 4","pages":"1 - 31"},"PeriodicalIF":0.0,"publicationDate":"2024-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139437964","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

Enabling WiFi Sensing on New-generation WiFi Cards 在新一代 WiFi 卡上启用 WiFi 传感功能

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Pub Date : 2024-01-12 DOI: 10.1145/3633807

E. Yi, Fusang Zhang, Jie Xiong, Kai Niu, Zhiyun Yao, Daqing Zhang

{"title":"Enabling WiFi Sensing on New-generation WiFi Cards","authors":"E. Yi, Fusang Zhang, Jie Xiong, Kai Niu, Zhiyun Yao, Daqing Zhang","doi":"10.1145/3633807","DOIUrl":"https://doi.org/10.1145/3633807","url":null,"abstract":"The last few years have witnessed the rapid development of WiFi sensing with a large spectrum of applications enabled. However, existing works mainly leverage the obsolete 802.11n WiFi cards (i.e., Intel 5300 and Atheros AR9k series cards) for sensing. On the other hand, the mainstream WiFi protocols currently in use are 802.11ac/ax and commodity WiFi products on the market are equipped with new-generation WiFi chips such as Broadcom BCM43794 and Qualcomm QCN5054. After conducting some benchmark experiments, we find that WiFi sensing has problems working on these new cards. The new communication features (e.g., MU-MIMO) designed to facilitate data transmissions negatively impact WiFi sensing. Conventional CSI base signals such as CSI amplitude and/or CSI phase difference between antennas which worked well on Intel 5300 802.11n WiFi card may fail on new cards. In this paper, we propose delicate signal processing schemes to make wireless sensing work well on these new WiFi cards. We employ two typical sensing applications, i.e., human respiration monitoring and human trajectory tracking to demonstrate the effectiveness of the proposed schemes. We believe it is critical to ensure WiFi sensing compatible with the latest WiFi protocols and this work moves one important step towards real-life adoption of WiFi sensing.","PeriodicalId":20553,"journal":{"name":"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies","volume":"7 4","pages":"1 - 26"},"PeriodicalIF":0.0,"publicationDate":"2024-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139437586","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

ClearSpeech ClearSpeech

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Pub Date : 2024-01-12 DOI: 10.1145/3631409

Dong Ma, Ting Dang, Ming Ding, Rajesh Balan

引用次数: 0

RLoc RLoc

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Pub Date : 2024-01-12 DOI: 10.1145/3631437

Tianyu Zhang, Dongheng Zhang, Guanzhong Wang, Yadong Li, Yang Hu, Qibin sun, Yan Chen

{"title":"RLoc","authors":"Tianyu Zhang, Dongheng Zhang, Guanzhong Wang, Yadong Li, Yang Hu, Qibin sun, Yan Chen","doi":"10.1145/3631437","DOIUrl":"https://doi.org/10.1145/3631437","url":null,"abstract":"In recent years, decimeter-level accuracy in WiFi indoor localization has become attainable within controlled environments. However, existing methods encounter challenges in maintaining robustness in more complex indoor environments: angle-based methods are compromised by the significant localization errors due to unreliable Angle of Arrival (AoA) estimations, and fingerprint-based methods suffer from performance degradation due to environmental changes. In this paper, we propose RLoc, a learning-based system designed for reliable localization and tracking. The key design principle of RLoc lies in quantifying the uncertainty level arises in the AoA estimation task and then exploiting the uncertainty to enhance the reliability of localization and tracking. To this end, RLoc first manually extracts the underutilized beamwidth feature via signal processing techniques. Then, it integrates the uncertainty quantification into neural network design through Kullback-Leibler (KL) divergence loss and ensemble techniques. Finally, these quantified uncertainties guide RLoc to optimally leverage the diversity of Access Points (APs) and the temporal continuous information of AoAs. Our experiments, evaluating on two datasets gathered from commercial off-the-shelf WiFi devices, demonstrate that RLoc surpasses state-of-the-art approaches by an average of 36.27% in in-domain scenarios and 20.40% in cross-domain scenarios.","PeriodicalId":20553,"journal":{"name":"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies","volume":"12 3","pages":"1 - 28"},"PeriodicalIF":0.0,"publicationDate":"2024-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139437883","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