Puneet Jain, Justin Manweiler, Romit Roy Choudhury
Many emerging mobile computing applications are continuous vision based. The primary challenge these applications face is computation partitioning between the phone and cloud. The indoor location information is one metadata that can help these applications in making this decision. In this extended-abstract, we propose a vision based scheme to uniquely fingerprint an environment which can in turn be used to identify user's location from the uploaded visual features. Our approach takes into account that the opportunity to identify location is fleeting and the phones are resource constrained -- therefore minimal yet sufficient computation needs to be performed to make the offloading decision. Our work aims to achieve near real-time performance while scaling to buildings of arbitrary sizes. The current work is in preliminary stages but holds promise for the future -- may apply to many applications in this area.
{"title":"Poster: User Location Fingerprinting at Scale","authors":"Puneet Jain, Justin Manweiler, Romit Roy Choudhury","doi":"10.1145/2789168.2795175","DOIUrl":"https://doi.org/10.1145/2789168.2795175","url":null,"abstract":"Many emerging mobile computing applications are continuous vision based. The primary challenge these applications face is computation partitioning between the phone and cloud. The indoor location information is one metadata that can help these applications in making this decision. In this extended-abstract, we propose a vision based scheme to uniquely fingerprint an environment which can in turn be used to identify user's location from the uploaded visual features. Our approach takes into account that the opportunity to identify location is fleeting and the phones are resource constrained -- therefore minimal yet sufficient computation needs to be performed to make the offloading decision. Our work aims to achieve near real-time performance while scaling to buildings of arbitrary sizes. The current work is in preliminary stages but holds promise for the future -- may apply to many applications in this area.","PeriodicalId":424497,"journal":{"name":"Proceedings of the 21st Annual International Conference on Mobile Computing and Networking","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124864683","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}
L. Baron, F. Boubekeur, Radomir Klacza, M. Rahman, Ciro Scognamiglio, Nina Kurose, T. Friedman, S. Fdida
Gathering the required measurements to produce accurate results for mobile communications and wireless networking protocols, technologies and applications, relies on the use of expensive experimental computer networking facilities. Until very recently, large-scale testbed facilities have existed in separate silos, each with its own authentication mechanisms and experiment support tools. There lacked a viable federation model that reconciled the challenges posed by how to provide a single entry point to access heterogeneous and distributed resources, and how to federate these resources that are under the control of multiple authorities. The OneLab experimental facility, which came online in 2014, realizes this model, making a set of world-class testbeds freely available to researchers through a unique credential for each user and a common set of tools. We allow users to deploy innovative experiments across our federated platforms that include the embedded object testbeds of FIT IoT-Lab, the cognitive radio testbed of FIT CorteXlab, the wireless testbeds of NITOS-Lab, and the internet overlay testbed PlanetLab Europe (PLE), which together provide thousands of nodes for experimentation. Also federated under OneLab are the FUSECO Playground, which includes cloud, M2M, SDN, and mobile broadband; w-iLab.t wireless facilities; and the Virtual Wall testbed of wired networks and applications. Our demo describes the resources offered by the OneLab platforms, and illustrates how any member of the MobiCom community can create an account and start using these platforms today to deploy experiments for mobile and wireless testing.
收集所需的测量以产生移动通信和无线网络协议、技术和应用的准确结果，依赖于使用昂贵的实验性计算机网络设施。直到最近，大型测试平台设施都存在于独立的筒仓中，每个筒仓都有自己的身份验证机制和实验支持工具。缺乏一个可行的联邦模型来协调如何提供访问异构和分布式资源的单一入口点，以及如何联合这些在多个权威机构控制下的资源所带来的挑战。2014年上线的OneLab实验设施实现了这一模式，通过为每个用户提供独特的证书和一套通用工具，为研究人员免费提供了一套世界级的测试平台。我们允许用户在我们的联合平台上部署创新实验，包括FIT IoT-Lab的嵌入式对象测试平台、FIT CorteXlab的认知无线电测试平台、NITOS-Lab的无线测试平台和PlanetLab Europe (PLE)的互联网覆盖测试平台，这些平台共同提供数千个节点用于实验。OneLab旗下还有FUSECO Playground，包括云、M2M、SDN和移动宽带;w-iLab。T无线设施;以及有线网络和应用的虚拟墙测试平台。我们的演示描述了OneLab平台提供的资源，并说明了MobiCom社区的任何成员如何创建帐户并开始使用这些平台来部署移动和无线测试实验。
{"title":"Demo: OneLab: Major Computer Networking Testbeds for IoT and Wireless Experimentation","authors":"L. Baron, F. Boubekeur, Radomir Klacza, M. Rahman, Ciro Scognamiglio, Nina Kurose, T. Friedman, S. Fdida","doi":"10.1145/2789168.2789180","DOIUrl":"https://doi.org/10.1145/2789168.2789180","url":null,"abstract":"Gathering the required measurements to produce accurate results for mobile communications and wireless networking protocols, technologies and applications, relies on the use of expensive experimental computer networking facilities. Until very recently, large-scale testbed facilities have existed in separate silos, each with its own authentication mechanisms and experiment support tools. There lacked a viable federation model that reconciled the challenges posed by how to provide a single entry point to access heterogeneous and distributed resources, and how to federate these resources that are under the control of multiple authorities. The OneLab experimental facility, which came online in 2014, realizes this model, making a set of world-class testbeds freely available to researchers through a unique credential for each user and a common set of tools. We allow users to deploy innovative experiments across our federated platforms that include the embedded object testbeds of FIT IoT-Lab, the cognitive radio testbed of FIT CorteXlab, the wireless testbeds of NITOS-Lab, and the internet overlay testbed PlanetLab Europe (PLE), which together provide thousands of nodes for experimentation. Also federated under OneLab are the FUSECO Playground, which includes cloud, M2M, SDN, and mobile broadband; w-iLab.t wireless facilities; and the Virtual Wall testbed of wired networks and applications. Our demo describes the resources offered by the OneLab platforms, and illustrates how any member of the MobiCom community can create an account and start using these platforms today to deploy experiments for mobile and wireless testing.","PeriodicalId":424497,"journal":{"name":"Proceedings of the 21st Annual International Conference on Mobile Computing and Networking","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125035712","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}
Yunhan Jia, Qi Alfred Chen, Z. Morley Mao, J. Hui, Kranthi Sontineni, Alex Yoon, Samson Kwong, Kevin Lau
To understand VoLTE performance in a commercial deployment, in this paper we conduct the first comprehensive performance characterization of commercially deployed VoLTE, and compare with legacy call and over-the-top (OTT) VoIP call. We confirm that VoLTE excels in most metrics such as audio quality, but its call reliability still lags behind legacy call for all the three major U.S. operators. We propose an on-device VoLTE problem detection tool, which can capture new types of problems concerning audio quality with high accuracy and minimum overhead, and perform stress testing on VoLTE call's reliability. We discover 3 instances of problems in the early deployment of VoLTE lying in the protocol design and implementation. Although the identified problems are all concerned with the immature LTE coverage in the current deployment, we find that they can cause serious impairment on user experience and are urgent to be solved in the developing stage. For example, one such instance can lead to up to 50-second-long muting problem during a VoLTE call! We perform in-depth cross-layer analysis and find that the causes are rooted in the lack of coordination among protocols designed for different purposes, and invalid assumptions made by protocols used in existing infrastructure when integrated with VoLTE. We summarize learnt lessons and suggest solutions.
{"title":"Performance Characterization and Call Reliability Diagnosis Support for Voice over LTE","authors":"Yunhan Jia, Qi Alfred Chen, Z. Morley Mao, J. Hui, Kranthi Sontineni, Alex Yoon, Samson Kwong, Kevin Lau","doi":"10.1145/2789168.2790095","DOIUrl":"https://doi.org/10.1145/2789168.2790095","url":null,"abstract":"To understand VoLTE performance in a commercial deployment, in this paper we conduct the first comprehensive performance characterization of commercially deployed VoLTE, and compare with legacy call and over-the-top (OTT) VoIP call. We confirm that VoLTE excels in most metrics such as audio quality, but its call reliability still lags behind legacy call for all the three major U.S. operators. We propose an on-device VoLTE problem detection tool, which can capture new types of problems concerning audio quality with high accuracy and minimum overhead, and perform stress testing on VoLTE call's reliability. We discover 3 instances of problems in the early deployment of VoLTE lying in the protocol design and implementation. Although the identified problems are all concerned with the immature LTE coverage in the current deployment, we find that they can cause serious impairment on user experience and are urgent to be solved in the developing stage. For example, one such instance can lead to up to 50-second-long muting problem during a VoLTE call! We perform in-depth cross-layer analysis and find that the causes are rooted in the lack of coordination among protocols designed for different purposes, and invalid assumptions made by protocols used in existing infrastructure when integrated with VoLTE. We summarize learnt lessons and suggest solutions.","PeriodicalId":424497,"journal":{"name":"Proceedings of the 21st Annual International Conference on Mobile Computing and Networking","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124337857","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}
Stimulating user participation is of paramount importance for mobile crowdsensing applications to obtain high-quality data. Although many incentive mechanisms have been designed, most of them ignore the dynamic arrivals and different sensing requirements of tasks. Thus, the existing mechanisms will fail when being applied to the realistic scenario where tasks are publicized dynamically and heterogeneous with different sensing requirements of locations, time durations and sensing times. In this work, we propose an auction-based truthful mechanism for realistic mobile crowdsensing. Through extensive simulations, we demonstrate that our mechanism can satisfy the desired properties of truthfulness, individual rationality, computational efficiency with both low social cost and low total payment.
{"title":"Poster: TRIM: A Truthful Incentive Mechanism for Dynamic and Heterogeneous Tasks in Mobile Crowdsensing","authors":"Yue Fan, Hailong Sun, Xudong Liu","doi":"10.1145/2789168.2795179","DOIUrl":"https://doi.org/10.1145/2789168.2795179","url":null,"abstract":"Stimulating user participation is of paramount importance for mobile crowdsensing applications to obtain high-quality data. Although many incentive mechanisms have been designed, most of them ignore the dynamic arrivals and different sensing requirements of tasks. Thus, the existing mechanisms will fail when being applied to the realistic scenario where tasks are publicized dynamically and heterogeneous with different sensing requirements of locations, time durations and sensing times. In this work, we propose an auction-based truthful mechanism for realistic mobile crowdsensing. Through extensive simulations, we demonstrate that our mechanism can satisfy the desired properties of truthfulness, individual rationality, computational efficiency with both low social cost and low total payment.","PeriodicalId":424497,"journal":{"name":"Proceedings of the 21st Annual International Conference on Mobile Computing and Networking","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122744451","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}
Changmin Lee, Bonhong Koo, Na-Rae Kim, Huseyin Birkan Yilmaz, N. Farsad, A. Eckford, C. Chae
In molecular communication information is transferred with the use of molecules. Molecular multiple-input multiple- output (MIMO) system with drift (positive velocity) at macro- scale will be presented and the improvement against single- input single-output (SISO) molecular communication systems will be verified via our testbed. Until now it was unclear whether MIMO techniques, which are extensively used in modern radio frequency (RF) communications, could be applied to molecular communication. In the demonstration, using our MIMO testbed we will show that we can achieve nearly 1.7 times higher data rate than SISO molecular communication systems. Moreover, signal-to-inter-link-interfeence metric for one-shot signal will be depicted for a given symbol duration.
{"title":"Demo: Molecular MIMO with Drift","authors":"Changmin Lee, Bonhong Koo, Na-Rae Kim, Huseyin Birkan Yilmaz, N. Farsad, A. Eckford, C. Chae","doi":"10.1145/2789168.2789181","DOIUrl":"https://doi.org/10.1145/2789168.2789181","url":null,"abstract":"In molecular communication information is transferred with the use of molecules. Molecular multiple-input multiple- output (MIMO) system with drift (positive velocity) at macro- scale will be presented and the improvement against single- input single-output (SISO) molecular communication systems will be verified via our testbed. Until now it was unclear whether MIMO techniques, which are extensively used in modern radio frequency (RF) communications, could be applied to molecular communication. In the demonstration, using our MIMO testbed we will show that we can achieve nearly 1.7 times higher data rate than SISO molecular communication systems. Moreover, signal-to-inter-link-interfeence metric for one-shot signal will be depicted for a given symbol duration.","PeriodicalId":424497,"journal":{"name":"Proceedings of the 21st Annual International Conference on Mobile Computing and Networking","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115816678","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}
Although GPS has become a standard component of smartphones, providing accurate navigation during the last portion of a trip remains an important but unsolved problem. Despite extensive research on localization, the limited resolution of a map imposes restrictions on the navigation engine in both indoor and outdoor environments. To bridge the gap between the end position obtained from legacy navigation services and the real destination, we propose FollowMe, a "last-mile" navigation system to enable plug-and-play navigation in indoor and semi-outdoor environments. FollowMe exploits the ubiquitous, stable geomagnetic field and natural walking patterns to navigate the users to the same destination taken by an earlier traveler. Unlike existing localization and navigation systems, FollowMe is infrastructure-free, energy-efficient and cost-saving. We implemented FollowMe on smartphones, and evaluated it in a four-story campus building with a testing area of 2000m2. Our experimental results with 5 users show that 95% of spatial errors during navigation were 2m or less with at least 50% energy savings over a benchmark system.
{"title":"Last-Mile Navigation Using Smartphones","authors":"Yuanchao Shu, K. Shin, T. He, Jiming Chen","doi":"10.1145/2789168.2790099","DOIUrl":"https://doi.org/10.1145/2789168.2790099","url":null,"abstract":"Although GPS has become a standard component of smartphones, providing accurate navigation during the last portion of a trip remains an important but unsolved problem. Despite extensive research on localization, the limited resolution of a map imposes restrictions on the navigation engine in both indoor and outdoor environments. To bridge the gap between the end position obtained from legacy navigation services and the real destination, we propose FollowMe, a \"last-mile\" navigation system to enable plug-and-play navigation in indoor and semi-outdoor environments. FollowMe exploits the ubiquitous, stable geomagnetic field and natural walking patterns to navigate the users to the same destination taken by an earlier traveler. Unlike existing localization and navigation systems, FollowMe is infrastructure-free, energy-efficient and cost-saving. We implemented FollowMe on smartphones, and evaluated it in a four-story campus building with a testing area of 2000m2. Our experimental results with 5 users show that 95% of spatial errors during navigation were 2m or less with at least 50% energy savings over a benchmark system.","PeriodicalId":424497,"journal":{"name":"Proceedings of the 21st Annual International Conference on Mobile Computing and Networking","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131091424","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}
The extremely-high display density of modern smartphones imposes a significant burden on power consumption, yet does not always provide an improved user experience and may even lead to a compromised user experience. As human visually-perceivable ability highly depends on the user-screen distance, a reduced display resolution may still achieve the same user experience when the user-screen distance is large. This provides new power-saving opportunities. We present a flexible dynamic resolution scaling system for smartphones. The system adopts an ultrasonic-based approach to detect the user-screen distance at low-power cost and makes scaling decisions automatically for maximum user experience and power saving. App developers or users can also adjust the resolution manually and dynamically as their needs. Our system is able to work on the existing commercial smartphones and support the legacy apps, without requiring re-building the ROM or any changes from apps.
{"title":"Demo: Optimizing Smartphone Power Consumption through Dynamic Resolution Scaling","authors":"Songtao He, Yunxin Liu, Hucheng Zhou","doi":"10.1145/2789168.2789175","DOIUrl":"https://doi.org/10.1145/2789168.2789175","url":null,"abstract":"The extremely-high display density of modern smartphones imposes a significant burden on power consumption, yet does not always provide an improved user experience and may even lead to a compromised user experience. As human visually-perceivable ability highly depends on the user-screen distance, a reduced display resolution may still achieve the same user experience when the user-screen distance is large. This provides new power-saving opportunities. We present a flexible dynamic resolution scaling system for smartphones. The system adopts an ultrasonic-based approach to detect the user-screen distance at low-power cost and makes scaling decisions automatically for maximum user experience and power saving. App developers or users can also adjust the resolution manually and dynamically as their needs. Our system is able to work on the existing commercial smartphones and support the legacy apps, without requiring re-building the ROM or any changes from apps.","PeriodicalId":424497,"journal":{"name":"Proceedings of the 21st Annual International Conference on Mobile Computing and Networking","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125248703","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}
The future of mobile computing involves autonomous drones, robots and vehicles. To accurately sense their surroundings in a variety of scenarios, these mobile computers require a robust environmental mapping system. One attractive approach is to reuse millimeterwave communication hardware in these devices, e.g. 60GHz networking chipset, and capture signals reflected by the target surface. The devices can also move while collecting reflection signals, creating a large synthetic aperture radar (SAR) for high-precision RF imaging. Our experimental measurements, however, show that this approach provides poor precision in practice, as imaging results are highly sensitive to device positioning errors that translate into phase errors. We address this challenge by proposing a new 60GHz imaging algorithm, {em RSS Series Analysis}, which images an object using only RSS measurements recorded along the device's trajectory. In addition to object location, our algorithm can discover a rich set of object surface properties at high precision, including object surface orientation, curvature, boundaries, and surface material. We tested our system on a variety of common household objects (between 5cm--30cm in width). Results show that it achieves high accuracy (cm level) in a variety of dimensions, and is highly robust against noises in device position and trajectory tracking. We believe that this is the first practical mobile imaging system (re)using 60GHz networking devices, and provides a basic primitive towards the construction of detailed environmental mapping systems.
{"title":"Reusing 60GHz Radios for Mobile Radar Imaging","authors":"Yanzi Zhu, Yibo Zhu, Ben Y. Zhao, Haitao Zheng","doi":"10.1145/2789168.2790112","DOIUrl":"https://doi.org/10.1145/2789168.2790112","url":null,"abstract":"The future of mobile computing involves autonomous drones, robots and vehicles. To accurately sense their surroundings in a variety of scenarios, these mobile computers require a robust environmental mapping system. One attractive approach is to reuse millimeterwave communication hardware in these devices, e.g. 60GHz networking chipset, and capture signals reflected by the target surface. The devices can also move while collecting reflection signals, creating a large synthetic aperture radar (SAR) for high-precision RF imaging. Our experimental measurements, however, show that this approach provides poor precision in practice, as imaging results are highly sensitive to device positioning errors that translate into phase errors. We address this challenge by proposing a new 60GHz imaging algorithm, {em RSS Series Analysis}, which images an object using only RSS measurements recorded along the device's trajectory. In addition to object location, our algorithm can discover a rich set of object surface properties at high precision, including object surface orientation, curvature, boundaries, and surface material. We tested our system on a variety of common household objects (between 5cm--30cm in width). Results show that it achieves high accuracy (cm level) in a variety of dimensions, and is highly robust against noises in device position and trajectory tracking. We believe that this is the first practical mobile imaging system (re)using 60GHz networking devices, and provides a basic primitive towards the construction of detailed environmental mapping systems.","PeriodicalId":424497,"journal":{"name":"Proceedings of the 21st Annual International Conference on Mobile Computing and Networking","volume":"192 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114226908","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}
An unobtrusive and continuous estimation of breathing volume could play a vital role in health care, such as for critically ill patients, neonatal ventilation, post-operative monitoring, just to name a few. While radar-based estimation of breathing rate has been discussed in the literature, estimating breathing volume using wireless signal remains relatively intact. With the presence of patient body movement and posture changes, long-term monitoring of breathing volume at fine granularity is even more challenging. In this work, we propose for the first time an autonomous system that monitors a patient's breathing volume with high resolution. We discuss the key research components and challenges in realizing the system. We also present an initial system design encompassing a continuous wave radar, motion tracking and control system, and a set of methods to accurately derive breathing volume from the reflected signal and to address challenges caused by body movement and posture changes. Our implementation shows promising results in estimating breathing volume with fine granularity.
{"title":"Poster: Continuous and Fine-grained Respiration Volume Monitoring Using Continuous Wave Radar","authors":"Phuc Nguyen, Xinyu Zhang, A. Halbower, Tam N. Vu","doi":"10.1145/2789168.2795177","DOIUrl":"https://doi.org/10.1145/2789168.2795177","url":null,"abstract":"An unobtrusive and continuous estimation of breathing volume could play a vital role in health care, such as for critically ill patients, neonatal ventilation, post-operative monitoring, just to name a few. While radar-based estimation of breathing rate has been discussed in the literature, estimating breathing volume using wireless signal remains relatively intact. With the presence of patient body movement and posture changes, long-term monitoring of breathing volume at fine granularity is even more challenging. In this work, we propose for the first time an autonomous system that monitors a patient's breathing volume with high resolution. We discuss the key research components and challenges in realizing the system. We also present an initial system design encompassing a continuous wave radar, motion tracking and control system, and a set of methods to accurately derive breathing volume from the reflected signal and to address challenges caused by body movement and posture changes. Our implementation shows promising results in estimating breathing volume with fine granularity.","PeriodicalId":424497,"journal":{"name":"Proceedings of the 21st Annual International Conference on Mobile Computing and Networking","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115141747","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}
Imagine a user typing on a laptop keyboard while wearing a smart watch. This paper asks whether motion sensors from the watch can leak information about what the user is typing. While its not surprising that some information will be leaked, the question is how much? We find that when motion signal processing is combined with patterns in English language, the leakage is substantial. Reported results show that when a user types a word $W$, it is possible to shortlist a median of 24 words, such that $W$ is in this shortlist. When the word is longer than $6$ characters, the median shortlist drops to $10$. Of course, such leaks happen without requiring any training from the user, and also under the (obvious) condition that the watch is only on the left hand. We believe this is surprising and merits awareness, especially in light of various continuous sensing apps that are emerging in the app market. Moreover, we discover additional "leaks" that can further reduce the shortlist -- we leave these exploitations to future work.
{"title":"MoLe: Motion Leaks through Smartwatch Sensors","authors":"He Wang, Tsung-Te Lai, Romit Roy Choudhury","doi":"10.1145/2789168.2790121","DOIUrl":"https://doi.org/10.1145/2789168.2790121","url":null,"abstract":"Imagine a user typing on a laptop keyboard while wearing a smart watch. This paper asks whether motion sensors from the watch can leak information about what the user is typing. While its not surprising that some information will be leaked, the question is how much? We find that when motion signal processing is combined with patterns in English language, the leakage is substantial. Reported results show that when a user types a word $W$, it is possible to shortlist a median of 24 words, such that $W$ is in this shortlist. When the word is longer than $6$ characters, the median shortlist drops to $10$. Of course, such leaks happen without requiring any training from the user, and also under the (obvious) condition that the watch is only on the left hand. We believe this is surprising and merits awareness, especially in light of various continuous sensing apps that are emerging in the app market. Moreover, we discover additional \"leaks\" that can further reduce the shortlist -- we leave these exploitations to future work.","PeriodicalId":424497,"journal":{"name":"Proceedings of the 21st Annual International Conference on Mobile Computing and Networking","volume":"581 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122691935","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}
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