Farshid Salemi Parizi, Eric Whitmire, Shwetak N. Patel
Wearable computing platforms, such as smartwatches and head-mounted mixed reality displays, demand new input devices for high-fidelity interaction. We present AuraRing, a wearable magnetic tracking system designed for tracking fine-grained finger movement. The hardware consists of a ring with an embedded electromagnetic transmitter coil and a wristband with multiple sensor coils. By measuring the magnetic fields at different points around the wrist, AuraRing estimates the five degree-of-freedom pose of the ring. AuraRing is trained only on simulated data and requires no runtime supervised training, ensuring user and session independence. It has a resolution of 0.1 mm and a dynamic accuracy of 4.4 mm, as measured through a user evaluation with optical ground truth. The ring is completely self-contained and consumes just 2.3 mW of power.
{"title":"AuraRing","authors":"Farshid Salemi Parizi, Eric Whitmire, Shwetak N. Patel","doi":"10.1145/3511285.3511295","DOIUrl":"https://doi.org/10.1145/3511285.3511295","url":null,"abstract":"Wearable computing platforms, such as smartwatches and head-mounted mixed reality displays, demand new input devices for high-fidelity interaction. We present AuraRing, a wearable magnetic tracking system designed for tracking fine-grained finger movement. The hardware consists of a ring with an embedded electromagnetic transmitter coil and a wristband with multiple sensor coils. By measuring the magnetic fields at different points around the wrist, AuraRing estimates the five degree-of-freedom pose of the ring. AuraRing is trained only on simulated data and requires no runtime supervised training, ensuring user and session independence. It has a resolution of 0.1 mm and a dynamic accuracy of 4.4 mm, as measured through a user evaluation with optical ground truth. The ring is completely self-contained and consumes just 2.3 mW of power.","PeriodicalId":29918,"journal":{"name":"GetMobile-Mobile Computing & Communications Review","volume":"103 1","pages":"34 - 37"},"PeriodicalIF":1.0,"publicationDate":"2022-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76110674","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}
Healthcare in the United States is inequitable. The consequence of inequity is that the burden of serious chronic disease, such as diabetes, falls disproportionately on populations experiencing health disparities, predominantly Black, Indigenous, and people of color. [1] The reasons for the inequity include the negative impact of the social determinants of health of individuals and families from these communities, being underrepresented as participants in clinical research, having limited access to technologies that support self-care, and a lack of researchers and clinicians from these same populations. [2] To achieve equity and fairness, there is a need for a paradigm shift in healthcare research and innovation based on improving access, trust, and self-efficacy [3] to convert new knowledge into positive health outcomes.
{"title":"A Systems Approach to Achieve Equity in Healthcare Research","authors":"Ashutosh Sabharwal, Souptik Barua, D. Kerr","doi":"10.1145/3511285.3511287","DOIUrl":"https://doi.org/10.1145/3511285.3511287","url":null,"abstract":"Healthcare in the United States is inequitable. The consequence of inequity is that the burden of serious chronic disease, such as diabetes, falls disproportionately on populations experiencing health disparities, predominantly Black, Indigenous, and people of color. [1] The reasons for the inequity include the negative impact of the social determinants of health of individuals and families from these communities, being underrepresented as participants in clinical research, having limited access to technologies that support self-care, and a lack of researchers and clinicians from these same populations. [2] To achieve equity and fairness, there is a need for a paradigm shift in healthcare research and innovation based on improving access, trust, and self-efficacy [3] to convert new knowledge into positive health outcomes.","PeriodicalId":29918,"journal":{"name":"GetMobile-Mobile Computing & Communications Review","volume":"8 1","pages":"5 - 11"},"PeriodicalIF":1.0,"publicationDate":"2022-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73031114","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}
With the growing concern on data privacy and security, it is undesirable to collect data from all users to perform machine learning tasks. Federated learning, a decentralized learning framework, was proposed to construct a shared prediction model while keeping owners' data on their own devices. This paper presents an introduction to the emerging federated learning standard and discusses its various aspects, including i) an overview of federated learning, ii) types of federated learning, iii) major concerns and the performance evaluation criteria of federated learning, and iv) associated regulatory requirements. The purpose of this paper is to provide an understanding of the standard and facilitate its usage in model building across organizations while meeting privacy and security concerns.
{"title":"An Introduction to the Federated Learning Standard","authors":"Ticao Zhang, S. Mao","doi":"10.1145/3511285.3511291","DOIUrl":"https://doi.org/10.1145/3511285.3511291","url":null,"abstract":"With the growing concern on data privacy and security, it is undesirable to collect data from all users to perform machine learning tasks. Federated learning, a decentralized learning framework, was proposed to construct a shared prediction model while keeping owners' data on their own devices. This paper presents an introduction to the emerging federated learning standard and discusses its various aspects, including i) an overview of federated learning, ii) types of federated learning, iii) major concerns and the performance evaluation criteria of federated learning, and iv) associated regulatory requirements. The purpose of this paper is to provide an understanding of the standard and facilitate its usage in model building across organizations while meeting privacy and security concerns.","PeriodicalId":29918,"journal":{"name":"GetMobile-Mobile Computing & Communications Review","volume":"31 1","pages":"18 - 22"},"PeriodicalIF":1.0,"publicationDate":"2022-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78171927","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 recipient of the 2021 SIGMOBILE RockStar Award is Aruna Balasubramanian, associate professor of computer science at Stony Brook University, NY. The award recognizes Aruna's outstanding contributions in the areas of mobile systems and mobile web performance, and her mentoring and leadership efforts in improving diversity in the SIGMOBILE community.
{"title":"2021 ACM SIGMOBILE Rockstar Award","authors":"Samir R Das","doi":"10.1145/3486880.3486886","DOIUrl":"https://doi.org/10.1145/3486880.3486886","url":null,"abstract":"The recipient of the 2021 SIGMOBILE RockStar Award is Aruna Balasubramanian, associate professor of computer science at Stony Brook University, NY. The award recognizes Aruna's outstanding contributions in the areas of mobile systems and mobile web performance, and her mentoring and leadership efforts in improving diversity in the SIGMOBILE community.","PeriodicalId":29918,"journal":{"name":"GetMobile-Mobile Computing & Communications Review","volume":"9 1","pages":"21 - 21"},"PeriodicalIF":1.0,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89498406","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}
M. Satyanarayanan, Nathan Beckmann, G. Lewis, Brandon Lucia
This position paper examines a spectrum of approaches to overcoming the limited computing power of mobile devices caused by their need to be small, lightweight and energy efficient. At one extreme is offloading of compute-intensive operations to a cloudlet nearby. At the other extreme is the use of fixed-function hardware accelerators on mobile devices. Between these endpoints lie various configurations of programmable hardware accelerators. We explore the strengths and weaknesses of these approaches and conclude that they are, in fact, complementary. Based on this insight, we advocate a softwarehardware co-evolution path that combines their strengths.
{"title":"The Role of Edge Offload for Hardware - Accelerated Mobile Devices","authors":"M. Satyanarayanan, Nathan Beckmann, G. Lewis, Brandon Lucia","doi":"10.1145/3486880.3486882","DOIUrl":"https://doi.org/10.1145/3486880.3486882","url":null,"abstract":"This position paper examines a spectrum of approaches to overcoming the limited computing power of mobile devices caused by their need to be small, lightweight and energy efficient. At one extreme is offloading of compute-intensive operations to a cloudlet nearby. At the other extreme is the use of fixed-function hardware accelerators on mobile devices. Between these endpoints lie various configurations of programmable hardware accelerators. We explore the strengths and weaknesses of these approaches and conclude that they are, in fact, complementary. Based on this insight, we advocate a softwarehardware co-evolution path that combines their strengths.","PeriodicalId":29918,"journal":{"name":"GetMobile-Mobile Computing & Communications Review","volume":"19 1","pages":"5 - 13"},"PeriodicalIF":1.0,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79186287","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}
HyeokHyen Kwon, C. Tong, H. Haresamudram, Yan Gao, G. Abowd, Nicholas D. Lane, T. Ploetz
Today's smartphones and wearable devices come equipped with an array of inertial sensors, along with IMU-based Human Activity Recognition models to monitor everyday activities. However, such models rely on large amounts of annotated training data, which require considerable time and effort for collection. One has to recruit human subjects, define clear protocols for the subjects to follow, and manually annotate the collected data, along with the administrative work that goes into organizing such a recording.
{"title":"Can You See It?","authors":"HyeokHyen Kwon, C. Tong, H. Haresamudram, Yan Gao, G. Abowd, Nicholas D. Lane, T. Ploetz","doi":"10.1145/3486880.3486891","DOIUrl":"https://doi.org/10.1145/3486880.3486891","url":null,"abstract":"Today's smartphones and wearable devices come equipped with an array of inertial sensors, along with IMU-based Human Activity Recognition models to monitor everyday activities. However, such models rely on large amounts of annotated training data, which require considerable time and effort for collection. One has to recruit human subjects, define clear protocols for the subjects to follow, and manually annotate the collected data, along with the administrative work that goes into organizing such a recording.","PeriodicalId":29918,"journal":{"name":"GetMobile-Mobile Computing & Communications Review","volume":"41 1","pages":"38 - 42"},"PeriodicalIF":1.0,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82327399","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}
Fusang Zhang, Zhaoxin Chang, Jie Xiong, Daqing Zhang
Wireless sensing received a great amount of attention in recent years and various wireless technologies have been exploited for sensing, including WiFi [1], RFID [2], ultrasound [3], 60 GHz mmWave [4] and visible light [5]. The key advantage of wireless sensing over traditional sensing is that the target does not need to be equipped with any sensor(s) and the wireless signal itself is being used for sensing. Exciting new applications have been enabled, such as passive localization [6] and contactless human activity sensing [7]. While promising in many aspects, one key limitation of current wireless sensing techniques is the very small sensing range. This is because while both direct path and reflection path signals are used for communication, only the weak target-reflection signals can be used for sensing. Take Wi-Fi as an example: the communication range can reach 20 to 50 meters indoors but its sensing range is merely 4 to 8 meters. This small range further limits the through-wall sensing capability of Wi-Fi. On the other hand, many applications do require long-range and through-wall sensing capability. In a fire rescue scenario, the sensing device cannot be placed close to the building, and the long-range through-wall sensing capabilities are critical for detecting people deep inside the building. Table I summarizes the sensing range of existing wireless technologies. We can see that long-range through-wall sensing is still missing with wireless sensing.
{"title":"Exploring LoRa for Sensing","authors":"Fusang Zhang, Zhaoxin Chang, Jie Xiong, Daqing Zhang","doi":"10.1145/3486880.3486890","DOIUrl":"https://doi.org/10.1145/3486880.3486890","url":null,"abstract":"Wireless sensing received a great amount of attention in recent years and various wireless technologies have been exploited for sensing, including WiFi [1], RFID [2], ultrasound [3], 60 GHz mmWave [4] and visible light [5]. The key advantage of wireless sensing over traditional sensing is that the target does not need to be equipped with any sensor(s) and the wireless signal itself is being used for sensing. Exciting new applications have been enabled, such as passive localization [6] and contactless human activity sensing [7]. While promising in many aspects, one key limitation of current wireless sensing techniques is the very small sensing range. This is because while both direct path and reflection path signals are used for communication, only the weak target-reflection signals can be used for sensing. Take Wi-Fi as an example: the communication range can reach 20 to 50 meters indoors but its sensing range is merely 4 to 8 meters. This small range further limits the through-wall sensing capability of Wi-Fi. On the other hand, many applications do require long-range and through-wall sensing capability. In a fire rescue scenario, the sensing device cannot be placed close to the building, and the long-range through-wall sensing capabilities are critical for detecting people deep inside the building. Table I summarizes the sensing range of existing wireless technologies. We can see that long-range through-wall sensing is still missing with wireless sensing.","PeriodicalId":29918,"journal":{"name":"GetMobile-Mobile Computing & Communications Review","volume":"292 1","pages":"33 - 37"},"PeriodicalIF":1.0,"publicationDate":"2021-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74959150","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}
Jasper de Winkel, Vito Kortbeek, Josiah D. Hester, P. Pawełczak
Any future mobile electronic device with which a user interacts (smartphone, hand-held game console) should not pollute our planet. Consequently, designers need to rethink how to build mobile devices with fewer components that negatively impact the environment (by replacing batteries with energy harvesting sources) while not compromising the user experience quality. This article addresses the challenges of battery-free mobile interaction and presents the first battery-free, personal mobile gaming device powered by energy harvested from gamer actions and sunlight. Our design implements a power failure resilient Nintendo Game Boy emulator that can run off-the-shelf classic Game Boy games like Tetris or Super Mario Land. Beyond a fun toy, our design represents the first battery-free system design for continuous user attention despite frequent power failures caused by intermittent energy harvesting.
{"title":"Battery-Free Game Boy","authors":"Jasper de Winkel, Vito Kortbeek, Josiah D. Hester, P. Pawełczak","doi":"10.1145/3486880.3486888","DOIUrl":"https://doi.org/10.1145/3486880.3486888","url":null,"abstract":"Any future mobile electronic device with which a user interacts (smartphone, hand-held game console) should not pollute our planet. Consequently, designers need to rethink how to build mobile devices with fewer components that negatively impact the environment (by replacing batteries with energy harvesting sources) while not compromising the user experience quality. This article addresses the challenges of battery-free mobile interaction and presents the first battery-free, personal mobile gaming device powered by energy harvested from gamer actions and sunlight. Our design implements a power failure resilient Nintendo Game Boy emulator that can run off-the-shelf classic Game Boy games like Tetris or Super Mario Land. Beyond a fun toy, our design represents the first battery-free system design for continuous user attention despite frequent power failures caused by intermittent energy harvesting.","PeriodicalId":29918,"journal":{"name":"GetMobile-Mobile Computing & Communications Review","volume":"2 1","pages":"22 - 26"},"PeriodicalIF":1.0,"publicationDate":"2021-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87493136","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}
J. Oostvogels, F. Yang, Sam Michiels, W. Joosen, D. Hughes
Latency-sensitive applications for the Internet of Things (IoT) often require performance guarantees that contemporary wireless networks fail to offer. Application scenarios involving real-time control of industrial machinery, robotics, or delay-sensitive actuation therefore typically still rely on cables: today's wireless networks cannot deliver messages in a sufficiently small and predictable amount of time. Drop-in wireless replacements for these cabled systems would nevertheless provide great benefit by eliminating the high cost and complexity associated with running cables in harsh industrial environments [1]. The symbolsynchronous bus, introduced in this article and embodied in a platform called Zero-Wire, is a novel wireless networking paradigm that addresses this gap. Using concurrent optical transmissions, it strives to bring low-latency deterministic networking to the wireless IoT.
{"title":"Zero-Wire","authors":"J. Oostvogels, F. Yang, Sam Michiels, W. Joosen, D. Hughes","doi":"10.1145/3471440.3471450","DOIUrl":"https://doi.org/10.1145/3471440.3471450","url":null,"abstract":"Latency-sensitive applications for the Internet of Things (IoT) often require performance guarantees that contemporary wireless networks fail to offer. Application scenarios involving real-time control of industrial machinery, robotics, or delay-sensitive actuation therefore typically still rely on cables: today's wireless networks cannot deliver messages in a sufficiently small and predictable amount of time. Drop-in wireless replacements for these cabled systems would nevertheless provide great benefit by eliminating the high cost and complexity associated with running cables in harsh industrial environments [1]. The symbolsynchronous bus, introduced in this article and embodied in a platform called Zero-Wire, is a novel wireless networking paradigm that addresses this gap. Using concurrent optical transmissions, it strives to bring low-latency deterministic networking to the wireless IoT.","PeriodicalId":29918,"journal":{"name":"GetMobile-Mobile Computing & Communications Review","volume":"13 1","pages":"34 - 38"},"PeriodicalIF":1.0,"publicationDate":"2021-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87816511","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}
With the rapid increase of high-fidelity audio, video, and multimedia traffic in the new era of 5G and beyond, the current Wi-Fi solution exhibits more and more limitations. Crowded spectrum is creating realistic bottlenecks in the deployment of Wi-Fi, some of which can be well alleviated by the Light Fidelity (Li-Fi) technology. High transmission rate, wide bandwidth, no electromagnetic interference, and no health hazards have made Li-Fi an attractive technique for future smallcell communication. The emerging standardization of visible light communication (VLC) facilitates the acceleration of the development of Li-Fi technology and will eventually deliver real-world Li-Fi deployments. This article overviews the recent progress on VLC standardization and presents the mainstream VLC standards created by different standardization organizations.
{"title":"A Survey on Visible Light Communication Standards","authors":"Jian Chen, Tian Liu, Tao Shu","doi":"10.1145/3471440.3471444","DOIUrl":"https://doi.org/10.1145/3471440.3471444","url":null,"abstract":"With the rapid increase of high-fidelity audio, video, and multimedia traffic in the new era of 5G and beyond, the current Wi-Fi solution exhibits more and more limitations. Crowded spectrum is creating realistic bottlenecks in the deployment of Wi-Fi, some of which can be well alleviated by the Light Fidelity (Li-Fi) technology. High transmission rate, wide bandwidth, no electromagnetic interference, and no health hazards have made Li-Fi an attractive technique for future smallcell communication. The emerging standardization of visible light communication (VLC) facilitates the acceleration of the development of Li-Fi technology and will eventually deliver real-world Li-Fi deployments. This article overviews the recent progress on VLC standardization and presents the mainstream VLC standards created by different standardization organizations.","PeriodicalId":29918,"journal":{"name":"GetMobile-Mobile Computing & Communications Review","volume":"37 1","pages":"9 - 15"},"PeriodicalIF":1.0,"publicationDate":"2021-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76920909","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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