{"title":"Session details: Leveraging Mobility","authors":"R. Kravets","doi":"10.1145/3257165","DOIUrl":"https://doi.org/10.1145/3257165","url":null,"abstract":"","PeriodicalId":309322,"journal":{"name":"Proceedings of the 18th International Workshop on Mobile Computing Systems and Applications","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117188744","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}
{"title":"Session details: New Ideas in Radio Sensing and Coverage","authors":"G. Pau","doi":"10.1145/3257161","DOIUrl":"https://doi.org/10.1145/3257161","url":null,"abstract":"","PeriodicalId":309322,"journal":{"name":"Proceedings of the 18th International Workshop on Mobile Computing Systems and Applications","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121462814","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}
Ho-Kyeong Ra, Jungmo Ahn, Hee-Jung Yoon, D. Yoon, S. Son, Jeonggil Ko
With the wide-distribution of smart wearables, it seems as though ubiquitous healthcare can finally permeate into our everyday lives, opening the possibility to realize clinical-grade applications. However, given that clinical applications require reliable sensing, there is a need to understand how accurate healthcare sensors on wearable devices (e.g., heart rate sensors) are. To answer this question, this work starts with a thorough investigation on the accuracy of widely used wearable devices' heart rate sensors. Specifically, we show that when actively moving, heart rate readings can diverge far from the ground truth, and also show that such inaccuracies cannot be easily correlated, nor predicted, using accelerometer and gyroscope measurements. Rather, we point out that the light intensity readings at the photoplethysmography (PPG) sensor can be an effective indicator of heart rate accuracy. Using a Viterbi algorithm-based Hidden Markov Model, we show that it is possible to design a filter that allows smartwatches to self-classify measurement quality with ~ 98% accuracy. Given that such capabilities allow the smartwatch to internally filter misleading values from being application input, we foresee this as an essential step in catalyzing novel clinical-grade wearable applications.
{"title":"I am a \"Smart\" watch, Smart Enough to Know the Accuracy of My Own Heart Rate Sensor","authors":"Ho-Kyeong Ra, Jungmo Ahn, Hee-Jung Yoon, D. Yoon, S. Son, Jeonggil Ko","doi":"10.1145/3032970.3032977","DOIUrl":"https://doi.org/10.1145/3032970.3032977","url":null,"abstract":"With the wide-distribution of smart wearables, it seems as though ubiquitous healthcare can finally permeate into our everyday lives, opening the possibility to realize clinical-grade applications. However, given that clinical applications require reliable sensing, there is a need to understand how accurate healthcare sensors on wearable devices (e.g., heart rate sensors) are. To answer this question, this work starts with a thorough investigation on the accuracy of widely used wearable devices' heart rate sensors. Specifically, we show that when actively moving, heart rate readings can diverge far from the ground truth, and also show that such inaccuracies cannot be easily correlated, nor predicted, using accelerometer and gyroscope measurements. Rather, we point out that the light intensity readings at the photoplethysmography (PPG) sensor can be an effective indicator of heart rate accuracy. Using a Viterbi algorithm-based Hidden Markov Model, we show that it is possible to design a filter that allows smartwatches to self-classify measurement quality with ~ 98% accuracy. Given that such capabilities allow the smartwatch to internally filter misleading values from being application input, we foresee this as an essential step in catalyzing novel clinical-grade wearable applications.","PeriodicalId":309322,"journal":{"name":"Proceedings of the 18th International Workshop on Mobile Computing Systems and Applications","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132190812","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}
{"title":"Session details: Towards Happier Mobile Users","authors":"R. Likamwa","doi":"10.1145/3257162","DOIUrl":"https://doi.org/10.1145/3257162","url":null,"abstract":"","PeriodicalId":309322,"journal":{"name":"Proceedings of the 18th International Workshop on Mobile Computing Systems and Applications","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131472986","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}
Guru Prasad Srinivasa, R. Begum, Scott Haseley, Mark Hempstead, Geoffrey Challen
Smartphone consumers, app developers, and even mobile systems researchers operate under the assumption that performance differences between identical smartphones should be small. Consumers pick a model to purchase and don't consider that the specific device they leave the store with may vary quite dramatically from the identical models it sat next to on the shelf. App rating systems typically collect the model from reviewers, but not more detailed information-again, assuming that all instances of a particular model perform similarly. Even mobile systems researchers will conduct studies using small numbers of devices that fail to account or control for inherent differences between identical phones. Unfortunately seemingly-identical smartphones can in fact have very different performance characteristics. Note that we are not referring to differences in battery or Flash performance caused over time by wear. Inherent differences would separate two brand-new phones still in the original packaging. Our experiments show up to 20% performance and energy consumption differences between otherwise identical devices. These differences result from process variation in the manufacture of smartphone CPUs, which causes some CPUs to perform much more poorly than others. This paper explains the causes of this variation, measures its impacts, and discusses implications for smartphone researchers, software developers, and consumers.
{"title":"Separated By Birth: Hidden Differences Between Seemingly-Identical Smartphone CPUs","authors":"Guru Prasad Srinivasa, R. Begum, Scott Haseley, Mark Hempstead, Geoffrey Challen","doi":"10.1145/3032970.3032982","DOIUrl":"https://doi.org/10.1145/3032970.3032982","url":null,"abstract":"Smartphone consumers, app developers, and even mobile systems researchers operate under the assumption that performance differences between identical smartphones should be small. Consumers pick a model to purchase and don't consider that the specific device they leave the store with may vary quite dramatically from the identical models it sat next to on the shelf. App rating systems typically collect the model from reviewers, but not more detailed information-again, assuming that all instances of a particular model perform similarly. Even mobile systems researchers will conduct studies using small numbers of devices that fail to account or control for inherent differences between identical phones. Unfortunately seemingly-identical smartphones can in fact have very different performance characteristics. Note that we are not referring to differences in battery or Flash performance caused over time by wear. Inherent differences would separate two brand-new phones still in the original packaging. Our experiments show up to 20% performance and energy consumption differences between otherwise identical devices. These differences result from process variation in the manufacture of smartphone CPUs, which causes some CPUs to perform much more poorly than others. This paper explains the causes of this variation, measures its impacts, and discusses implications for smartphone researchers, software developers, and consumers.","PeriodicalId":309322,"journal":{"name":"Proceedings of the 18th International Workshop on Mobile Computing Systems and Applications","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130780163","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}
K. T. W. Choo, R. Balan, Tan Kiat Wee, Jagmohan Chauhan, Archan Misra, Youngki Lee
We describe our vision for Empath-D, our system to enable Empathetic User Interface Design. Our key idea is to leverage Virtual and Augmented Reality (VR / AR) displays to provide an Immersive Reality environment, where developers/designers can emulate impaired interactions by elderly or disabled users while testing the usability of their applications. Our early experiences with the Empath-D prototype show that Empath-D can emulate a cataract vision impairment of the elderly and guide designers to create accessible web pages with less mental workload.
{"title":"Empath-D: Empathetic Design for Accessibility","authors":"K. T. W. Choo, R. Balan, Tan Kiat Wee, Jagmohan Chauhan, Archan Misra, Youngki Lee","doi":"10.1145/3032970.3032981","DOIUrl":"https://doi.org/10.1145/3032970.3032981","url":null,"abstract":"We describe our vision for Empath-D, our system to enable Empathetic User Interface Design. Our key idea is to leverage Virtual and Augmented Reality (VR / AR) displays to provide an Immersive Reality environment, where developers/designers can emulate impaired interactions by elderly or disabled users while testing the usability of their applications. Our early experiences with the Empath-D prototype show that Empath-D can emulate a cataract vision impairment of the elderly and guide designers to create accessible web pages with less mental workload.","PeriodicalId":309322,"journal":{"name":"Proceedings of the 18th International Workshop on Mobile Computing Systems and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128985278","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. Rasekh, Zhinus Marzi, Yanzi Zhu, Upamanyu Madhow, Haitao Zheng
Millimeter (mm) wave picocellular networks have the potential for providing the 1000X capacity increase required to keep up with the explosive growth of mobile data. However, maintaining beams towards mobile users and adapting to frequent blockage, requires efficient, dynamic path tracking algorithms. In this paper, we develop and experimentally demonstrate a novel noncoherent compressive strategy for this problem, and compare it with conventional hierarchical and exhaustive beam scanning. To the best of our knowledge, this is the first experimental demonstration of practical, scalable path estimation for mmWave/60GHz picocells. Our results indicate the feasibility of sub-second path tracking with low overhead on today's mmWave hardware, and open up a rich space for design of 5G mmWave networks.
{"title":"Noncoherent mmWave Path Tracking","authors":"M. Rasekh, Zhinus Marzi, Yanzi Zhu, Upamanyu Madhow, Haitao Zheng","doi":"10.1145/3032970.3032974","DOIUrl":"https://doi.org/10.1145/3032970.3032974","url":null,"abstract":"Millimeter (mm) wave picocellular networks have the potential for providing the 1000X capacity increase required to keep up with the explosive growth of mobile data. However, maintaining beams towards mobile users and adapting to frequent blockage, requires efficient, dynamic path tracking algorithms. In this paper, we develop and experimentally demonstrate a novel noncoherent compressive strategy for this problem, and compare it with conventional hierarchical and exhaustive beam scanning. To the best of our knowledge, this is the first experimental demonstration of practical, scalable path estimation for mmWave/60GHz picocells. Our results indicate the feasibility of sub-second path tracking with low overhead on today's mmWave hardware, and open up a rich space for design of 5G mmWave networks.","PeriodicalId":309322,"journal":{"name":"Proceedings of the 18th International Workshop on Mobile Computing Systems and Applications","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126377710","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}
As cities ramp up the efforts to convert their aging lighting infrastructure to connected and energy-efficient Light-Emitting Diodes (LEDs), they are confounded by the lack of reliable information about their existing outdoor lighting bases. In this paper, we propose a vehicle-mounted spectrom etry-based approach to scalably audit the roadway lamp types by driving across the city, thereby quickly and efficiently providing the basis for planning and executing LED conversion projects. LambdaSeek, a mobile sensing system that can be mounted on a vehicle, is developed to reliably capture the Spectral Power Distributions (SPDs) of the light emitted by the luminaires on the light poles by driving around the city. The on-board illuminance sensor and the global positioning system receiver helps to localize the SPDs, which are then classified into the corresponding lamp types using a k-Nearest Neighbor classification algorithm. Validation experiments across four field trials are presented: the most commonly found High-Pressure Sodium, Mercury Vapor, Metal Halide and LED lamps were classified correctly with a recall rate of more than 95%.
{"title":"Automated Lamp-Type Identification for City-Wide Outdoor Lighting Infrastructures","authors":"Shengrong Yin, Talmai Oliveira, A. Murthy","doi":"10.1145/3032970.3032980","DOIUrl":"https://doi.org/10.1145/3032970.3032980","url":null,"abstract":"As cities ramp up the efforts to convert their aging lighting infrastructure to connected and energy-efficient Light-Emitting Diodes (LEDs), they are confounded by the lack of reliable information about their existing outdoor lighting bases. In this paper, we propose a vehicle-mounted spectrom etry-based approach to scalably audit the roadway lamp types by driving across the city, thereby quickly and efficiently providing the basis for planning and executing LED conversion projects. LambdaSeek, a mobile sensing system that can be mounted on a vehicle, is developed to reliably capture the Spectral Power Distributions (SPDs) of the light emitted by the luminaires on the light poles by driving around the city. The on-board illuminance sensor and the global positioning system receiver helps to localize the SPDs, which are then classified into the corresponding lamp types using a k-Nearest Neighbor classification algorithm. Validation experiments across four field trials are presented: the most commonly found High-Pressure Sodium, Mercury Vapor, Metal Halide and LED lamps were classified correctly with a recall rate of more than 95%.","PeriodicalId":309322,"journal":{"name":"Proceedings of the 18th International Workshop on Mobile Computing Systems and Applications","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125848829","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}
Benchmarking the performance of mobile devices such as Android-based smartphones is important in understanding and comparing the performance of different devices. Performance benchmarking tools such as Antutu have been widely used in both academia and industry. However, one of the main difficulties when benchmarking smartphone performance is due to the fact that the performance cannot be measured accurately and steadily. This paper investigates the challenges on performance benchmarking for Android-based smartphones. We identify key factors affecting performance benchmarking, which include frequency scaling setting, temperature, running background services, etc. Experiments show that some of these factors may cause performance fluctuation by as high as 60%. We show preliminary results in controlling the performance benchmarking process to generate steady results, for example freezing a smartphone in a refrigerator could remove most of the fluctuations. Finally, we discuss the implications of our study and possible future research directions.
{"title":"Freeze It If You Can: Challenges and Future Directions in Benchmarking Smartphone Performance","authors":"Yao Guo, Yunnan Xu, Xiangqun Chen","doi":"10.1145/3032970.3032979","DOIUrl":"https://doi.org/10.1145/3032970.3032979","url":null,"abstract":"Benchmarking the performance of mobile devices such as Android-based smartphones is important in understanding and comparing the performance of different devices. Performance benchmarking tools such as Antutu have been widely used in both academia and industry. However, one of the main difficulties when benchmarking smartphone performance is due to the fact that the performance cannot be measured accurately and steadily. This paper investigates the challenges on performance benchmarking for Android-based smartphones. We identify key factors affecting performance benchmarking, which include frequency scaling setting, temperature, running background services, etc. Experiments show that some of these factors may cause performance fluctuation by as high as 60%. We show preliminary results in controlling the performance benchmarking process to generate steady results, for example freezing a smartphone in a refrigerator could remove most of the fluctuations. Finally, we discuss the implications of our study and possible future research directions.","PeriodicalId":309322,"journal":{"name":"Proceedings of the 18th International Workshop on Mobile Computing Systems and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129524850","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}
{"title":"Session details: Fresh Insights and Directions for Mobile Performance Testing","authors":"A. A. Sani","doi":"10.1145/3257167","DOIUrl":"https://doi.org/10.1145/3257167","url":null,"abstract":"","PeriodicalId":309322,"journal":{"name":"Proceedings of the 18th International Workshop on Mobile Computing Systems and Applications","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130936376","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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