Supriyo Chakraborty, K. Raghavan, Matthew P. Johnson, M. Srivastava
We study the competing goals of utility and privacy as they arise when a user shares personal sensor data with apps on a smartphone. On the one hand, there can be value to the user for sharing data in the form of various personalized services and recommendations; on the other hand, there is the risk of revealing behaviors to the app producers that the user would like to keep private. The current approaches to privacy, usually defined in multi-user settings, rely on anonymization to prevent such sensitive behaviors from being traced back to the user---a strategy which does not apply if user identity is already known, as is the case here. Instead of protecting identity, we focus on the more general problem of choosing what data to share, in such a way that certain kinds of inferences---i.e., those indicating the user's sensitive behavior---cannot be drawn. The use of inference functions allows us to establish a terminology to unify prior notions of privacy as special cases of this more general problem. We identify several information disclosure regimes, each corresponding to a specific privacy-utility tradeoff, as well as privacy mechanisms designed to realize these tradeoff points. Finally, we propose ipShield as a privacy-aware framework which uses current user context together with a model of user behavior to quantify an adversary's knowledge regarding a sensitive inference, and obfuscate data accordingly before sharing. We conclude by describing initial work towards realizing this framework.
{"title":"A framework for context-aware privacy of sensor data on mobile systems","authors":"Supriyo Chakraborty, K. Raghavan, Matthew P. Johnson, M. Srivastava","doi":"10.1145/2444776.2444791","DOIUrl":"https://doi.org/10.1145/2444776.2444791","url":null,"abstract":"We study the competing goals of utility and privacy as they arise when a user shares personal sensor data with apps on a smartphone. On the one hand, there can be value to the user for sharing data in the form of various personalized services and recommendations; on the other hand, there is the risk of revealing behaviors to the app producers that the user would like to keep private. The current approaches to privacy, usually defined in multi-user settings, rely on anonymization to prevent such sensitive behaviors from being traced back to the user---a strategy which does not apply if user identity is already known, as is the case here.\u0000 Instead of protecting identity, we focus on the more general problem of choosing what data to share, in such a way that certain kinds of inferences---i.e., those indicating the user's sensitive behavior---cannot be drawn. The use of inference functions allows us to establish a terminology to unify prior notions of privacy as special cases of this more general problem. We identify several information disclosure regimes, each corresponding to a specific privacy-utility tradeoff, as well as privacy mechanisms designed to realize these tradeoff points. Finally, we propose ipShield as a privacy-aware framework which uses current user context together with a model of user behavior to quantify an adversary's knowledge regarding a sensitive inference, and obfuscate data accordingly before sharing. We conclude by describing initial work towards realizing this framework.","PeriodicalId":88972,"journal":{"name":"Proceedings. IEEE Workshop on Mobile Computing Systems and Applications","volume":"16 1","pages":"11"},"PeriodicalIF":0.0,"publicationDate":"2013-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81656041","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}
Yu Xiao, P. Simoens, P. Pillai, Kiryong Ha, M. Satyanarayanan
Mobile crowdsensing is becoming a vital technique for environment monitoring, infrastructure management, and social computing. However, deploying mobile crowdsensing applications in large-scale environments is not a trivial task. It creates a tremendous burden on application developers as well as mobile users. In this paper we try to reveal the barriers hampering the scale-up of mobile crowdsensing applications, and to offer our initial thoughts on the potential solutions to lowering the barriers.
{"title":"Lowering the barriers to large-scale mobile crowdsensing","authors":"Yu Xiao, P. Simoens, P. Pillai, Kiryong Ha, M. Satyanarayanan","doi":"10.1145/2444776.2444789","DOIUrl":"https://doi.org/10.1145/2444776.2444789","url":null,"abstract":"Mobile crowdsensing is becoming a vital technique for environment monitoring, infrastructure management, and social computing. However, deploying mobile crowdsensing applications in large-scale environments is not a trivial task. It creates a tremendous burden on application developers as well as mobile users. In this paper we try to reveal the barriers hampering the scale-up of mobile crowdsensing applications, and to offer our initial thoughts on the potential solutions to lowering the barriers.","PeriodicalId":88972,"journal":{"name":"Proceedings. IEEE Workshop on Mobile Computing Systems and Applications","volume":"100 1","pages":"9"},"PeriodicalIF":0.0,"publicationDate":"2013-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85788842","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}
S. Nirjon, Robert F. Dickerson, J. Stankovic, G. Shen, Xiaofan Jiang
Due to limited processing capability, contemporary smartphones cannot extract frequency domain acoustic features in real-time on the device when the sampling rate is high. We propose a solution to this problem which exploits the sparseness in speech to extract frequency domain acoustic features inside a smartphone in real-time, without requiring any support from a remote server even when the sampling rate is as high as 44.1 KHz. We perform an empirical study to quantify the sparseness in speech recorded on a smartphone and use it to obtain a highly accurate and sparse approximation of a widely used feature of speech called the Mel-Frequency Cepstral Coefficients (MFCC) efficiently. We name the new feature the sparse MFCC or sMFCC, in short. We experimentally determine the trade-offs between the approximation error and the expected speedup of sMFCC. We implement a simple spoken word recognition application using both MFCC and sMFCC features, show that sMFCC is expected to be up to 5.84 times faster and its accuracy is within 1.1% -- 3.9% of that of MFCC, and determine the conditions under which sMFCC runs in real-time.
{"title":"sMFCC: exploiting sparseness in speech for fast acoustic feature extraction on mobile devices -- a feasibility study","authors":"S. Nirjon, Robert F. Dickerson, J. Stankovic, G. Shen, Xiaofan Jiang","doi":"10.1145/2444776.2444787","DOIUrl":"https://doi.org/10.1145/2444776.2444787","url":null,"abstract":"Due to limited processing capability, contemporary smartphones cannot extract frequency domain acoustic features in real-time on the device when the sampling rate is high. We propose a solution to this problem which exploits the sparseness in speech to extract frequency domain acoustic features inside a smartphone in real-time, without requiring any support from a remote server even when the sampling rate is as high as 44.1 KHz. We perform an empirical study to quantify the sparseness in speech recorded on a smartphone and use it to obtain a highly accurate and sparse approximation of a widely used feature of speech called the Mel-Frequency Cepstral Coefficients (MFCC) efficiently. We name the new feature the sparse MFCC or sMFCC, in short. We experimentally determine the trade-offs between the approximation error and the expected speedup of sMFCC. We implement a simple spoken word recognition application using both MFCC and sMFCC features, show that sMFCC is expected to be up to 5.84 times faster and its accuracy is within 1.1% -- 3.9% of that of MFCC, and determine the conditions under which sMFCC runs in real-time.","PeriodicalId":88972,"journal":{"name":"Proceedings. IEEE Workshop on Mobile Computing Systems and Applications","volume":"15 1","pages":"8"},"PeriodicalIF":0.0,"publicationDate":"2013-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91136773","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}
Blerim Cici, A. Markopoulou, E. Frías-Martínez, Nikolaos Laoutaris
Ride-sharing on the daily home-work-home commute can help individuals save on gasoline and other car-related costs, while at the same time reducing traffic and pollution in the city. Work in this area has typically focused on technology, usability, security, and legal issues. However, the success of any ride-sharing technology relies on the implicit assumption that human mobility patterns and city layouts exhibit enough route overlap to allow for ride-sharing on the first place. In this paper we validate this assumption using mobility data extracted from city-wide Call Description Records (CDRs) from the city of Madrid. We derive an upper bound on the effectiveness of ride-sharing by making the simplifying assumption that any commuter can share a ride with any other as long as their routes overlap. We show that simple ride-sharing among people having neighboring home and work locations can reduce the number of cars in the city at the expense of a relatively short detour to pick up/drop off passengers; e.g., for a 0.6 km detour, there is a 52% reduction in the number of cars. Smartphone technology enables additional passengers to be picked up along the way, which can further reduce the number of cars, as much as 67%.
{"title":"Quantifying the potential of ride-sharing using call description records","authors":"Blerim Cici, A. Markopoulou, E. Frías-Martínez, Nikolaos Laoutaris","doi":"10.1145/2444776.2444799","DOIUrl":"https://doi.org/10.1145/2444776.2444799","url":null,"abstract":"Ride-sharing on the daily home-work-home commute can help individuals save on gasoline and other car-related costs, while at the same time reducing traffic and pollution in the city. Work in this area has typically focused on technology, usability, security, and legal issues. However, the success of any ride-sharing technology relies on the implicit assumption that human mobility patterns and city layouts exhibit enough route overlap to allow for ride-sharing on the first place. In this paper we validate this assumption using mobility data extracted from city-wide Call Description Records (CDRs) from the city of Madrid. We derive an upper bound on the effectiveness of ride-sharing by making the simplifying assumption that any commuter can share a ride with any other as long as their routes overlap. We show that simple ride-sharing among people having neighboring home and work locations can reduce the number of cars in the city at the expense of a relatively short detour to pick up/drop off passengers; e.g., for a 0.6 km detour, there is a 52% reduction in the number of cars. Smartphone technology enables additional passengers to be picked up along the way, which can further reduce the number of cars, as much as 67%.","PeriodicalId":88972,"journal":{"name":"Proceedings. IEEE Workshop on Mobile Computing Systems and Applications","volume":"25 1","pages":"17"},"PeriodicalIF":0.0,"publicationDate":"2013-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76122863","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}
Xiang Chen, Yiran Chen, Zhan Ma, Felix C. A. Fernandes
Smartphones have emerged as a popular and frequently used platform for the consumption of multimedia. New display technologies, such as AMOLED, have been recently introduced to smartphones to fulfill the requirements of these multimedia applications. However, as an AMOLED screen's power consumption is determined by the display content, such applications are often limited by the battery life of the device they are running on, inspiring many researches to develop new power management schemes. In this work, we evaluate the power consumption of several applications on a series of Samsung smartphones and take a deep look into AMOLED's power consumption and its relative contributions for multimedia apps. We improve AMOLED power analysis by considering the dynamic factors in displaying, and analyze the individual factors affecting power consumption when streaming video, playing a video game, and recording video via a device's built-in camera. Our detailed measurements refine the power analysis of smartphones and reveal some interesting perspectives regarding the power consumption of AMOLED displays in multimedia applications.
{"title":"How is energy consumed in smartphone display applications?","authors":"Xiang Chen, Yiran Chen, Zhan Ma, Felix C. A. Fernandes","doi":"10.1145/2444776.2444781","DOIUrl":"https://doi.org/10.1145/2444776.2444781","url":null,"abstract":"Smartphones have emerged as a popular and frequently used platform for the consumption of multimedia. New display technologies, such as AMOLED, have been recently introduced to smartphones to fulfill the requirements of these multimedia applications. However, as an AMOLED screen's power consumption is determined by the display content, such applications are often limited by the battery life of the device they are running on, inspiring many researches to develop new power management schemes. In this work, we evaluate the power consumption of several applications on a series of Samsung smartphones and take a deep look into AMOLED's power consumption and its relative contributions for multimedia apps. We improve AMOLED power analysis by considering the dynamic factors in displaying, and analyze the individual factors affecting power consumption when streaming video, playing a video game, and recording video via a device's built-in camera. Our detailed measurements refine the power analysis of smartphones and reveal some interesting perspectives regarding the power consumption of AMOLED displays in multimedia applications.","PeriodicalId":88972,"journal":{"name":"Proceedings. IEEE Workshop on Mobile Computing Systems and Applications","volume":"21 1","pages":"3"},"PeriodicalIF":0.0,"publicationDate":"2013-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83894004","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 display cloud model allows users to select local and remote programmable displays, and add them to a user specific cloud display where the user can arrange them freely. On a cloud display, the abstraction representing remote graphical content is termed a visual. It can be positioned and resized freely. Wherever a visual touches a part of the cloud display with physical displays present, the physical displays will show the corresponding graphical content of the visual. The physical displays can simultaneously show several visuals from one or many users. The display cloud approach is suitable for public environments because we do not allow user customization of the displays, a user does not have to expose any data except the actual graphical content to the display computers, and he does not have to go through the displays to do user interaction with his resources. Mobile devices have an essential role in achieving this. They provide, for each user, the means to detect displays, to add displays to the user's cloud display, to manage displays and visuals in a cloud display, and to interact with visuals. An insight is that the display cloud model is maximally decentralized between users, and maximally centralized per user. We conducted a set of experiments on a prototype using 28 display computers with up to 21 users. The results show that the prototype reacts interactively fast for each, and scales well to many users.
{"title":"Cloud displays for mobile users in a display cloud","authors":"Lars Tiede, J. Bjørndalen, Otto J. Anshus","doi":"10.1145/2444776.2444793","DOIUrl":"https://doi.org/10.1145/2444776.2444793","url":null,"abstract":"The display cloud model allows users to select local and remote programmable displays, and add them to a user specific cloud display where the user can arrange them freely. On a cloud display, the abstraction representing remote graphical content is termed a visual. It can be positioned and resized freely. Wherever a visual touches a part of the cloud display with physical displays present, the physical displays will show the corresponding graphical content of the visual. The physical displays can simultaneously show several visuals from one or many users.\u0000 The display cloud approach is suitable for public environments because we do not allow user customization of the displays, a user does not have to expose any data except the actual graphical content to the display computers, and he does not have to go through the displays to do user interaction with his resources. Mobile devices have an essential role in achieving this. They provide, for each user, the means to detect displays, to add displays to the user's cloud display, to manage displays and visuals in a cloud display, and to interact with visuals.\u0000 An insight is that the display cloud model is maximally decentralized between users, and maximally centralized per user. We conducted a set of experiments on a prototype using 28 display computers with up to 21 users. The results show that the prototype reacts interactively fast for each, and scales well to many users.","PeriodicalId":88972,"journal":{"name":"Proceedings. IEEE Workshop on Mobile Computing Systems and Applications","volume":"158 1","pages":"12"},"PeriodicalIF":0.0,"publicationDate":"2013-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88848095","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}
Michael Butkiewicz, Zhe Wu, Shunan Li, P. Murali, Vagelis Hristidis, H. Madhyastha, V. Sekar
Web access on mobile platforms already constitutes a significant (> 20%) share of web traffic [3]. Furthermore, this share is projected to even surpass access from laptops and desktops [11]. In conjunction with this growth, user expectations for the performance of mobile applications and websites is also growing rapidly [15]. Surveys show that 71% of users expect websites to load almost as quickly as their desktops and 33% of annoyed users are likely to go to a competitor's site leading to loss of ad- and click-based revenue streams [1].
{"title":"Enabling the transition to the mobile web with WebSieve","authors":"Michael Butkiewicz, Zhe Wu, Shunan Li, P. Murali, Vagelis Hristidis, H. Madhyastha, V. Sekar","doi":"10.1145/2444776.2444795","DOIUrl":"https://doi.org/10.1145/2444776.2444795","url":null,"abstract":"Web access on mobile platforms already constitutes a significant (> 20%) share of web traffic [3]. Furthermore, this share is projected to even surpass access from laptops and desktops [11]. In conjunction with this growth, user expectations for the performance of mobile applications and websites is also growing rapidly [15]. Surveys show that 71% of users expect websites to load almost as quickly as their desktops and 33% of annoyed users are likely to go to a competitor's site leading to loss of ad- and click-based revenue streams [1].","PeriodicalId":88972,"journal":{"name":"Proceedings. IEEE Workshop on Mobile Computing Systems and Applications","volume":"43 2 1","pages":"14"},"PeriodicalIF":0.0,"publicationDate":"2013-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78207939","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 mobile computing experience would improve if users could switch seamlessly from one device to another, with both data and computation state preserved across the switch without apparent delay. This paper proposes VMsync, a system for synchronizing the state of live virtual machines (VMs) among mobile devices. VMsync seeks to incrementally transfer changes in an active VM on one device to standby VMs in other devices, so as to maintain a consistent VM image and minimize switching latency. However, constraints of the mobile environment make these goals difficult to achieve and raise many research questions. We present our preliminary design for VMsync and a feasibility study aimed at determining how much data would need to be transferred under different mobile workloads and synchronization policies. For example, through experiments with a Xen VM running Android and playing a YouTube video, we show that sending dirty memory pages transfers 3 times more data than sending only the bytes that actually changed in those pages. Overall, we conclude that VMsync is a feasible approach deserving of further research.
{"title":"Towards synchronization of live virtual machines among mobile devices","authors":"Jeffrey Bickford, R. Cáceres","doi":"10.1145/2444776.2444794","DOIUrl":"https://doi.org/10.1145/2444776.2444794","url":null,"abstract":"The mobile computing experience would improve if users could switch seamlessly from one device to another, with both data and computation state preserved across the switch without apparent delay. This paper proposes VMsync, a system for synchronizing the state of live virtual machines (VMs) among mobile devices. VMsync seeks to incrementally transfer changes in an active VM on one device to standby VMs in other devices, so as to maintain a consistent VM image and minimize switching latency. However, constraints of the mobile environment make these goals difficult to achieve and raise many research questions. We present our preliminary design for VMsync and a feasibility study aimed at determining how much data would need to be transferred under different mobile workloads and synchronization policies. For example, through experiments with a Xen VM running Android and playing a YouTube video, we show that sending dirty memory pages transfers 3 times more data than sending only the bytes that actually changed in those pages. Overall, we conclude that VMsync is a feasible approach deserving of further research.","PeriodicalId":88972,"journal":{"name":"Proceedings. IEEE Workshop on Mobile Computing Systems and Applications","volume":"1 1","pages":"13"},"PeriodicalIF":0.0,"publicationDate":"2013-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80841830","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}
Tianyu Wang, Giuseppe Cardone, Antonio Corradi, L. Torresani, A. Campbell
Research in social science has shown that mobile phone conversations distract users, presenting a significant impact to pedestrian safety; for example, a mobile phone user deep in conversation while crossing a street is generally more at risk than other pedestrians not engaged in such behavior. We propose WalkSafe, an Android smartphone application that aids people that walk and talk, improving the safety of pedestrian mobile phone users. WalkSafe uses the back camera of the mobile phone to detect vehicles approaching the user, alerting the user of a potentially unsafe situation; more specifically WalkSafe i) uses machine learning algorithms implemented on the phone to detect the front views and back views of moving vehicles and ii) exploits phone APIs to save energy by running the vehicle detection algorithm only during active calls. We present our initial design, implementation and evaluation of the WalkSafe App that is capable of real-time detection of the front and back views of cars, indicating cars are approaching or moving away from the user, respectively. WalkSafe is implemented on Android phones and alerts the user of unsafe conditions using sound and vibration from the phone. WalkSafe is available on Android Market.
{"title":"WalkSafe: a pedestrian safety app for mobile phone users who walk and talk while crossing roads","authors":"Tianyu Wang, Giuseppe Cardone, Antonio Corradi, L. Torresani, A. Campbell","doi":"10.1145/2162081.2162089","DOIUrl":"https://doi.org/10.1145/2162081.2162089","url":null,"abstract":"Research in social science has shown that mobile phone conversations distract users, presenting a significant impact to pedestrian safety; for example, a mobile phone user deep in conversation while crossing a street is generally more at risk than other pedestrians not engaged in such behavior. We propose WalkSafe, an Android smartphone application that aids people that walk and talk, improving the safety of pedestrian mobile phone users. WalkSafe uses the back camera of the mobile phone to detect vehicles approaching the user, alerting the user of a potentially unsafe situation; more specifically WalkSafe i) uses machine learning algorithms implemented on the phone to detect the front views and back views of moving vehicles and ii) exploits phone APIs to save energy by running the vehicle detection algorithm only during active calls. We present our initial design, implementation and evaluation of the WalkSafe App that is capable of real-time detection of the front and back views of cars, indicating cars are approaching or moving away from the user, respectively. WalkSafe is implemented on Android phones and alerts the user of unsafe conditions using sound and vibration from the phone. WalkSafe is available on Android Market.","PeriodicalId":88972,"journal":{"name":"Proceedings. IEEE Workshop on Mobile Computing Systems and Applications","volume":"1 1","pages":"5"},"PeriodicalIF":0.0,"publicationDate":"2012-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82849399","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}
Zheng Sun, Aveek Purohit, Shijia Pan, Frank Mokaya, R. Bose, Pei Zhang
Ubiquitous computing applications commonly use digital compass sensors to obtain orientation of a device relative to the magnetic north of the earth. However, these compass readings are always prone to significant errors in indoor environments due to presence of metallic objects in close proximity. Such errors can adversely affect the performance and quality of user experience of the applications utilizing digital compass sensors. In this paper, we propose Polaris, a novel approach to provide reliable orientation information for mobile devices in indoor environments. Polaris achieves this by aggregating pictures of the ceiling of an indoor environment and applies computer vision based pattern matching techniques to utilize them as orientation references for correcting digital compass readings. To show the feasibility of the Polaris system, we implemented the Polaris system on mobile devices, and field tested the system in multiple office buildings. Our results show that Polaris achieves 4.5° average orientation accuracy, which is about 3.5 times better than what can be achieved through sole use of raw digital compass readings.
{"title":"Polaris: getting accurate indoor orientations for mobile devices using ubiquitous visual patterns on ceilings","authors":"Zheng Sun, Aveek Purohit, Shijia Pan, Frank Mokaya, R. Bose, Pei Zhang","doi":"10.1145/2162081.2162101","DOIUrl":"https://doi.org/10.1145/2162081.2162101","url":null,"abstract":"Ubiquitous computing applications commonly use digital compass sensors to obtain orientation of a device relative to the magnetic north of the earth. However, these compass readings are always prone to significant errors in indoor environments due to presence of metallic objects in close proximity. Such errors can adversely affect the performance and quality of user experience of the applications utilizing digital compass sensors.\u0000 In this paper, we propose Polaris, a novel approach to provide reliable orientation information for mobile devices in indoor environments. Polaris achieves this by aggregating pictures of the ceiling of an indoor environment and applies computer vision based pattern matching techniques to utilize them as orientation references for correcting digital compass readings. To show the feasibility of the Polaris system, we implemented the Polaris system on mobile devices, and field tested the system in multiple office buildings. Our results show that Polaris achieves 4.5° average orientation accuracy, which is about 3.5 times better than what can be achieved through sole use of raw digital compass readings.","PeriodicalId":88972,"journal":{"name":"Proceedings. IEEE Workshop on Mobile Computing Systems and Applications","volume":"7 1","pages":"14"},"PeriodicalIF":0.0,"publicationDate":"2012-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90733625","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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