Many occupant-oriented smarthome applications such as automated lighting, heating and cooling, and activity recognition need room location information of residents within a building. Surveillance based tracking systems used to track people in commercial buildings, are privacy invasive in homes. In this paper, we present the RF Doormat - a RF threshold system that can accurately track people's room locations by monitoring their movement through the doorways in the home. We also present a set of guidelines and a visualization to easily and rapidly setup the RF-Doormat system on any doorway. To evaluate our system, we perform 580 doorway crossings across 11 different doorways in a home. Results indicate that our system can detect doorway crossings made by people with an average accuracy of 98%. To our knowledge, the RF Doormat is the first highly accurate room location tracking system that can be used for long time periods without the need for privacy invasive cameras.
{"title":"An RF doormat for tracking people's room locations","authors":"Juhi Ranjan, Yu Yao, K. Whitehouse","doi":"10.1145/2493432.2493514","DOIUrl":"https://doi.org/10.1145/2493432.2493514","url":null,"abstract":"Many occupant-oriented smarthome applications such as automated lighting, heating and cooling, and activity recognition need room location information of residents within a building. Surveillance based tracking systems used to track people in commercial buildings, are privacy invasive in homes. In this paper, we present the RF Doormat - a RF threshold system that can accurately track people's room locations by monitoring their movement through the doorways in the home. We also present a set of guidelines and a visualization to easily and rapidly setup the RF-Doormat system on any doorway. To evaluate our system, we perform 580 doorway crossings across 11 different doorways in a home. Results indicate that our system can detect doorway crossings made by people with an average accuracy of 98%. To our knowledge, the RF Doormat is the first highly accurate room location tracking system that can be used for long time periods without the need for privacy invasive cameras.","PeriodicalId":262104,"journal":{"name":"Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125834401","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: Location privacy","authors":"Frank Dürr","doi":"10.1145/3254797","DOIUrl":"https://doi.org/10.1145/3254797","url":null,"abstract":"","PeriodicalId":262104,"journal":{"name":"Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134332620","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}
Heading information becomes widely used in ubiquitous computing applications for mobile devices. Digital magnetometers, also known as geomagnetic field sensors, provide absolute device headings relative to the earth's magnetic north. However, magnetometer readings are prone to significant errors in indoor environments due to the existence of magnetic interferences, such as from printers, walls, or metallic shelves. These errors adversely affect the performance and quality of user experience of the applications requiring device headings. In this paper, we propose Headio, a novel approach to provide reliable device headings in indoor environments. Headio achieves this by aggregating ceiling images of an indoor environment, and by using computer vision-based pattern detection techniques to provide directional references. To achieve zero-configured and energy-efficient heading sensing, Headio also utilizes multimodal sensing techniques to dynamically schedule sensing tasks. To fully evaluate the system, we implemented Headio on both Android and iOS mobile platforms, and performed comprehensive experiments in both small-scale controlled and large-scale public indoor environments. Evaluation results show that Headio constantly provides accurate heading detection performance in diverse situations, achieving better than 1 degree average heading accuracy, up to 33X improvement over existing techniques.
{"title":"Headio: zero-configured heading acquisition for indoor mobile devices through multimodal context sensing","authors":"Zheng Sun, Shijia Pan, Yu-Chi Su, Pei Zhang","doi":"10.1145/2493432.2493434","DOIUrl":"https://doi.org/10.1145/2493432.2493434","url":null,"abstract":"Heading information becomes widely used in ubiquitous computing applications for mobile devices. Digital magnetometers, also known as geomagnetic field sensors, provide absolute device headings relative to the earth's magnetic north. However, magnetometer readings are prone to significant errors in indoor environments due to the existence of magnetic interferences, such as from printers, walls, or metallic shelves. These errors adversely affect the performance and quality of user experience of the applications requiring device headings. In this paper, we propose Headio, a novel approach to provide reliable device headings in indoor environments. Headio achieves this by aggregating ceiling images of an indoor environment, and by using computer vision-based pattern detection techniques to provide directional references. To achieve zero-configured and energy-efficient heading sensing, Headio also utilizes multimodal sensing techniques to dynamically schedule sensing tasks. To fully evaluate the system, we implemented Headio on both Android and iOS mobile platforms, and performed comprehensive experiments in both small-scale controlled and large-scale public indoor environments. Evaluation results show that Headio constantly provides accurate heading detection performance in diverse situations, achieving better than 1 degree average heading accuracy, up to 33X improvement over existing techniques.","PeriodicalId":262104,"journal":{"name":"Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132420586","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}
Xuan Bao, Songchun Fan, A. Varshavsky, Kevin A. Li, Romit Roy Choudhury
This paper describes a system for automatically rating content - mainly movies and videos - at multiple granularities. Our key observation is that the rich set of sensors available on today's smartphones and tablets could be used to capture a wide spectrum of user reactions while users are watching movies on these devices. Examples range from acoustic signatures of laughter to detect which scenes were funny, to the stillness of the tablet indicating intense drama. Moreover, unlike in most conventional systems, these ratings need not result in just one numeric score, but could be expanded to capture the user's experience. We combine these ideas into an Android based prototype called Pulse, and test it with 11 users each of whom watched 4 to 6 movies on Samsung tablets. Encouraging results show consistent correlation between the user's actual ratings and those generated by the system. With more rigorous testing and optimization, Pulse could be a candidate for real-world adoption.
{"title":"Your reactions suggest you liked the movie: automatic content rating via reaction sensing","authors":"Xuan Bao, Songchun Fan, A. Varshavsky, Kevin A. Li, Romit Roy Choudhury","doi":"10.1145/2493432.2493440","DOIUrl":"https://doi.org/10.1145/2493432.2493440","url":null,"abstract":"This paper describes a system for automatically rating content - mainly movies and videos - at multiple granularities. Our key observation is that the rich set of sensors available on today's smartphones and tablets could be used to capture a wide spectrum of user reactions while users are watching movies on these devices. Examples range from acoustic signatures of laughter to detect which scenes were funny, to the stillness of the tablet indicating intense drama. Moreover, unlike in most conventional systems, these ratings need not result in just one numeric score, but could be expanded to capture the user's experience. We combine these ideas into an Android based prototype called Pulse, and test it with 11 users each of whom watched 4 to 6 movies on Samsung tablets. Encouraging results show consistent correlation between the user's actual ratings and those generated by the system. With more rigorous testing and optimization, Pulse could be a candidate for real-world adoption.","PeriodicalId":262104,"journal":{"name":"Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115633452","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}
Gonzalo Garcia-Perate, N. Dalton, R. Dalton, Duncan Wilson
In this paper we present the design and first-stage analysis of a purposely built, smart, pop-up wine shop. Our shop learns from visitors' choices and recommends wine using collaborative filtering and ambient feedback displays integrated into its furniture. Our ambient recommender system was tested in a controlled laboratory environment. We report on the qualitative feedback and between subjects study, testing the influence the system had in wine choice behavior. Participants reported the system helpful, and results from our empirical analysis suggest it influenced buying behavior.
{"title":"Ambient recommendations in the pop-up shop","authors":"Gonzalo Garcia-Perate, N. Dalton, R. Dalton, Duncan Wilson","doi":"10.1145/2493432.2494525","DOIUrl":"https://doi.org/10.1145/2493432.2494525","url":null,"abstract":"In this paper we present the design and first-stage analysis of a purposely built, smart, pop-up wine shop. Our shop learns from visitors' choices and recommends wine using collaborative filtering and ambient feedback displays integrated into its furniture. Our ambient recommender system was tested in a controlled laboratory environment. We report on the qualitative feedback and between subjects study, testing the influence the system had in wine choice behavior. Participants reported the system helpful, and results from our empirical analysis suggest it influenced buying behavior.","PeriodicalId":262104,"journal":{"name":"Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116032880","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}
W. Ouyang, Animesh Srivastava, P. Prabahar, Romit Roy Choudhury, Merideth A. Addicott, F. J. McClernon
This paper presents iSee, a crowdsourced approach to detecting and localizing events in outdoor environments. Upon spotting an event, an iSee user only needs to swipe on her smartphone's touchscreen in the direction of the event. These swiping directions are often inaccurate and so are the compass measurements. Moreover, the swipes do not encode any notion of how far the event is located from the user, neither is the GPS location of the user accurate. Furthermore, multiple events may occur simultaneously and users do not explicitly indicate which events they are swiping towards. Nonetheless, as more users start contributing data, we show that our proposed system is able to quickly detect and estimate the locations of the events. We have implemented iSee on Android phones and have experimented in real-world settings by planting virtual "events" in our campus and asking volunteers to swipe on seeing one. Results show that iSee performs appreciably better than established triangulation and clustering-based approaches, in terms of localization accuracy, detection coverage, and robustness to sensor noise.
{"title":"If you see something, swipe towards it: crowdsourced event localization using smartphones","authors":"W. Ouyang, Animesh Srivastava, P. Prabahar, Romit Roy Choudhury, Merideth A. Addicott, F. J. McClernon","doi":"10.1145/2493432.2493455","DOIUrl":"https://doi.org/10.1145/2493432.2493455","url":null,"abstract":"This paper presents iSee, a crowdsourced approach to detecting and localizing events in outdoor environments. Upon spotting an event, an iSee user only needs to swipe on her smartphone's touchscreen in the direction of the event. These swiping directions are often inaccurate and so are the compass measurements. Moreover, the swipes do not encode any notion of how far the event is located from the user, neither is the GPS location of the user accurate. Furthermore, multiple events may occur simultaneously and users do not explicitly indicate which events they are swiping towards. Nonetheless, as more users start contributing data, we show that our proposed system is able to quickly detect and estimate the locations of the events. We have implemented iSee on Android phones and have experimented in real-world settings by planting virtual \"events\" in our campus and asking volunteers to swipe on seeing one. Results show that iSee performs appreciably better than established triangulation and clustering-based approaches, in terms of localization accuracy, detection coverage, and robustness to sensor noise.","PeriodicalId":262104,"journal":{"name":"Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122477935","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: At work","authors":"A. Dey","doi":"10.1145/3254779","DOIUrl":"https://doi.org/10.1145/3254779","url":null,"abstract":"","PeriodicalId":262104,"journal":{"name":"Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124792809","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}
We investigate how technology usage in homes has changed with the increasing prevalence of mobile devices including Tablets and Smart Phones. We logged Internet usage from 86 Belgium households to determine their six most common Internet Activities. Next, we surveyed households about what devices they own, how they share those devices, and which device they use for different Internet activities. We then conducted semi-structured interviews with 18 of 55 households that responded to the survey in which participants explained their device usage patterns and where they use technology in their home. Our findings suggest that the nature of online activity and social context influence device preference. Many participants reported that their Desktop PC is now a special purpose device, which they use only for specific activities such as working from home or online gaming. Compared to past studies, we observed technology use in many more locations in the home, most notably kitchens and bathrooms.
{"title":"Home computing unplugged: why, where and when people use different connected devices at home","authors":"F. Kawsar, A. Brush","doi":"10.1145/2493432.2493494","DOIUrl":"https://doi.org/10.1145/2493432.2493494","url":null,"abstract":"We investigate how technology usage in homes has changed with the increasing prevalence of mobile devices including Tablets and Smart Phones. We logged Internet usage from 86 Belgium households to determine their six most common Internet Activities. Next, we surveyed households about what devices they own, how they share those devices, and which device they use for different Internet activities. We then conducted semi-structured interviews with 18 of 55 households that responded to the survey in which participants explained their device usage patterns and where they use technology in their home. Our findings suggest that the nature of online activity and social context influence device preference. Many participants reported that their Desktop PC is now a special purpose device, which they use only for specific activities such as working from home or online gaming. Compared to past studies, we observed technology use in many more locations in the home, most notably kitchens and bathrooms.","PeriodicalId":262104,"journal":{"name":"Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124796442","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: Sport and fitness","authors":"J. Kay","doi":"10.1145/3254786","DOIUrl":"https://doi.org/10.1145/3254786","url":null,"abstract":"","PeriodicalId":262104,"journal":{"name":"Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125197174","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. Frost, Afsaneh Doryab, M. Faurholt-Jepsen, L. Kessing, J. Bardram
There is a growing interest in personal health technologies that sample behavioral data from a patient and visualize this data back to the patient for increased health awareness. However, a core challenge for patients is often to understand the connection between specific behaviors and health, i.e. to go beyond health awareness to disease insight. This paper presents MONARCA 2.0, which records subjective and objective data from patients suffering from bipolar disorder, processes this, and informs both the patient and clinicians on the importance of the different data items according to the patient's mood. The goal is to provide patients with a increased insight into the parameters influencing the nature of their disease. The paper describes the user-centered design and the technical implementation of the system, as well as findings from an initial field deployment.
{"title":"Supporting disease insight through data analysis: refinements of the monarca self-assessment system","authors":"M. Frost, Afsaneh Doryab, M. Faurholt-Jepsen, L. Kessing, J. Bardram","doi":"10.1145/2493432.2493507","DOIUrl":"https://doi.org/10.1145/2493432.2493507","url":null,"abstract":"There is a growing interest in personal health technologies that sample behavioral data from a patient and visualize this data back to the patient for increased health awareness. However, a core challenge for patients is often to understand the connection between specific behaviors and health, i.e. to go beyond health awareness to disease insight. This paper presents MONARCA 2.0, which records subjective and objective data from patients suffering from bipolar disorder, processes this, and informs both the patient and clinicians on the importance of the different data items according to the patient's mood. The goal is to provide patients with a increased insight into the parameters influencing the nature of their disease. The paper describes the user-centered design and the technical implementation of the system, as well as findings from an initial field deployment.","PeriodicalId":262104,"journal":{"name":"Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125412345","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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