Smartphone pedometry offers the possibility of ubiquitous health monitoring, context awareness and indoor location tracking through Pedestrian Dead Reckoning (PDR) systems. However, there is currently no detailed understanding of how well pedometry works when applied to smartphones in typical, unconstrained use. This paper evaluates common walk detection (WD) and step counting (SC) algorithms applied to smartphone sensor data. Using a large dataset (27 people, 130 walks, 6 smartphone placements) optimal algorithm parameters are provided and applied to the data. The results favour the use of standard deviation thresholding (WD) and windowed peak detection (SC) with error rates of less than 3%. Of the six different placements, only the back trouser pocket is found to degrade the step counting performance significantly, resulting in undercounting for many algorithms.
{"title":"Walk detection and step counting on unconstrained smartphones","authors":"Agata Brajdic, R. Harle","doi":"10.1145/2493432.2493449","DOIUrl":"https://doi.org/10.1145/2493432.2493449","url":null,"abstract":"Smartphone pedometry offers the possibility of ubiquitous health monitoring, context awareness and indoor location tracking through Pedestrian Dead Reckoning (PDR) systems. However, there is currently no detailed understanding of how well pedometry works when applied to smartphones in typical, unconstrained use. This paper evaluates common walk detection (WD) and step counting (SC) algorithms applied to smartphone sensor data. Using a large dataset (27 people, 130 walks, 6 smartphone placements) optimal algorithm parameters are provided and applied to the data. The results favour the use of standard deviation thresholding (WD) and windowed peak detection (SC) with error rates of less than 3%. Of the six different placements, only the back trouser pocket is found to degrade the step counting performance significantly, resulting in undercounting for many algorithms.","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":"126443630","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}
Semantic place labels are labels like "home", "work", and "school" given to geographic locations where a person spends time. Such labels are important both for giving understandable location information to people and for automatically inferring activities. Deployed products often compute semantic labels with heuristics, which are difficult to program reliably. In this paper, we develop Placer, an algorithm to infer semantic places labels. It uses data from two large, government diary studies to create a principled algorithm for labeling places based on machine learning. Our labeling reduces to a classification problem, where we classify locations into different label categories based on individual demographics, the timing of visits, and nearby businesses. Using these government studies gives us an unprecedented amount of training and test data. For instance, one of our experiments used training data from 87,600 place visits (from 10,372 distinct people) evaluated on 1,135,053 visits (from 124,517 distinct people). We show labeling accuracy for a number of experiments, including one that gives a 14 percentage point increase in accuracy when labeling is a function of nearby businesses in addition to demographic and time features. We also test on GPS data from 28 subjects.
{"title":"Placer: semantic place labels from diary data","authors":"John Krumm, Dany Rouhana","doi":"10.1145/2493432.2493504","DOIUrl":"https://doi.org/10.1145/2493432.2493504","url":null,"abstract":"Semantic place labels are labels like \"home\", \"work\", and \"school\" given to geographic locations where a person spends time. Such labels are important both for giving understandable location information to people and for automatically inferring activities. Deployed products often compute semantic labels with heuristics, which are difficult to program reliably. In this paper, we develop Placer, an algorithm to infer semantic places labels. It uses data from two large, government diary studies to create a principled algorithm for labeling places based on machine learning. Our labeling reduces to a classification problem, where we classify locations into different label categories based on individual demographics, the timing of visits, and nearby businesses. Using these government studies gives us an unprecedented amount of training and test data. For instance, one of our experiments used training data from 87,600 place visits (from 10,372 distinct people) evaluated on 1,135,053 visits (from 124,517 distinct people). We show labeling accuracy for a number of experiments, including one that gives a 14 percentage point increase in accuracy when labeling is a function of nearby businesses in addition to demographic and time features. We also test on GPS data from 28 subjects.","PeriodicalId":262104,"journal":{"name":"Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing","volume":"96 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":"134270292","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-based services I","authors":"C. Mascolo","doi":"10.1145/3254782","DOIUrl":"https://doi.org/10.1145/3254782","url":null,"abstract":"","PeriodicalId":262104,"journal":{"name":"Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing","volume":"25 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":"114211606","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. Feese, B. Arnrich, G. Tröster, M. Burtscher, Bertolt Meyer, K. Jonas
Firefighting is a dangerous task and many research projects have aimed at supporting firefighters during missions by developing new and often costly equipment. In contrast to previous approaches, we use the smartphone to monitor firefighters during real-world missions in order to provide objective data that can be used in post-incident briefings and trainings. In this paper, we present CoenoFire, a smartphone based sensing system aimed at monitoring temporal and behavioral performance indicators of firefighting missions. We validate the performance metrics showing that they can indicate why certain teams performed faster than others in a training scenario conducted by 16 firefighting teams. Furthermore, we deployed CoenoFire over a period of six weeks in a professional fire brigade. In total, 71 firefighters participated in our study and the collected data includes 76 real-world missions totaling to over 148 hours of mission data. Additionally, we visualize real-world mission data and show how mission feedback is supported by the data.
{"title":"CoenoFire: monitoring performance indicators of firefighters in real-world missions using smartphones","authors":"S. Feese, B. Arnrich, G. Tröster, M. Burtscher, Bertolt Meyer, K. Jonas","doi":"10.1145/2493432.2493450","DOIUrl":"https://doi.org/10.1145/2493432.2493450","url":null,"abstract":"Firefighting is a dangerous task and many research projects have aimed at supporting firefighters during missions by developing new and often costly equipment. In contrast to previous approaches, we use the smartphone to monitor firefighters during real-world missions in order to provide objective data that can be used in post-incident briefings and trainings. In this paper, we present CoenoFire, a smartphone based sensing system aimed at monitoring temporal and behavioral performance indicators of firefighting missions. We validate the performance metrics showing that they can indicate why certain teams performed faster than others in a training scenario conducted by 16 firefighting teams. Furthermore, we deployed CoenoFire over a period of six weeks in a professional fire brigade. In total, 71 firefighters participated in our study and the collected data includes 76 real-world missions totaling to over 148 hours of mission data. Additionally, we visualize real-world mission data and show how mission feedback is supported by the data.","PeriodicalId":262104,"journal":{"name":"Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing","volume":"32 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":"114357734","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: Systems","authors":"H. Tokuda","doi":"10.1145/3254787","DOIUrl":"https://doi.org/10.1145/3254787","url":null,"abstract":"","PeriodicalId":262104,"journal":{"name":"Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing","volume":"17 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":"114672440","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}
Ubiquitous computing systems tend to be complex, seamless, data-driven and interactive. Reacting to both context, and users' implicit actions resulting from the lived experience, they cast all traces of human life as potential 'data'. To augment users' endeavours, such systems are necessarily embedded below the line of human attention, drawing upon new and highly sensitive types of data. This begs the question, where is the moment of user consent and how can this moment be truly informed? We would argue that it is time to revisit our design principles in respect of consent and redress the balance of agency towards the user. We draw upon a series of multidisciplinary interviews with experts to (a) reframe consent for ubicomp, and (b) offer three indicative principles, supportive of consent, for designers to 'balance' against system functionality. We hope that this will afford a new prism through which designers might make value judgements.
{"title":"An informed view on consent for UbiComp","authors":"E. Luger, T. Rodden","doi":"10.1145/2493432.2493446","DOIUrl":"https://doi.org/10.1145/2493432.2493446","url":null,"abstract":"Ubiquitous computing systems tend to be complex, seamless, data-driven and interactive. Reacting to both context, and users' implicit actions resulting from the lived experience, they cast all traces of human life as potential 'data'. To augment users' endeavours, such systems are necessarily embedded below the line of human attention, drawing upon new and highly sensitive types of data. This begs the question, where is the moment of user consent and how can this moment be truly informed? We would argue that it is time to revisit our design principles in respect of consent and redress the balance of agency towards the user. We draw upon a series of multidisciplinary interviews with experts to (a) reframe consent for ubicomp, and (b) offer three indicative principles, supportive of consent, for designers to 'balance' against system functionality. We hope that this will afford a new prism through which designers might make value judgements.","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":"134224336","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}
Jorge Gonçalves, Denzil Ferreira, S. Hosio, Yong Liu, Jakob Rogstadius, Hannu Kukka, V. Kostakos
This study is the first attempt to investigate altruistic use of interactive public displays in natural usage settings as a crowdsourcing mechanism. We test a non-paid crowdsourcing service on public displays with eight different motivation settings and analyse users' behavioural patterns and crowdsourcing performance (e.g., accuracy, time spent, tasks completed). The results show that altruistic use, such as for crowdsourcing, is feasible on public displays, and through the controlled use of motivational design and validation check mechanisms, performance can be improved. The results shed insights on three research challenges in the field: i) how does crowdsourcing performance on public displays compare to that of online crowdsourcing, ii) how to improve the quality of feedback collected from public displays which tends to be noisy, and iii) identify users' behavioural patterns towards crowdsourcing on public displays in natural usage settings.
{"title":"Crowdsourcing on the spot: altruistic use of public displays, feasibility, performance, and behaviours","authors":"Jorge Gonçalves, Denzil Ferreira, S. Hosio, Yong Liu, Jakob Rogstadius, Hannu Kukka, V. Kostakos","doi":"10.1145/2493432.2493481","DOIUrl":"https://doi.org/10.1145/2493432.2493481","url":null,"abstract":"This study is the first attempt to investigate altruistic use of interactive public displays in natural usage settings as a crowdsourcing mechanism. We test a non-paid crowdsourcing service on public displays with eight different motivation settings and analyse users' behavioural patterns and crowdsourcing performance (e.g., accuracy, time spent, tasks completed). The results show that altruistic use, such as for crowdsourcing, is feasible on public displays, and through the controlled use of motivational design and validation check mechanisms, performance can be improved. The results shed insights on three research challenges in the field: i) how does crowdsourcing performance on public displays compare to that of online crowdsourcing, ii) how to improve the quality of feedback collected from public displays which tends to be noisy, and iii) identify users' behavioural patterns towards crowdsourcing on public displays in natural usage settings.","PeriodicalId":262104,"journal":{"name":"Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing","volume":"173 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":"134104841","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}
A major challenge of ubiquitous computing resides in the acquisition and modelling of rich and heterogeneous context data, among which, ongoing human activities at different degrees of granularity. In a previous work, we advocated the use of probabilistic description logics (DLs) in a multilevel activity recognition framework. In this paper, we present an in-depth study of activity modeling and reasoning within that framework, as well as an experimental evaluation with a large real-world dataset. Our solution allows us to cope with the uncertain nature of ontological descriptions of activities, while exploiting the expressive power and inference tools of the OWL 2 language. Targeting a large dataset of real human activities, we developed a probabilistic ontology modeling nearly 150 activities and actions of daily living. Experiments with a prototype implementation of our framework confirm the viability of our solution.
{"title":"A probabilistic ontological framework for the recognition of multilevel human activities","authors":"Rim Helaoui, Daniele Riboni, H. Stuckenschmidt","doi":"10.1145/2493432.2493501","DOIUrl":"https://doi.org/10.1145/2493432.2493501","url":null,"abstract":"A major challenge of ubiquitous computing resides in the acquisition and modelling of rich and heterogeneous context data, among which, ongoing human activities at different degrees of granularity. In a previous work, we advocated the use of probabilistic description logics (DLs) in a multilevel activity recognition framework. In this paper, we present an in-depth study of activity modeling and reasoning within that framework, as well as an experimental evaluation with a large real-world dataset. Our solution allows us to cope with the uncertain nature of ontological descriptions of activities, while exploiting the expressive power and inference tools of the OWL 2 language. Targeting a large dataset of real human activities, we developed a probabilistic ontology modeling nearly 150 activities and actions of daily living. Experiments with a prototype implementation of our framework confirm the viability of our solution.","PeriodicalId":262104,"journal":{"name":"Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing","volume":"163 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":"116778032","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}
Advanced information technology has become a key enabler in modern media and entertainment. This comprises the production of animation or live action films, the design of next-generation toys and consumer products, or the creation of richer experiences in theme parks. At Disney Research Zurich, more than 200 researchers and scientists are working at the forefront of innovation in entertainment technology. Our research covers a wide spectrum of different fields, including graphics and animation, human computer interaction, wireless communication, computer vision, materials and design, robotics, and more. In this talk I will demonstrate how innovations in information technology and computational methods developed at Disney Research are serving as platforms for future content creation. I will emphasize the transformative power of 3D printing, digital fabrication, and our increasing ability to make the whole world responsive and interactive.
{"title":"Creating the magic with information technology","authors":"M. Gross","doi":"10.1145/2493432.2501096","DOIUrl":"https://doi.org/10.1145/2493432.2501096","url":null,"abstract":"Advanced information technology has become a key enabler in modern media and entertainment. This comprises the production of animation or live action films, the design of next-generation toys and consumer products, or the creation of richer experiences in theme parks. At Disney Research Zurich, more than 200 researchers and scientists are working at the forefront of innovation in entertainment technology. Our research covers a wide spectrum of different fields, including graphics and animation, human computer interaction, wireless communication, computer vision, materials and design, robotics, and more. In this talk I will demonstrate how innovations in information technology and computational methods developed at Disney Research are serving as platforms for future content creation. I will emphasize the transformative power of 3D printing, digital fabrication, and our increasing ability to make the whole world responsive and interactive.","PeriodicalId":262104,"journal":{"name":"Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing","volume":"122 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":"125032568","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}
This paper develops a holistic framework of questions which seem to motivate sustainability research in computing in order to enable new opportunities for critique. Analysis of systematically selected corpora of computing publications demonstrates that several of these question areas are well covered, while others are ripe for further exploration. It also provides insight into which of these questions tend to be addressed by different communities within sustainable computing. The framework itself reveals discursive similarities between other existing environmental discourses, enabling reflection and participation with the broader sustainability debate. It is argued that the current computing discourse on sustainability is reformist and premised in a Triple Bottom Line construction of sustainability. A radical, Quadruple Bottom Line alternative is explored as a new vista for computing research.
{"title":"Exploring sustainability research in computing: where we are and where we go next","authors":"Bran Knowles, L. Blair, M. Hazas, S. Walker","doi":"10.1145/2493432.2493474","DOIUrl":"https://doi.org/10.1145/2493432.2493474","url":null,"abstract":"This paper develops a holistic framework of questions which seem to motivate sustainability research in computing in order to enable new opportunities for critique. Analysis of systematically selected corpora of computing publications demonstrates that several of these question areas are well covered, while others are ripe for further exploration. It also provides insight into which of these questions tend to be addressed by different communities within sustainable computing. The framework itself reveals discursive similarities between other existing environmental discourses, enabling reflection and participation with the broader sustainability debate. It is argued that the current computing discourse on sustainability is reformist and premised in a Triple Bottom Line construction of sustainability. A radical, Quadruple Bottom Line alternative is explored as a new vista for computing research.","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":"130385598","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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