Prototyping and sampling experience to evaluate ubiquitous computing privacy in the real world
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Physical, Social, and Experiential Knowledge in Pervasive Computing Environments
IEEE Pervasive Computing
From privacy methods to a privacy toolbox: Evaluation shows that heuristics are complementary
ACM Transactions on Computer-Human Interaction (TOCHI)
Flowers or a robot army?: encouraging awareness & activity with personal, mobile displays
UbiComp '08 Proceedings of the 10th international conference on Ubiquitous computing
An empirical investigation of concerns of everyday tracking and recording technologies
UbiComp '08 Proceedings of the 10th international conference on Ubiquitous computing
Privacy risks emerging from the adoption of innocuous wearable sensors in the mobile environment
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Pervasive'11 Proceedings of the 9th international conference on Pervasive computing
A survey on privacy in mobile participatory sensing applications
Journal of Systems and Software
mConverse: inferring conversation episodes from respiratory measurements collected in the field
Proceedings of the 2nd Conference on Wireless Health
Journal of Biomedical Informatics
Using height sensors for biometric identification in multi-resident homes
Pervasive'10 Proceedings of the 8th international conference on Pervasive Computing
CoMon: cooperative ambience monitoring platform with continuity and benefit awareness
Proceedings of the 10th international conference on Mobile systems, applications, and services
Long-term effects of ubiquitous surveillance in the home
Proceedings of the 2012 ACM Conference on Ubiquitous Computing
Investigating receptiveness to sensing and inference in the home using sensor proxies
Proceedings of the 2012 ACM Conference on Ubiquitous Computing
Privacy in mobile technology for personal healthcare
ACM Computing Surveys (CSUR)
Understanding sharing preferences and behavior for mHealth devices
Proceedings of the 2012 ACM workshop on Privacy in the electronic society
Exploring user preferences for privacy interfaces in mobile sensing applications
Proceedings of the 11th International Conference on Mobile and Ubiquitous Multimedia
SocioPhone: everyday face-to-face interaction monitoring platform using multi-phone sensor fusion
Proceeding of the 11th annual international conference on Mobile systems, applications, and services
Viewing and controlling personal sensor data: what do users want?
PERSUASIVE'13 Proceedings of the 8th international conference on Persuasive Technology
Fine-grained sharing of sensed physical activity: a value sensitive approach
Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing
The break-time barometer: an exploratory system forworkplace break-time social awareness
Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing
Understanding the coverage and scalability of place-centric crowdsensing
Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing
Real-time air quality monitoring through mobile sensing in metropolitan areas
Proceedings of the 2nd ACM SIGKDD International Workshop on Urban Computing
Proceedings of International Conference on Advances in Mobile Computing & Multimedia
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More and more personal devices such as mobile phones and multimedia players use embedded sensing. This means that people are wearing and carrying devices capable of sensing details about them such as their activity, location, and environment. In this paper, we explore privacy concerns about such personal sensing through interviews with 24 participants who took part in a three month study that used personal sensing to detect their physical activities. Our results show that concerns often depended on what was being recorded, the context in which participants worked and lived and thus would be sensed, and the value they perceived would be provided. We suggest ways in which personal sensing can be made more privacy-sensitive to address these concerns.