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Sensing meets mobile social networks: the design, implementation and evaluation of the CenceMe application
Abstract
We present the design, implementation, evaluation, and user ex periences of theCenceMe application, which represents the first system that combines the inference of the presence of individuals using off-the-shelf, sensor-enabled mobile phones with sharing of this information through social networking applications such as Facebook and MySpace. We discuss the system challenges for the development of software on the Nokia N95 mobile phone. We present the design and tradeoffs of split-level classification, whereby personal sensing presence (e.g., walking, in conversation, at the gym) is derived from classifiers which execute in part on the phones and in part on the backend servers to achieve scalable inference. We report performance measurements that characterize the computational requirements of the software and the energy consumption of the CenceMe phone client. We validate the system through a user study where twenty two people, including undergraduates, graduates and faculty, used CenceMe continuously over a three week period in a campus town. From this user study we learn how the system performs in a production environment and what uses people find for a personal sensing system.
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Tapia, E. M., Intille, S. S., Haskell, W., Larson, K., Wright, J., King, A., & Friedman, R. (2007) · 2007 11th IEEE International Symposium on Wearable Computers · doi:10.1109/iswc.2007.4373774 · Cited by 458
Activity Recognition from On-Body Sensors: Accuracy-Power Trade-Off by Dynamic Sensor Selection
Zappi, P., Lombriser, C., Stiefmeier, T., Farella, E., Roggen, D., Benini, L., & Tröster, G. (2008) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-77690-1_2 · Cited by 329
Research works printed but not linked: 30
- 10.1109/MIC.2008.90 · DOI · Paper page
- E. Miluzzo , N. D. Lane , S. B. Eisenman , A. T. Campbell . CenceMe - Injecting Sensing Presence into Social Networking Applications In Proc. of EuroSSC '07 , Lake District, UK , October 23-25, 2007 . E. Miluzzo, N. D. Lane, S. B. Eisenman, A. T. Campbell. CenceMe - Injecting Sensing Presence into Social Networking Applications In Proc. of EuroSSC '07, Lake District, UK, October 23-25, 2007.
- D. Estrin , Seeing Our Signals: Combining location traces and web-based models for personal discovery . In Proc. of HotMobile '08 , Napa Valley, CA, USA , Feb. 25-26, 2008 . D. Estrin, et al. Seeing Our Signals: Combining location traces and web-based models for personal discovery. In Proc. of HotMobile '08, Napa Valley, CA, USA, Feb. 25-26, 2008.
- 10.5555/1786014.1786017 · doi:10.5555/1786014.1786017
- 10.1109/MPRV.2008.39 · DOI · Paper page
- 10.1145/1378600.1378620 · DOI · Paper page
- M. Musolesi , E. Miluzzo , N. D. Lane , S. B. Eisenman , T. Choudhury , A. T. Campbell ,. The Second Life of a Sensor: Integrating Real-world Experience in Virtual Worlds using Mobile Phones , In Proc. of HotEmNets '08 , Charlottesville, Virginia, USA , June 2008 . M. Musolesi, E. Miluzzo, N. D. Lane, S. B. Eisenman, T. Choudhury, A. T. Campbell,. The Second Life of a Sensor: Integrating Real-world Experience in Virtual Worlds using Mobile Phones, In Proc. of HotEmNets '08, Charlottesville, Virginia, USA, June 2008.
- 10.1109/MPRV.2004.1269136 · doi:10.1109/mprv.2004.1269136
- 10.1145/1460412.1460455 · doi:10.1145/1460412.1460455
- 10.1007/978-3-540-30119-6_13 · DOI
- 10.1007/11748625_1 · DOI · Paper page
- 10.1109/MPRV.2007.38 · DOI · Paper page
- 10.1145/1134680.1134693 · DOI
- N. Eagle , A. Pentland . Eigenbehaviors: Identifying Structure in Routine. Behavioral Ecology and Sociobiology (in submission) , 2007 . N. Eagle, A. Pentland. Eigenbehaviors: Identifying Structure in Routine. Behavioral Ecology and Sociobiology (in submission), 2007.
- 10.1007/s00779-005-0046-3 · DOI · Paper page
- J. Burke , Participatory sensing . In ACM Sensys World Sensor Web Workshop , Boulder, CO, USA , Oct 2006 . J. Burke, et al. Participatory sensing. In ACM Sensys World Sensor Web Workshop, Boulder, CO, USA, Oct 2006.
- 10.1007/978-3-540-39653-6_6 · DOI · Paper page
- 10.1145/1460412.1460444 · DOI · Paper page
- 10.1007/978-3-540-79576-6_5 · DOI
- 10.1007/s00779-003-0240-0 · DOI · Paper page
- 10.1145/1236360.1236433 · doi:10.1145/1236360.1236433
- I. H. Witten and E. Frank . Data Mining: Practical machine learning tools and techniques , 2 nd Edition, Morgan Kaufmann , San Francisco , 2005 . I. H. Witten and E. Frank. Data Mining: Practical machine learning tools and techniques, 2nd Edition, Morgan Kaufmann, San Francisco, 2005.
- 10.1145/1234161.1234179 · DOI · Paper page
- J. Paradiso , K.-Y. Hsiao , E. Hu Interactive Music for Instrumented Dancing Shoes In Proc. of ICMC '99 , Bejing, China , Oct. 1999 . J. Paradiso, K.-Y. Hsiao, E. Hu Interactive Music for Instrumented Dancing Shoes In Proc. of ICMC '99, Bejing, China, Oct. 1999.
- 10.1145/1247715.1247718 · DOI · Paper page
- R. O. Duda , P. E. Hart , D. G. Sork , Pattern Classification , Second Edition, Wiley Interscience . R. O. Duda, P. E. Hart, D. G. Sork, Pattern Classification, Second Edition, Wiley Interscience.
- 10.1007/978-3-540-24646-6_1 · DOI · Paper page
- 10.1007/11426646_24 · DOI
- J. Lester , Sensing and Modeling Activities to Support Physical Fitness . In Proc. of Ubicomp Workshop: Monitoring, Measuring, and Motivating Exercise: Ubiquitous Computing to Support Fitness) , Tokyo, Japan , Sep 2005 . J. Lester, et al. Sensing and Modeling Activities to Support Physical Fitness. In Proc. of Ubicomp Workshop: Monitoring, Measuring, and Motivating Exercise: Ubiquitous Computing to Support Fitness), Tokyo, Japan, Sep 2005.
- 10.5555/946249.946911 · doi:10.5555/946249.946911
Cited by
Activity recognition using cell phone accelerometers
Kwapisz, J. R., Weiss, G. M., & Moore, S. A. (2011) · ACM SIGKDD Explorations Newsletter · doi:10.1145/1964897.1964918 · Cited by 2,912
A survey of mobile phone sensing
Lane, N., Miluzzo, E., Lu, H., Peebles, D., Choudhury, T., & Campbell, A. (2010) · IEEE Communications Magazine · doi:10.1109/mcom.2010.5560598 · Cited by 2,292
Self-citationWang, R., Chen, F., Chen, Z., Li, T., Harari, G., Tignor, S., Zhou, X., Ben-Zeev, D., & Campbell, A. T. (2014) · Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing · doi:10.1145/2632048.2632054 · Cited by 1,116
Self-citationMohr, D. C., Burns, M. N., Schueller, S. M., Clarke, G., & Klinkman, M. (2013) · General Hospital Psychiatry · doi:10.1016/j.genhosppsych.2013.03.008 · Cited by 693
“One approach develops algorithms that predict patient states by using predefined algorithms derived a priori from scientific or clinical knowledge [47] [48].”
Harnessing context sensing to develop a mobile intervention for depression
Burns, M. N., Begale, M., Duffecy, J., Gergle, D., Karr, C. J., Giangrande, E., & Mohr, D. C. (2011) · Journal of Medical Internet Research · doi:10.2196/jmir.1838 · Cited by 646
Metadata
- Authors
- Miluzzo, E., Lane, N. D., Fodor, K., Peterson, R., Lu, H., Musolesi, M., Eisenman, S. B., Zheng, X., & Campbell, A. T.
- Venue
- Proceedings of the 6th ACM conference on Embedded network sensor systems
- Publisher
- ACM
- Published
- 2008-11-05
- Pages
- 337-350
- OpenAlex
- W2162555816
- Cited by
- 1,032
- References
- 2
- FWCI
- 61.97
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Miluzzo, E., Lane, N. D., Fodor, K., Peterson, R., Lu, H., Musolesi, M., Eisenman, S. B., Zheng, X., & Campbell, A. T. (2008). Sensing meets mobile social networks: the design, implementation and evaluation of the CenceMe application. Proceedings of the 6th ACM conference on Embedded network sensor systems. https://doi.org/10.1145/1460412.1460445
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