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CenceMe – Injecting Sensing Presence into Social Networking Applications

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Smart Sensing and Context (EuroSSC 2007)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 4793))

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Abstract

We present the design, prototype implementation, and evaluation of CenceMe, a personal sensing system that enables members of social networks to share their sensing presence with their buddies in a secure manner. Sensing presence captures a user’s status in terms of his activity (e.g., sitting, walking, meeting friends), disposition (e.g., happy, sad, doing OK), habits (e.g., at the gym, coffee shop today, at work) and surroundings (e.g., noisy, hot, bright, high ozone). CenceMe injects sensing presence into popular social networking applications such as Facebook, MySpace, and IM (Skype, Pidgin) allowing for new levels of “connection” and implicit communication (albeit non-verbal) between friends in social networks. The CenceMe system is implemented, in part, as a thin-client on a number of standard and sensor-enabled cell phones and offers a number of services, which can be activated on a per-buddy basis to expose different degrees of a user’s sensing presence; these services include, life patterns, my presence, friend feeds, social interaction, significant places, buddy search, buddy beacon, and “above average?”

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References

  1. Lester, J., et al.: Sensing and Modeling Activities to Support Physical Fitness. In: Proc. of Ubicomp Workshop: Monitoring, Measuring, and Motivating Excerise: Ubiquitous Computing to Support Fitness, Tokoyo (September 2005)

    Google Scholar 

  2. Kids say e-mail is, like, soooo dead. CNET (July 19, 2007), http://news.com.com/Kids+say+e-mail+is,+like,+soooo+dead/2009-1032_3-6197242.html

  3. Lester, J., et al.: A Hybrid Discriminative/generative Approach for Modeling Human Activities. In: Proc. of the 19th IntłJoint Conf. on Artificial Intelligence, Edinburgh, pp. 766–722 (2005)

    Google Scholar 

  4. MetroSense Project Web Page, http://metrosense.cs.dartmouth.edu

  5. Nike + , http://www.nikeplus.com

  6. Chaudhri, R., et al.: Mobile Device-Centric Exercise Monitoring with an External Sensor Population (Poster abstract). In: Proc of 3rd IEEE Int’l. Conf. on Distributed Computing in Sensor Systems, Santa Fe (June 2007)

    Google Scholar 

  7. Nokia, http://www.nokia.com

  8. Nakanishi, Y., Takahashi, K., Tsuji, T., Hakozaki, K.: iCAMS: A Mobile Communication Tool Using Location and Schedule Information. IEEE Pervasive Computing 3(1), 82–88 (2004)

    Article  Google Scholar 

  9. Skype, http://www.skype.com

  10. Moteiv Tmote Mini, http://www.moteiv.com/

  11. Johnson, P., Kapadia, A., Kotz, D., Triandopoulos, N.: People-Centric Urban Sensing: Security Challenges for the New Paradigm. Dartmouth Technical Report TR2007-586 (February 2007)

    Google Scholar 

  12. Gaim/Pidgin, http://sourceforge.net/projects/pidgin

  13. Marmasse, N., Schmandt, C., Spectre, D.: WatchMe: Communication and Awareness Between Members of a Closely-knit Group. In: Proc. of 6th Int’l. Conf. on Ubiq. Comp., Nottingham, pp. 214–231 (September 2004)

    Google Scholar 

  14. Lester, J., Choudhury, T., Borriello, G.: A Practical Approach to Recognizing Physical Activities. In: Proc. of 4th Int’l. Conf. on Perv. Comp., Dublin, pp. 1–16 (May 2006)

    Google Scholar 

  15. Abdelzaher, T., et al.: Mobiscopes for Human Spaces. IEEE Perv. Comp. 6(2), 20–29 (2007)

    Article  Google Scholar 

  16. Ganti, R., Jayachandran, P., Abdelzaher, T., Stankovic, J.: SATIRE: A Software Architecture for Smart AtTIRE. In: Proc. of 4th. Int’l. Conf. on Mobile Systems, Applications, and Services, Uppsala (June 2006)

    Google Scholar 

  17. Bentley, F., Metcalf, C.: Sharing Motion Information with Close Family and Friends. In: Proc of SIGCHI Conf. on Human Factors in Computing Systems, San Jose, pp. 1361–1370 (2007)

    Google Scholar 

  18. Eagle, N., Pentland, A., Lazer, D.: Inferring Social Network Structure using Mobile Phone Data (in submission, 2007)

    Google Scholar 

  19. Matlab Library for Speaker Identification using Cepstrul Coeff. http://www.mathworks.com/matlabcentral/fileexchange/loadFile.do?objectId=8802

  20. Food, Nutrition, Saftey and Cooking Site at the University of Nebraska - Lincoln, http://lancaster.unl.edu/food/

  21. Borriello, G., Brunette, W., Lester, J., Powledge, P., Rea, A.: An Ecosystem of Platforms to Support Sensors for Personal Fitness. In: Proc of 4th Int’l. Workshop on Wearable and Implantable Body Sensor Networks, Aachen (March 2006)

    Google Scholar 

  22. Cox, L., Dalton, A., Marupadi, V.: Presence-Exchanges: Toward Sustainable Presence-sharing. In: Proc. of 7th IEEE Workshop on Mobile Computing Systems and Applications, Durham, pp. 55–60 (April 2006)

    Google Scholar 

  23. Cox, L., Dalton, A., Marupadi, V.: SmokeScreen: Flexible Privacy Controls for Presence-sharing. In: Proc. of 5th Int’l. Conf. on Mobile Systems, Applications and Services, San Juan, pp. 233–245 (June 2007)

    Google Scholar 

  24. USDA UV-B Monitoring and Research Program, http://nadp.nrel.colostate.edu

  25. Eagle, N., Pentland, A.: Eigenbehaviors: Identifying Structure in Routine (2006)

    Google Scholar 

  26. Eagle, N., Pentland, A.: Reality Mining: Sensing Complex Social Systems. In: Personal Ubiq. Comp., pp. 255–268 (May 2006)

    Google Scholar 

  27. Lamming, M., Bohm, D.: SPECs: Another Approach to Human Context and Activity Sensing Research, Using Tiny Peer-to-Peer Wireless Computers. In: Proc. of 5th Int’l. Conf. on Ubiq. Comp. Seattle (October 2003)

    Google Scholar 

  28. Twitter, http://twitter.com

  29. Burke, J., et al.: Participatory sensing. In: ACM Sensys World Sensor Web Workshop, Boulder (October 2006)

    Google Scholar 

  30. Pering, T., et al.: The PSI Board: Realizing a Phone-Centric Body Sensor Network. In: Proc of 4th Int’l. Workshop on Wearable and Implantable Body Sensor Networks, Aachen (March 2006)

    Google Scholar 

  31. Sensorplanet, http://www.sensorplanet.org/

  32. Eisenman, S., et al.: Metrosense project: People-centric Sensing at Scale. In: Proc. of World Sensor Web Workshop, Boulder (October 2006)

    Google Scholar 

  33. Reddy, S., et al.: Image Browsing, Processing, and Clustering for Participatory Sensing: Lessons From a DietSense Prototype. In: Proc. of 4th Workshop on Embedded Networked Sensors, Cork (June 2007)

    Google Scholar 

  34. UbiFit Project, http://dub.washington.edu/projects/ubifit

  35. Kansal, A., Goraczko, M., Zhao, F.: Building a Sensor Network of Mobile Phones. In: Proc of IEEE 6th Int’l. IPSN Conf., Cambridge (April 2007)

    Google Scholar 

  36. Facebook, http://www.facebook.com

  37. MySpace, http://www.myspace.com

  38. Apple iPhone, http://www.apple.com/iphone/

  39. Witten, I.H., Frank, E.: Data Mining: Practical machine learning tools and techniques, 2nd edn. Morgan Kaufmann, San Francisco (2005)

    MATH  Google Scholar 

  40. Garmin Edge, http://www.garmin.com/products/edge305

  41. Campbell, A.T., et al.: People-Centric Urban Sensing (Invited Paper). In: Proc. of 2nd ACM/IEEE Annual Int’l. Wireless Internet Conf., Boston (August 2006)

    Google Scholar 

  42. Symbian, http://www.symbian.com

  43. Eisenman, S.B., et al.: The BikeNet Mobile Sensing System for Cyclist Experience Mapping. In: Proc. of 5th ACM Conf. on Embedded Networked Sensor Systems, Sydney, November 6-9, 2007, pp. 6–9. ACM Press, New York (2007)

    Google Scholar 

  44. CitySense, http://www.citysense.net/

  45. Place Lab., http://www.placelab.org/

  46. Gemmell, J., Bell, G., Lueder, R.: MyLifeBits: a Personal Database for Everything. Communications of the ACM 49(1), 88–95 (2006)

    Article  Google Scholar 

  47. Zhou, C., et al.: Discovering Personally Meaningful Places: An Interactive Clustering Approach. In: ACM Trans. on Information Systems vol. 25(3) (2007)

    Google Scholar 

  48. Skyhook Wireless, http://www.skyhookwireless.com/

  49. Liao, L., Fox, D., Kautz, H.: Extracting Places and Activities from GPS Traces using Hierarchical Conditional Random Field. Int’l. Journal of Robotics Research 26(1) (2007)

    Google Scholar 

  50. Krumm, J., Horvitz, E.: LOCADIO: Inferring Motion and Location from Wi-Fi Signal Strengths. In: Proc. of 1st Int’l. Conf. on Mobile and Ubiq. Systems: Networking and Services (August 2004)

    Google Scholar 

  51. Eisenman, S.B., Campbell, A.T.: SkiScape Sensing (poster abstract). In: Proc. of 4th ACM Conf. on Embedded Networked Sensor Systems, Boulder (November 2006)

    Google Scholar 

  52. Motorola L2, http://www.motorola.com/

  53. Lane, N.D., Lu, H., Campbell, A.T.: Ambient Beacon Localization: Using Sensed Characteristics of the Physical World to Localize Mobile Sensors. In: Proc. of 4th Workshop on Embedded Networked Sensors, Cork (June 2007)

    Google Scholar 

  54. Sohn, T., et al.: Mobility Detection Using Everyday GSM Traces. In: Proc. of the 6th Int’l. Conf. on Ubiq. Comp. Orange County, pp. 212–224 (September 2006)

    Google Scholar 

  55. Anderson, I., Muller, H.: Practical Activity Recognition using GSM Dat. In: Technical Report CSTR-06-016, Dept. of Comp. Sci., Univ. of Bristol (July 2006)

    Google Scholar 

  56. iGoogle, http://www.google.com/ig

  57. Kapadia, A., Henderson, T., Fielding, J.J., Kotz, D.: Virtual Walls: Protecting Digital Privacy in Pervasive Environments. In: Proc. of 5th Int’l. Conf. on Perv. Comp. Toronto, pp. 162–179 (May 2007)

    Google Scholar 

  58. Masoodian, M., Lane, N.: MATI: A System for Accessing Travel Itineary Information using Mobile Phones. In: Proc. of 16th British HCI Group Annual Conf., London (September 2002)

    Google Scholar 

  59. Google Gadgets, http://code.google.com/apis/gadgets

  60. Choudhury, T., Basu, S.: Modeling Conversational Dynamics as a Mixed Memory Markov Process. In: Advances in Neural Information Processing Systems 17, pp. 218–288. MIT Press, Cambridge (2005)

    Google Scholar 

  61. Hightower, J., et al.: Learning and Recognizing the Places We Go. In: Proc. of the 7th Int’l. Conf. on Ubiq. Comp. Toyko, pp. 159–176 (September 2005)

    Google Scholar 

  62. Welbourne, E., Lester, J., LaMarca, A., Borriello, G.: Mobile Context Inference Using Low-Cost Sensors. In: Strang, T., Linnhoff-Popien, C. (eds.) LoCA 2005. LNCS, vol. 3479, Springer, Heidelberg (2005)

    Google Scholar 

  63. Kang, J., Welbourne, W., Stewart, B., Borriello, G.: Extracting Places from Traces of Locations. In: Proc. of ACM Int’l. Workshop on Wireless Mobile Applications and Services on WLAN Hotspots, Philadelphia (October 2004)

    Google Scholar 

  64. DeVaul, R., Sung, M., Gips, J., Pentland, A.: MIThril 2003: Applications and Architecture. In: Proc. of 7th Int’l. Symp. on Wearable Computers, White Plains (October 2003)

    Google Scholar 

  65. Ashbrook, D., Starner, T.: Using GPS to Learn Significant Locations and Predict Movement across Multiple Users. In: Personal Ubiq. Comp., pp. 275–286 (2003)

    Google Scholar 

  66. Liao, L., Fox, D., Kautz, H.: Location-Based Activity Recognition using Relational Markov Networks. In: Proc of IJCAI-05, Edinburgh (August 2005)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Dartmouth College, Hanover NH 03755, USA

    Emiliano Miluzzo, Nicholas D. Lane & Andrew T. Campbell

  2. Columbia University, New York NY 10027, USA

    Shane B. Eisenman

Authors
  1. Emiliano Miluzzo
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  2. Nicholas D. Lane
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  3. Shane B. Eisenman
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  4. Andrew T. Campbell
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Gerd Kortuem Joe Finney Rodger Lea Vasughi Sundramoorthy

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© 2007 Springer-Verlag Berlin Heidelberg

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Miluzzo, E., Lane, N.D., Eisenman, S.B., Campbell, A.T. (2007). CenceMe – Injecting Sensing Presence into Social Networking Applications. In: Kortuem, G., Finney, J., Lea, R., Sundramoorthy, V. (eds) Smart Sensing and Context. EuroSSC 2007. Lecture Notes in Computer Science, vol 4793. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75696-5_1

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  • DOI: https://doi.org/10.1007/978-3-540-75696-5_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-75695-8

  • Online ISBN: 978-3-540-75696-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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