On heterogeneity in mobile sensing applications aiming at representative data collection

UbiComp 2013 Adjunct - Adjunct Publication of the 2013 ACM Conference on Ubiquitous Computing

Volumn , Issue , 2013, Pages 1087-1098

  Blunck, Henrik ^a   Kjærgaard, Mikkel Baun ^a   Bouvin, Niels Olof ^a   Lukowicz, Paul ^b   Franke, Tobias ^b   Wüstenberg, Markus ^a   Grœnbæk, Kaj ^a  

^a AARHUS UNIVERSITY   (Denmark)

^b GERMAN RESEARCH CENTER FOR ARTIFICIAL INTELLIGENCE DFKI   (Germany)

Author keywords

Data collection; Heterogeneity; Mobile sensing; Representativeness

Indexed keywords

DATA COLLECTION; HETEROGENEITY; MOBILE SENSING; REPRESENTATIVENESS; RESEARCH COMMUNITIES; RESEARCH QUESTIONS; SCIENTIFIC RESULTS; TRAJECTORY TRACKING;

MOBILE DEVICES; RESEARCH; UBIQUITOUS COMPUTING;

DATA ACQUISITION;

EID: 84885212677     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2494091.2499576     Document Type: Conference Paper

References (24)

1. http://blog.hunch.com/?p=51781, Mar. 2013.
2. http://reviewtimes.shinydevelopment.com/Mar. 2013.
3. http://www.tizen.org/Mar. 2013.
4. T. F. Abdelzaher, Y. Anokwa, P. Boda, J. Burke, D. Estrin, L. J. Guibas, A. Kansal, S. Madden, and J. Reich. Mobiscopes for human spaces. IEEE Pervasive Computing, 6(2):20-29, 2007.
5. H. Blunck, N. O. Bouvin, J. Mose Entwistle, K. Grønbæk, M. B. Kjærgaard, M. Nielsen, M. Graves Petersen, M. K. Rasmussen, and M. Wüstenberg. Computational environmental ethnography: combining collective sensing and ethnographic inquiries to advance means for reducing environmental footprints. In Proc. fourth international conference on Future energy systems (e-Energy 2013), pages 87-98. ACM, 2013.
6. J. P. Cohn. Citizen science: Can volunteers do real research? BioScience, 58(3):192-197, Mar. 2008.
7. S. Consolvo and M. Walker. Using the experience sampling method to evaluate ubicomp applications. Pervasive Computing, IEEE, 2(2):24-31, 2003.
8. H. S. M. Cramer, M. Rost, N. Belloni, F. Bentley, and D. Chincholle. Research in the large. using app stores, markets, and other wide distribution channels in ubicomp research. In UbiComp (Adjunct Papers), pages 511-514, 2010.
9. S. B. Eisenman, E. Miluzzo, N. D. Lane, R. A. Peterson, G.-S. Ahn, and A. T. Campbell. The bikenet mobile sensing system for cyclist experience mapping. In In SenSys, pages 87-101. ACM, 2007.
10. D. Ferreira, A. Dey, and V. Kostakos. Understanding human-smartphone concerns: A study of battery life. Pervasive Computing, pages 19-33, 2011.
11. J. Froehlich, T. Dillahunt, P. Klasnja, J. Mankoff, S. Consolvo, B. Harrison, and J. A. Landay. Ubigreen: investigating a mobile tool for tracking and supporting green transportation habits. In Proc. 27th international conference on Human factors in computing systems, pages 1043-1052. ACM, 2009.
12. R. K. Ganti, N. Pham, H. Ahmadi, S. Nangia, and T. F. Abdelzaher. Greengps: A participatory sensing fuel-efficient maps application. In In MobiSys, pages 151-164, 2010.
13. M. B. Kjærgaard, S. B. Bhattacharya, H. Blunck, and P. Nurmi. Energy-Efficient trajectory tracking for mobile devices. In Proc. 9th International Conference on Mobile Systems, Applications, and Services (MobiSys2011), pages 307-320. ACM Press, 2011.
14. M. B. Kjærgaard and H. Blunck. Unsupervised power profiling for mobile devices. In Proc. 8th International ICST Conferene on Mobile and Ubiquitous Systems (Mobiquitous '11), 2011.
15. M. B. Kjærgaard, J. Langdal, T. Godsk, and T. Toftkjær. Entracked: energy-efficient robust position tracking for mobile devices. In Proc. 7th international conference on Mobile systems, applications, and services, page 221-234, 2009.
16. N. D. Lane, H. Lu, S. B. Eisenman, and A. T. Campbell. Cooperative techniques supporting sensor-based people-centric inferencing. In In Pervasive, pages 75-92, 2008.
17. N. D. Lane, E. Miluzzo, H. Lu, D. Peebles, T. Choudhury, and A. T. Campbell. A survey of mobile phone sensing. IEEE Communications Magazine, 48(9):140-150, 2010.
18. E. Miluzzo, N. D. Lane, K. Fodor, R. A. Peterson, H. Lu, M. Musolesi, S. B. Eisenman, X. Zheng, and A. T. Campbell. Sensing meets mobile social networks: The design, implementation and evaluation of the cenceme application. In The ACM Conference on Embedded Networked Sensor Systems, pages 337-350. ACM, 2008.
19. S. Patel, J. Kientz, G. Hayes, S. Bhat, and G. Abowd. Farther than you may think: An empirical investigation of the proximity of users to their mobile phones. UbiComp 2006: Ubiquitous Computing, pages 123-140, 2006.
20. A. Pathak, A. Jindal, Y. C. Hu, and S. P. Midkiff. What is keeping my phone awake?: characterizing and detecting no-sleep energy bugs in smartphone apps. In Proc. 10th international conference on Mobile systems, applications, and services, page 267-280, 2012.
21. A. Rahmati, A. Qian, and L. Zhong. Understanding human-battery interaction on mobile phones. In Proc. 9th international conference on Human computer interaction with mobile devices and services, pages 265-272. ACM, 2007.
22. W. Willett, P. Aoki, N. Kumar, S. Subramanian, and A. Woodruff. Common sense community: scaffolding mobile sensing and analysis for novice users. In In Pervasive, pages 301-318. Springer-Verlag, 2010.
23. M. Wirz, T. Franke, D. Roggen, E. Mitleton-Kelly, P. Lukowicz, and G. Troster. Inferring crowd conditions from pedestrians' location traces for real-time crowd monitoring during city-scale mass gatherings. In Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE), 2012 IEEE 21st International Workshop on, pages 367-372. IEEE, 2012.
24. Y. Zheng, Y. Chen, Q. Li, X. Xie, and W.-Y. Ma. Understanding transportation modes based on gps data for web applications. ACM Transactions on the Web (TWEB), 4(1):1, 2010.