Understanding Human-Smartphone Concerns: A Study of Battery Life

  • Denzil Ferreira
  • Anind K. Dey
  • Vassilis Kostakos
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6696)


This paper presents a large, 4-week study of more than 4000 people to assess their smartphone charging habits to identify timeslots suitable for opportunistic data uploading and power intensive operations on such devices, as well as opportunities to provide interventions to support better charging behavior. The paper provides an overview of our study and how it was conducted using an online appstore as a software deployment mechanism, and what battery information was collected. We then describe how people charge their smartphones, the implications on battery life and energy usage, and discuss how to improve users’ experience with battery life.


Large-scale study battery life autonomous logging smartphones android 


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  1. 1.
    Android Developer Dashboard (September 1, 2010),
  2. 2.
    Android OS (2011), (last accessed February 24, 2011)
  3. 3.
    Buennemeyer, T.K., Nelson, T.M., Clagett, L.M., Dunning, J.P., Marchany, R.C., Tront, J.G.: Mobile Device Profiling and Intrusion Detection using Smart Batteries. In: Proceedings in the 41th Hawaii International Conference on System Sciences (2008)Google Scholar
  4. 4.
    Byrne, J.A.: The Proper Charging Of Stationary Lead-Acid Batteries (Your Battery Is Only As Good As How You Charge It.). In: Battcon 2010 (2010)Google Scholar
  5. 5.
    Corey, G.P.: Nine Ways To Murder Your Battery (These Are Only Some Of The Ways). In: Battcon 2010 (2010)Google Scholar
  6. 6.
    Cuervo, E., Balasubramanian, A., Cho, D., Wolman, A., Saroiu, S., Chandra, R., Bahl, P.: MAUI: Making Smartphones Last Longer with Code Offload. In: MobiSys 2010, San Francisco, California, June 15-18 (2010)Google Scholar
  7. 7.
    Gartner Research – Gartner Says Worldwide Mobile Device Sales Grew 13.8 Percent in Second Quarter of 2010, But Competition Drove Prices Down (August 12, 2010),
  8. 8.
    Gartner Says Worldwide Mobile Device Sales to End Users Reached 1.6 Billion Units in 2010; Smartphone Sales Grew 72 Percent in 2010 (February 9, 2011),
  9. 9.
    McDowall, J.: Memory Effect in Stationary Ni-CD Batteries? Forget about it! In: Battcon 2003 (2003)Google Scholar
  10. 10.
    Oliver, E.: The Challenges in Large-Scale Smartphone User Studies. In: International Conference On Mobile Systems, Applications And Services, Prec. 2nd ACM International Workshop on Hot Topics in Planet-scale Measurement, San Francisco, California (2010)Google Scholar
  11. 11.
    Oliver, E.: A Survey of Platforms for Mobile Networks Research. Mobile Computing and Communications Review 12(4) (2008)Google Scholar
  12. 12.
    Oliver, E., Keshav, S.: Data Driven Smartphone Energy Level Prediction. University of Waterloo Technical Report No. CS-2010-06 (April 15, 2010)Google Scholar
  13. 13.
    Open Handset Alliance, (last accessed February 24, 2011)
  14. 14.
    Ostendorp, P., Foster, S., Calwell, C.: Cellular Phones, Advancements in Energy Efficiency and Opportunities for Energy Savings. NRDC 23 (October 2004)Google Scholar
  15. 15.
    Patel, S.N., Kientz, J.A., Hayes, G.R., Bhat, S., Abowd, G.D.: Farther Than You May Think: An Empirical Investigation of the Proximity of Users to Their Mobile Phones. In: Dourish, P., Friday, A. (eds.) UbiComp 2006. LNCS, vol. 4206, pp. 123–140. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  16. 16.
    Rahmati, A., Qian, A., Zhong, L.: Understanding Human-Battery Interaction on Mobile Phones. In: MobileHCI 2007, Singapore, September 9-12 (2007)Google Scholar
  17. 17.
    Ravi, N., Scott, J., Han, L., Iftode, L.: Context-aware Battery Management for Mobile Phones. In: Sixth Annual IEEE International Conference on Pervasive Computing and Communications (2008)Google Scholar
  18. 18.
    Reddy, S., Mun, M., Burke, J., Estrin, D., Hansen, M., Srivastava, M.: Using Mobile Phones to Determine Transportation Modes. ACM Transactions on Sensor Networks 6(2), article 13 (February 2010)Google Scholar
  19. 19.
    Schmidt, A.D., Peters, F., Lamour, F., Scheel, C., Çamtepe, S.A., Albayrak, S.: Monitoring Smartphones for Anomaly Detection. Mobile Network Applications (2009)Google Scholar
  20. 20.
    Truong, K., Kientz, J., Sohn, T., Rosenzweig, A., Fonville, A., Smith, T.: The Design and Evalution of a Task-Centered Battery Interface. In: Ubicomp 2010 (2010)Google Scholar
  21. 21.
    Zhang, L., Tiwana, B., Dick, R.P., Qian, Z., Mao, Z.M., Wang, Z., Yang, L.: Accurate Online Power Estimation And Automatic Battery Behavior Based Power Model Generation for Smartphones. In: CODES+ISSS 2010, Scottsdale, Arizona, USA, October 24-29 (2010)Google Scholar
  22. 22.
    Zheng, P., Ni, L.M.: Spotlight: The Rise of the Smart Phone, vol. 7(3). IEEE Computer Society, Los Alamitos (March 2006)Google Scholar
  23. 23.
    Zhuang, Z., Kim, K., Singh, J.P.: Improving Energy Efficiency of Location Sensing on Smartphones. In: MobiSys 2010, San Francisco, California, June 15-18 (2010)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Denzil Ferreira
    • 1
    • 2
  • Anind K. Dey
    • 2
  • Vassilis Kostakos
    • 1
  1. 1.Madeira Interactive Technologies InstituteUniversity of MadeiraPortugal
  2. 2.Human-Computer Interaction InstituteCarnegie Mellon UniversityUSA

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