Abstract
Smartphones are widely used around the world, which are also equipped with some sensors that can be used for the awareness of their users’ state. These sensors include GPS, accelerometer, and microphone among others. In this paper, we present an empirical way to identify user’s state including daily activity like walking, running, accidental threats like falling-down, and emotional status like sadness, joy, and anger. The monitoring should be realized in a non-intrusive way. We realize this idea by the design and implementation of a comprehensive run time user state monitoring system on Android smartphones, as less instructive as possible. The experiments show that it has good performance in terms of both monitored state accuracy and footprint incurred while conduct monitoring. The evaluations also show that the power consumption of the monitoring system is even neglectable which proves the usability of the proposed monitoring system.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Gomes, J.B., Krishnaswamy, S., Gaber, M.M., Sousa, P.A.C., Menasalvas, E.: Mobile activity recognition using ubiquitous data stream mining. In: Cuzzocrea, A., Dayal, U. (eds.) DaWaK 2012. LNCS, vol. 7448, pp. 130–141. Springer, Heidelberg (2012)
Kwapisz, J., Weiss, G., Moore, S.: Activity recognition using cell phone accelerometers. ACM SIGKDD Explor. Newsl. 12(2), 74–82 (2011)
Lane, N., Miluzzo, E., Lu, H., Peebles, D., Choudhury, T., Campbell, A.: A survey of mobile phone sensing. IEEE Commun. Mag. 48(9), 140–150 (2010)
Mitchell, M., Sposaro, F., Wang, A., Tyson, G.: Beat: bio-environmental android tracking. In: IEEE Radio and Wireless Symposium (RWS) 2011, pp. 402–405. IEEE (2011)
Sönercan, M., Dinçer, S.: User state tracking using smartphones
Sposaro, F., Tyson, G.: iFall: an android application for fall monitoring and response. In: Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2009, pp. 6119–6122. IEEE (2009)
Sun, L., Zhang, D., Li, N.: Physical activity monitoring with mobile phones. In: Abdulrazak, B., Giroux, S., Bouchard, B., Pigot, H., Mokhtari, M. (eds.) ICOST 2011. LNCS, vol. 6719, pp. 104–111. Springer, Heidelberg (2011)
Zhang, S.: Emotion recognition by speech signal in madarin. Doctorate Degree dissertation of China University of Science and Technology (2007)
Zhang, W., Chen, L., Liu, X., et al.: An osgi-based flexible and adaptive pervasive cloud infrastructure. Sci. China Inf. Sci. 57(3), 1–11 (2014). http://dx.doi.org/10.1007/s11432-014-5070-3
Zhang, W., Chen, L., Lu, Q., et al.: Towards an osgi based pervasive cloud infrastructure. In: 2013 IEEE International Conference on and IEEE Cyber, Physical and Social Computing. pp. 418–425. IEEE (2013)
Zhang, W., Chen, L., Lu, Q., Zhang, P., Yang, S.: Flexible component migration in an OSGi based pervasive cloud infrastructure. In: Lomuscio, A.R., Nepal, S., Patrizi, F., Benatallah, B., Brandić, I. (eds.) ICSOC 2013. LNCS, vol. 8377, pp. 505–514. Springer, Heidelberg (2014)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Zhang, W., Wang, X. (2015). A Lightweight User State Monitoring System on Android Smartphones. In: Toumani, F., et al. Service-Oriented Computing - ICSOC 2014 Workshops. Lecture Notes in Computer Science(), vol 8954. Springer, Cham. https://doi.org/10.1007/978-3-319-22885-3_23
Download citation
DOI: https://doi.org/10.1007/978-3-319-22885-3_23
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-22884-6
Online ISBN: 978-3-319-22885-3
eBook Packages: Computer ScienceComputer Science (R0)