Awareness Home Automation System Based on User Behavior through Mobile Sensing

  • Rischan MafrurEmail author
  • M. Fiqri Muthohar
  • Gi Hyun Bang
  • Do Kyeong Lee
  • Deokjai Choi
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 330)


This paper proposed awareness home automation system (HAS) based on mobile sensing. Some of the ideas have been proposed in HAS but most of them still requires human intervention such as click the button, voice commands, etc. We want to design and develop HAS which can understand and comprehend the user desires without having to wait for commands from the user (awareness HAS). In this research we exploit two of android sensors. First, accelerometer sensor for identification and activity recognition, second, magnetic field for user indoor positioning system and defined the context related to physical environment. This paper presenting the result of used both of the sensors for developing awareness HAS.


Mobile sensing awareness home automation system 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Efendi, A.M., Oh, S., Negara, A.F.P., Choi, D.: Battery-less 6lowpan-based wireless home automation by use of energy harvesting. International Journal of Distributed Sensor Networks 2013 (2013)Google Scholar
  2. 2.
    Pinker, S.: The Language Instinct. Perennial Modern Classics, Harper (2007)Google Scholar
  3. 3.
    Sharma, U., Reddy, S.: Design of home/office automation using wireless sensor network. International Journal of Computer Applications 43(22) (April 2012)Google Scholar
  4. 4.
    Sun, Q., Yu, W., Kochurov, N., Hao, Q., Hu, F.: A multi-agent-based intelligent sensor and actuator network design for smart house and home automation. Journal of Sensor and Actuator Networks (2013)Google Scholar
  5. 5.
    Han, D.-M., Lim, J.-H.: Design and implementation of smart home energy management systems based on zigbee. IEEE Transactions 56(3) (2010)Google Scholar
  6. 6.
    Assaf, M.H., Mootoo, R., Das, S.R., Petriu, E.M., Groza, V., Biswas, S.: Sensor based home automation and security system. In: 2012 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), May 13-16 (2012)Google Scholar
  7. 7.
    Ali Fahmi, P.N., Kodirov, E., Ardiansyah, D.C., Gueesang, L.: Hey home, open your door, i’m back! authentication system using ear biometrics for smart home. International Journal of Smart Home 7(1) (2014)Google Scholar
  8. 8.
    Das, S.R., Chita, S., Peterson, N., Shirazi, B.A., Bhadkamkar, M.: Experimental evaluation of speech recognition technologies for voice-based home automation control in a smart home. In: 4th Workshop on Speech and Language Processing for Assistive Technologies, French, August 21-22 (2013)Google Scholar
  9. 9.
    Ramlee, R.A., Leong, M.H., Singh, R.S.S., Ismail, M.M., Othman, M.A., Sulaiman, H.A., Misran, M.H., Said, M.: Bluetooth remote home automation system using android application. The International Journal of Engineering And Science (IJES) 2(1) (2014)Google Scholar
  10. 10.
    Thang, H.M., Viet, V.Q., Thuc, N.D., Choi, D.: Gait Identification Using Accelerometer on Mobile Phone. In: ICCAIS (2012)Google Scholar
  11. 11.
    Kwon, Y., Kang, K., Bae, C.: Unsupervised learning for human activity recognition using smartphone sensors. Journal Expert Systems with Applications 41 (2014)Google Scholar
  12. 12.
    Banos, O., Damas, M., Pomares, H., Prieto, A., Rojas, I.: Daily living activity recognition based on statistical feature quality group selection. Journal Expert Systems with Applications 39 (2012)Google Scholar
  13. 13.
    Khan, A.M., Tufail, A., Khattak, A.M., Laine, T.H.: Activity recognition on smartphones via sensor-fusion and kda-based svms. International Journal of Distributed Sensor Networks 2014 (2014)Google Scholar
  14. 14.
    Yun, K., Jo, Y., Kim, N., Jo, U., Kim, Y.: Experimental performance evaluation of a simple indoor positioning scheme with two commonly used sensors. In: SERSC Proceedings 2013 (2013)Google Scholar
  15. 15.
    Li, B., Gallagher, T., Rizos, C., Dempster, A.G.: Using geomagnetic field for indoor positioning. In: International Global Navigation Satellite Systems Society IGNSS Symposium 2013, Australia, (2013)Google Scholar
  16. 16.
    Galvan-Tejada, C.E., Garcia-Vazquez, J.P., Brena, R.F.: Magnetic field feature extraction and selection for indoor location estimation. Sensors 2014 (2014) ISSN 1424-8220; CODEN: SENSC9Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Rischan Mafrur
    • 1
    Email author
  • M. Fiqri Muthohar
    • 1
  • Gi Hyun Bang
    • 1
  • Do Kyeong Lee
    • 1
  • Deokjai Choi
    • 1
  1. 1.School of Electronics and Computer EngineeringChonnam National UniversityGwangjuSouth Korea

Personalised recommendations