Google scholar arxiv informatics ads IJAIS publications are indexed with Google Scholar, NASA ADS, Informatics et. al.

Call for Paper

-

November Edition 2021

International Journal of Applied Information Systems solicits high quality original research papers for the November 2021 Edition of the journal. The last date of research paper submission is October 15, 2021.

Pervasive Recommender System for Smart Home Environment

Naouar Belghini, Nesrine Gouttaya, Wafaâ Bouab Bennani, Adil Sayouti. Published in Artificial Intelligence

International Journal of Applied Information Systems
Year of Publication: 2016
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors: Naouar Belghini, Nesrine Gouttaya, Wafaâ Bouab Bennani, Adil Sayouti
10.5120/ijais2016451528
Download full text
  1. Naouar Belghini, Nesrine Gouttaya, Wafaâ Bouab Bennani and Adil Sayouti. Pervasive Recommender System for Smart Home Environment. International Journal of Applied Information Systems 10(9):1-7, May 2016. URL, DOI BibTeX

    @article{10.5120/ijais2016451528,
    	author = "Naouar Belghini and Nesrine Gouttaya and Wafaâ Bouab Bennani and Adil Sayouti",
    	title = "Pervasive Recommender System for Smart Home Environment",
    	journal = "International Journal of Applied Information Systems",
    	issue_date = "May 2016",
    	volume = 10,
    	number = 9,
    	month = "May",
    	year = 2016,
    	issn = "2249-0868",
    	pages = "1-7",
    	numpages = 7,
    	url = "http://www.ijais.org/archives/volume10/number9/888-2016451528",
    	doi = "10.5120/ijais2016451528",
    	publisher = "Foundation of Computer Science (FCS), NY, USA",
    	address = "New York, USA"
    }
    

Abstract

Buildings today become complex in terms of structures and advanced technologies. Intelligent buildings are autonomic environment that provide useful services to make occupants lives’ more comfortable (e.g. physical security, automatic lighting, thermal comfort, etc…). Smart buildings use IT systems to connect a variety of independent sub-systems, so that these systems can share information to improve total building performance.

In this paper, we propose an approach that offers the most relevant services to inhabitants according to the contextual information provided by the physical sensors. The proposed approach considers five parameters to represent the contextual information: the user activity (sleeping, walking, sitting down, …), time(morning, afternoon, night, …) localization ( kitchen, living room,..), temperature(warm, cold, hot, …) , special event (ween end, holidays,..) and activate the most adequate service to be applied in a given context of use.

Reference

  1. Das S, Cook D, Battacharya A, Heierman E, Lin T. The role of prediction algorithms in the MavHome smart home architecture. IEEE Trans. On Wireless Communications, 2002,9(6):77–84.
  2. Gopalratnam K, Cook D J. Online sequential prediction via incremental parsing: The Active LeZi algorithm. IEEE Trans. On Intelligent Systems, 2007,22(1):52–58.
  3. Katharina R. Smart assistants for smart homes. Phd Thesis, 2013,Stockholm, Sweden.
  4. Gouttaya N, Belghini N , Begdouri A , Zarghili A. Improving the Proactive Recommendation in Smart Home Environments: An Approach Based on Case Based Reasoning and BP-Neural Network .I.J. Intelligent Systems and Applications, 2015, 07, 29-35.
  5. M. Montaner, B. López , and J. L. De La Rosa,”A Taxonomy of Recommender Agents on the Internet, Artificial Intelligence Review, pp. 285-330,June 2003.
  6. M. Weiser. The computer for the 21st century. On Scientific American, 1991, 265(3): 94-104.
  7. R. Burke,”Hybrid Recommender Systems: Survey and Experiments”,Journal of Personalization Research, User Modeling and User-Adapted Interaction,vol.12 , pp. 331 - 370 , November 2002.
  8. T. Cioara, I. Anghel, I. Salomie, M. Dinsoreanu, G. Copil, and D. Moldovan, “A self-adapting algorithm for context aware systems,” in Roedunet International Conference (RoEduNet), 2010 9th, june 2010, pp. 374 –379.
  9. A K Dey, G D Abowd. “Towards a better understanding of context and context-awareness”. Proceedings of the Workshop on the What, Who, Where, When and How of Context-Awareness. 2000, ACM Press, New York .
  10. J. Coutaz, J. Crowley, S. Dobson, and D. Garlan. “Context is key.” Communications of the ACM 48(3), March 2005.
  11. A. Manzoor, H.Truong, & S.Dustdar. On the Evaluation of Quality of Context. In 3rd European Conference on Smart Sensing and Context pp. 140-153, 2008
  12. A.Held, S. Buchholz and A.Schill. Modeling of context information for pervasive computing applications. In Proceedings of SCI 2002/ISAS, 2002.
  13. Claudio Bettini, Oliver Brdiczka, Karen Henricksen, Jadwiga Indulska, Daniela Nicklas, Anand Ranganathan, Daniele Riboni, "A Survey of Context Modelling and Reasoning Techniques". Journal of Pervasive and Mobile Computing, 6(2):161-180, Elsevier, 2010.
  14. Ye et all., Situation identification techniques in pervasive computing: A review, Pervasive and Mobile Computing (2011), doi:10.1016/j.pmcj.2011.01.004
  15. T. van Kasteren, G. Englebienne, and B. Krose, “Activity recognition using semi-markov models on real world mart home datasets,” J.Ambient Intell. Smart Environ., vol. 2, no. 3, 2010.
  16. T. van Kasteren, G. Englebienne, and B. Kr¨ose, “Transferring knowledge of activity recognition across sensor networks,” in Pervasive, 2010.
  17. E. Hoque and J. Stankovic, “AALO: Activity recognition in smart homes using Active Learning in the presence of Overlapped activities,” in Proc. of IEEE Int. Conf. on Pervasive Computing Technologies for Healthcare, San Diego, CA, 2012.
  18. M. A. Dragan and I. Mocanu, "Human Activity Recognition in Smart Environments," Control Systems and Computer Science (CSCS), 2013 19th International Conference on, Bucharest, 2013, pp. 495-502.
  19. M. A. Dragan and I. Mocanu, "Human Activity Recognition in Smart Environments," Control Systems and Computer Science (CSCS), 2013 19th International Conference on, Bucharest, 2013, pp. 495-502.
  20. R. Agrawal,” Fast algorithms for mining association rules”.Proceeding of the 20th International Conference Very Large Data Bases, pp. 487–499, August 1994.

Keywords

Smart home, pervasive computing, recommender systems, human activity recognition, neural network