Abstract
With the rapid growth of ICT, almost all the entities exist in this world are moving towards computing enabled digital space. At present, the computing infrastructure is not only an infrastructure for scientific computation and communication, but also it has been considered as a platform for computation of anything appearing at anytime and anywhere. One of such computing platform is smart environment (SE); which is an intelligent physical environment equipped with different types of hardware and network tools & technologies in order to sense and interpret the present context of the environment so that proactive services can be delivered to the users/inhabitants for making the inhabitants lives more comfortable. Researches in different directions at different levels in the domain of SE are currently becoming very popular in the minds of researchers. This work is also such kind of research work wherein the mechanism for intelligent control of the devices through learning has been considered. Learning is the major attribute to be incorporated in a SE through which the environment will be able to understand about the preferences of the status of the devices for a specific inhabitant at a given time. In this regard, this work tried to find out the mechanism to enable the learning feature by proposing a data structure. Working concept of the proposed data structure and running time analysis of the same also have been placed in this paper along with its required procedures. Experiments also have been performed for evaluating the proposed mechanism.
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References
Weiser, M.: The computer for the twenty-first century. Sci. Am. 94–100 (1991)
Cook, D.J., Das, S.K.: Smart Environments: Technology, Protocols and Applications. (Wiley Series on Parallel and Distributed Computing). Wiley, Hoboken (2004)
Kidd, C: The aware home: a living laboratory for ubiquitous computing research. In: Proceedings of 2nd International Workshop on Cooperative Buildings, pp. 190–197 (1999)
Kientz, J.A., Patel, S.N., Jones, B., Price, E., Mynatt, E.D., Abowd, G.D.: The Georgia Tech aware home. In: Extended Abstracts of the Conference on Human Factors in Computing Systems (CHI 2008), pp. 3675–3680 (2008)
Holmes, A., Duman, H., Pounds-Cornish, A.: The iDorm: Gateway to heterogeneous networking environments. In: Proceedings of International Test and Evaluation Association (ITEA) Workshop on Virtual Home Environments, pp. 30–37 (2002)
Cook, D., Youngblood, M., Heierman, E., Gopalratnam, K., Rao, S., Litvin, A., Khawaja, F.: MavHome: an agent-based smart home. In: Proceedings of the First IEEE International Conference on Pervasive Computing and Communications (PerCom 2003), pp. 521–524 (2003)
Youngblood, G., Cook, D.J., Holder, L.: The MavHome architecture. In: Technical Report CSE-2004-18, University of Texas at Arlington (2004)
Helal, S., Mann, W., El-Zabadani, H., King, J., Kaddoura, Y., Jansen, E.: The Gator Tech Smart House: a programmable pervasive space. Computer 38(3), 50–60 (2005)
Cook, D.J., Crandall, A.S., Thomas, B.L., Krishnan, N.C.: CASAS: a smart home in a box. Computer 46(7), 62–69 (2013)
Heierman, E.O., Cook, D.J.: Improving home automation by discovering regularly occurring device usage patterns. In: Proceedings of the 3rd IEEE International Conference on Data Mining (ICDM), FL, USA (2003)
Coble, J., Cook, D., Holder, L., Rathi, R.: Structure discovery from sequential data. In: Proceedings of the 17th International Florida Artificial Intelligence Research Society Conference, USA (2004)
Jakkula, V. R., Cook, D. J.: Using temporal relations in smart environment data for activity prediction. In: Proceedings of the 24th International Conference on Machine Learning (2007)
Hussain, S., Schaffner, S., Moseychuck, D.: Applications of wireless sensor networks and RFID in a smart home environment. In: Proceedings of Seventh Annual Communications Networks and Services Research Conference (2009)
Hsu, H., Lee, C., Chen, Y.: An RFID-based reminder system for smart home. In: Proceedings of the IEEE International Conference on Advanced Information Networking and Applications (AINA), pp. 264–269, Singapore (2011)
Kumar, S., Qadeer, M.A.: Application of AI in home automation. Int. J. Eng. Technol. 4(6), 803–807 (2012)
Akter, S.S., Holder, L.B.: Activity recognition using graphical features. In: Proceedings of 13th International Conference on Machine Learning and Applications (ICMLA), pp. 165–170 (2014)
Twomey, N., Diethe, T., Flach, P.: Unsupervised Learning of Sensor Topologies for Improving Activity Recognition in Smart Environments. Neurocomputing-2017 234, 93–106 (2017)
Acknowledgement
The expenditure for participating in the conference including travel allowance is supported through the faculty and staff development grant under TEQIP III project of GUIST. We are thankful for the support.
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Deka, V., Sarma, S.K. (2020). A New Design Prospective for User Specific Intelligent Control of Devices in a Smart Environment. In: Abraham, A., Cherukuri, A.K., Melin, P., Gandhi, N. (eds) Intelligent Systems Design and Applications. ISDA 2018 2018. Advances in Intelligent Systems and Computing, vol 940. Springer, Cham. https://doi.org/10.1007/978-3-030-16657-1_74
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