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IOT Based Home Automation System Through Adaptive Decision Making Fuzzy Algorithm
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Real time automation is increasingly gets popular due to its flexibility in utilizing open source tool and adapting the new node without any complexity in programming. This paper proposes the human machine interface through context aware and decision support system using distance based fuzzy algorithm which utilizes the user’s domain knowledge to frame the rules. The developed system is based on Linux OS and the algorithm is developed in python and results were stored in internet by FHEM API, used in Raspberry Pi B+ kit which is an IoT application and the mobile SSH settings using Wi-Fi modem. Using this app we can access through home automation systems by connecting IP address of the web server and also voice assisted module helps the patients to control the appliance through voice control. Effective algorithmic decision making and voice assisted automation produces the better result in automating the things in real world.
Keywords
Real Time Automation, Human Machine Interface, Decision Support System, FHEM API, Raspberry Pi B+, Voice Control.
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- K. Mukendi and M. Adonis, "The development of a remotely controlled home automation system for energy saving," 2017 International Conference on the Domestic Use of Energy (DUE), Cape Town, 2017, pp. 265-270.
- P. Padmavathi and M. Mathankumar (2015, April) “An Enhanced Approach on Secured Data Communication Using Mobile Relay Node in Wireless Sensor Network” International Journal of Applied Engineering Research, Vol. 10 No.20. https://www.ripublication.com/Volume/ijaerv10n20spl.htm
- C. Mohanraj et al. (2013) “Design and development of secret session key generation using embedded crypto device – ARM-LPC2148”, Journal of Artificial Intelligence, vol. 6 (2).http://scialert.net/abstract/?doi=jai.2013.134.144.
- S. Kim, H. Cho, T. Yang, C. Kim and S. H. Kim, "Low-Cost Multipath Routing Protocol by Adapting Opportunistic Routing in Wireless Sensor Networks," 2017 IEEE Wireless Communications and Networking Conference (WCNC), San Francisco, CA, 2017, pp. 1-6.
- A. C. Jose and R. Malekian, "Improving Smart Home Security: Integrating Logical Sensing Into Smart Home," in IEEE Sensors Journal, vol. 17, no. 13, pp. 4269-4286, July1, 1 2017.
- S. Jain, A. Vaibhav and L. Goyal, "Raspberry Pi based interactive home automation system through E-mail," 2014 International Conference on Reliability Optimization and Information Technology (ICROIT), Faridabad, 2014, pp. 277-280.
- G. D. Abowd, A. K. Dey, R. Orr and J. Brotherton, "Contextawareness in wearable and ubiquitous computing," Digest of Papers. First International Symposium on Wearable Computers, Cambridge, MA, USA, 1997, pp. 179-180.
- G. D. Abowd, A. K. Dey, R. Orr and J. Brotherton, "Context-awareness in wearable and ubiquitous computing," Digest of Papers. First International Symposium on Wearable Computers, Cambridge, MA, USA, 1997, pp. 179-180.
- Y. Evchina, A. Dvoryanchikova and J. L. Martinez Lastra, "Semantic information management for user and context aware smart home with social services," 2013 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA), San Diego, CA, 2013, pp. 262-268. doi: 10.1109/CogSIMA.2013.6523856
- P. TalebiFard and V. C. M. Leung, “A data fusion approach to context-aware service delivery in heterogeneous network environments,” Procedia Comput. Sci., vol. 5, pp. 312–319, 2011.
- R. Schafer, “Rules for using multi-attribute utility theory estimating a user’s interests,” in Proc. Workshop Adaptivity User Modell, 2001.
- X. Wang, D. Rosenblum, and Y. Wang, “Context-aware mobile music recommendation for daily activities,” in Proc. 20th ACM Int.Conf. Multimedia, Nara, Japan, pp. 99–108, 2012.
- A. Al-Hmouz, J. Shen, R. Al-Homouz, and J. Yan, “Modeling and simulation of an adaptive neuro-fuzzy interface system (ANFIS) for mobile learning,” IEEE Trans. Learning Technol., vol. 5, no. 3, pp. 226–237, Jul.–Sep. 2012.
- Q. Duan, D. Miao, H. Zhang, and J. Zheng, “Personalized web retrieval based on rough-fuzzy method,” J. Comput. Inform. Syst., vol. 3, no. 2, pp. 203–208, 2007.
- G. Acampora, M. Gaeta, V. Loia, and A. V. Vasilakos, “Interoperable and adaptive fuzzy service for ambient intelligence applications,” ACM Trans. Autonomous Adaptive Syst., vol. 5, no. 2, pp. 1–26, 2010.
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