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Licensed Unlicensed Requires Authentication Published by De Gruyter October 12, 2022

Intelligent home control system based on BP neural network speech recognition

  • Ruini Liu ORCID logo EMAIL logo

Abstract

With the rapid progress and wide application of cutting-edge technologies such as automatic control technology and wireless communication technology in recent years, smart home, as an effective combination of these cutting-edge technologies and daily life, has received more and more attention and Research has been greatly developed. In order to solve the shortcomings of the existing home control need to download various cumbersome APP, the WeChat applet is introduced into the smart home system, and the intelligent voice technology is planned to be used in the smart home control to realize the voice control, improve the user experience and make the home Life gets smarter. This time, the deep learning technology was used in the development process of the smart home control system, and according to the historical information of the home, combined with the learning ability of the recurrent neural network for time series data, through the mining, analysis and learning of historical data, the construction based on specific The user’s unique computing model can seamlessly connect the capabilities of the voice cloud platform with the capabilities of the Internet of Things cloud platform through the Web server, making it possible to quickly access the voice recognition capabilities to smart homes. The entire system has stable connectivity, easy deployment and low cost. The main functions are deployed in the cloud and extended. After 10 rounds of iterative training of the Attention-GRU model in this paper, its prediction accuracy can quickly rise to about 97%, and finally stabilize at about 98.2%, and the lighting prediction accuracy can reach 95% or higher.


Corresponding author: Ruini Liu, College of Information Engineering, Xi'an Mingde Institute Technology, Xi’ an 710124, Shaanxi, China, E-mail:

Funding source: Artificial intelligence technology application research team of Xi’an Fanyi University

Award Identifier / Grant number: XFU21KYTDB02

  1. Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: This work was supported by Artificial intelligence technology application research team of Xi’an Fanyi University (No. XFU21KYTDB02).

  3. Conflict of interest statement: The authors declare no conflicts of interest regarding this article.

References

1. Min, C, Yang, J, Xuan, Z, Wang, X, Liu, M, Song, J. Smart home 2.0: innovative smart home system powered by botanical IoT and emotion detection. Mobile Network Appl 2017;22:1159–69.10.1007/s11036-017-0866-1Search in Google Scholar

2. Tang, S, Kalavally, V, Ng, KY, Parkkinen, J. Development of a prototype smart home intelligent lighting control architecture using sensors onboard a mobile computing system. Energy Build 2017;138:368–76.10.1016/j.enbuild.2016.12.069Search in Google Scholar

3. Oukrich, N, Bouazzaoui, CE, Maach, A, Driss, E. Human activities recognition based on autoencoder pre-training and back-propagation algorithm. J Theor Appl Inf Technol 2017;95:5194–202.Search in Google Scholar

4. Melhem, FY, Grunder, O, Hammoudan, Z. Optimization and energy management in smart home considering photovoltaic, wind, and battery storage system with integration of electric vehicles. Can J Electr Comput Eng 2017;40:128–38, https://doi.org/10.1109/cjece.2017.2716780.Search in Google Scholar

5. Gunawan, TS, Gani, M, Rahman, F, Kartiwi, M. Development of face recognition on Raspberry Pi for security enhancement of smart home system. Indones J Electr Eng Inf 2017;5:317–25.Search in Google Scholar

6. Ma, C. Analysis of applications and technologies for smart home system. Int J Comput Intell Res 2019;15:33–45.Search in Google Scholar

7. Filho, GPR, Villas, LA, Freitas, H, Valejo, A. ResiDI: towards a smarter smart home system for decision-making using wireless sensors and actuators. Comput Network 2018;135:54–69.10.1016/j.comnet.2018.02.009Search in Google Scholar

8. Marrapu, S, Satyanarayana, S, Arunkumar, V. Smart home based security system for door access control using smart phone. Int J Eng Technol 2018;7:249–51, https://doi.org/10.14419/ijet.v7i1.9247.Search in Google Scholar

9. Wong, J, Leung, J, Skitmore, M. Technical requirements of age-friendly smart home technologies in high-rise residential buildings: a system intelligence analytical approach. Autom ConStruct 2017;73:12–9, https://doi.org/10.1016/j.autcon.2016.10.007.Search in Google Scholar

10. Augustine, A, Gambo, Y. Construction and implementation of smart home system. Int J Comput Appl 2020;176:15–7, https://doi.org/10.5120/ijca2020920031.Search in Google Scholar

11. Luo, J. A Zigbee and sip-based smart home system design and implementation. Int J Online Eng 2017;13:42.10.3991/ijoe.v13i01.6258Search in Google Scholar

12. Alvarez, R, Araque, J, Sierra, JE. A novel smart home energy management system: architecture and optimization model. Indian J Sci Technol 2017;10:1–8, https://doi.org/10.17485/ijst/2017/v10i26/110684.Search in Google Scholar

13. Artono, B, Susanto, F. Wireless smart home system menggunakan internet of things. J Teknol Informasi dan Terap 2019;5:17–24, https://doi.org/10.25047/jtit.v5i1.74.Search in Google Scholar

14. Kotsiubivska, K, Prisych, V, Yavorskyi, O. lmplementation of internet technologies of things when creating a smart home system. Digit Platform Inf Technol Sociocult Sphere 2019;2:136–43.Search in Google Scholar

15. Purnawan, PW, Rosita, Y. Rancang bangun smart home system Menggunakan NodeMCU Esp8266 berbasis Komunikasi Telegram Messenger. Tech Commun 2019;18:348–60, https://doi.org/10.33633/tc.v18i4.2862.Search in Google Scholar

16. Ivanov, R, Ivanov, V, Bande, CM. Energy efficiency in smart home system. Int J Sci Res Publi 2020;10:683–8, https://doi.org/10.29322/ijsrp.10.09.2020.p10581.Search in Google Scholar

17. Nasyarudin, AF, Ritzkal, Goeritno, A. Prototipe Perangkat untuk Pemantauan dan Pengendalian Berbasis Web Diiintegrasikan ke Smarthome System. Indones J Electron Instrumen Syst 2020;10:167–78, https://doi.org/10.22146/ijeis.58316.Search in Google Scholar

18. Augustine, A, Gambo, Y. Construction and implementation of smart home system. Int J Comput Appl 2020;176:15–7, https://doi.org/10.5120/ijca2020920031.Search in Google Scholar

19. Alkhafaf, OS, Wali, MK, Al-Timemy, AH. Improved hand prostheses control for transradial amputees based on hybrid of voice recognition and electromyography. Int J Artif Organs 2021;44:509–17, https://doi.org/10.1177/0391398820976656.Search in Google Scholar PubMed

20. Zanwar, SR, Vaidya, NS, Mohite, JN, Nakrani, MG. Voice recognition based device control system using smartphone app. Int J Adv Res Comput Sci Manag 2021;6:54–60.Search in Google Scholar

21. Gul, M, Bayrak, U. A smart home system based on microcontroller using android application and MySQL database. Acad Perspect Procedia 2020;3:455–64, https://doi.org/10.33793/acperpro.03.01.90.Search in Google Scholar

22. Lasera, AB, Wahyudi, IH. Smart Home System dengan Kontrol Daya Listrik berbasis IoT. Electron Inf Vocat Educ 2021;5:132–40, https://doi.org/10.21831/elinvo.v5i2.34261.Search in Google Scholar

23. Akhinov, IA, Cahyono, M. Pengembangan Smart Home System Berbasis Kecerdasan Buatan untuk Memanajemen Konsumsi Energi Rumah Tangga dengan Pendekatan Finansial. J Sci Appl Inf 2021;4:1–10, https://doi.org/10.36085/jsai.v4i1.1218.Search in Google Scholar

24. Rui, H, Gao, C. Neural network-based urban green vegetation coverage detection and smart home system optimization. Arabian J Geosci 2021;14:1–17, https://doi.org/10.1007/s12517-021-07463-y.Search in Google Scholar

Received: 2022-04-27
Accepted: 2022-08-14
Published Online: 2022-10-12

© 2022 Walter de Gruyter GmbH, Berlin/Boston

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