IRO Journals
Journal of Electrical Engineering and Automation

Intelligent Smart Home Control Using NLP

Open Access
Published: 09 May, 2026
Pages: 118-134
  • Rizwani G. , Rizwani G.
    Assistant Professor, Department of Electronics and Communication Engineering, Malla Reddy College of Engineering, Secundrabad, Telangana, India
    Assistant Professor, Department of Electronics and Communication Engineering, Malla Reddy College of Engineering, Secundrabad, Telangana, India
  • Ramakumar N. , Ramakumar N.
    Assistant Professor, Department of Electronics and Communication Engineering, ACEM, Aditya College of Engineering, Madanapalle, India
    Assistant Professor, Department of Electronics and Communication Engineering, ACEM, Aditya College of Engineering, Madanapalle, India
  • Shaik Mohammad Ali , Shaik Mohammad Ali
    Assistant Professor, Department of Electronics and Communication Engineering, Kuppam Engineering College, Kuppam, India
    Assistant Professor, Department of Electronics and Communication Engineering, Kuppam Engineering College, Kuppam, India
  • Ajay Kumar Reddy P. Ajay Kumar Reddy P.
    Associate Professor, Department of Electronics and Communication Engineering, Kuppam Engineering College, Kuppam, India
    Associate Professor, Department of Electronics and Communication Engineering, Kuppam Engineering College, Kuppam, India
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How to Cite

G., Rizwani, Ramakumar N., Shaik Mohammad Ali, and Ajay Kumar Reddy P. 2026. “Intelligent Smart Home Control Using NLP”. Journal of Electrical Engineering and Automation 8 (2): 118-34. https://doi.org/10.36548/jeea.2026.2.004.
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Keywords

Smart Home
IoT
NLP - Natural Language Processing
Voice Commands
Text Commands
Secure Home
Intelligent Smart Home

Abstract

The present research suggests an innovative smart home automation system using NLP and IoT technology, providing efficient control of household appliances through voice and text instructions. This system combines an NLP module with the Home module, offering natural communication between humans and devices without the need for pre-defined command set. The NLP module takes up the user commands by applying speech recognition, tokenization, intent classification, and entity extraction algorithms, whereas the Home module controls the appliances via Arduino UNO with the use of relays. Real time control of light, fan, and door in household environment becomes possible through text or voice communication. Experiments show that this approach is efficient in increasing the user convenience and accessibility, while decreasing dependence on complicated interfaces. The proposed intelligent automated control system is cost-effective to future intelligent smart home systems.

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