Smart Home Automation and Analysis Using Machine Learning

Authors

  • Aman Shukla Student, Department of Electronics and Telecommunication Engineering, K.C. College of Engineering and Management Studies and Research, Thane, India
  • Masoom Shaikh Student, Department of Electronics and Telecommunication Engineering, K.C. College of Engineering and Management Studies and Research, Thane, India
  • Jugal Paswan Student, Department of Electronics and Telecommunication Engineering, K.C. College of Engineering and Management Studies and Research, Thane, India
  • Siddhyant Mishra Student, Department of Electronics and Telecommunication Engineering, K.C. College of Engineering and Management Studies and Research, Thane, India
  • Baban U. Rindhe Assistant Professor, Department of Electronics and Telecommunication Engineering, K.C. College of Engineering and Management Studies and Research, Thane, India

Keywords:

ESP32, Wi-Fi, smart phone, home automation

Abstract

The technologies are moving rapidly towards the automation. Now, people need more comfort and want to do all the things with less efforts and less time and the solution is automation. This research paper aims to develop and design home automation using Esp32 which have inbuild Bluetooth and Wi-Fi module. Home automation with ESP32 is a rapidly growing trend in which household appliances and systems are automated to create a more convenient and efficient living environment. Because of its built-in Wi-Fi and Bluetooth connectivity, low cost, and high versatility, the ESP32 is a powerful microcontroller that is widely used in IoT projects. Overall, home automation with ESP32 is a fun and easy way to make your home more efficient and convenient. As technology advances, ESP32-based home automation systems are expected to become more sophisticated and integrated into our daily lives.

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Published

01-05-2023

Issue

Section

Articles

How to Cite

[1]
A. Shukla, M. Shaikh, J. Paswan, S. Mishra, and B. U. Rindhe, “Smart Home Automation and Analysis Using Machine Learning”, IJMDES, vol. 2, no. 4, pp. 52–56, May 2023, Accessed: Jun. 13, 2024. [Online]. Available: https://journal.ijmdes.com/ijmdes/article/view/131

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