Internet of Things Enabled Intelligent Automation for Smart Home with the Integration of PSO Algorithm and PID Controller

  • Rajesh Singh
  • , Anita Gehlot
  • , Piyush Kuchhal
  • , Sushabhan Choudhury
  • , Shaik Vaseem Akram
  • , Neeraj Priyadarshi
  • , Baseem Khan

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

Currently, due to the widespread population growth, there is a widespread concern about an electricity shortage. As a result, smart devices have evolved and gained significant attention to reduce power consumption in home appliances due to electricity shortages. However, it lacks a universal remote control that can control home appliances based on environmental conditions. To overcome these challenges, this study proposed a hardware-based remote-control system that operates both in autonomous and semiautonomous modes to control home appliances based on environmental conditions. In the autonomous mode, the receiver section regulates the parameters under ambient conditions by varying the appliance's applied voltage levels via a dimmer. The parameters in semiautonomous are monitored by the user via various levels of remote control. A 2.4 GHz RF modem is used to establish wireless personal network (WPAN) communication between the remote and the receiver. In addition, a Wi-Fi modem is built into the receiver to enable internet-based mobile applications to operate appliances. During the MATLAB analysis, a proportional integral derivative (PID) controller with a particle swarm optimization (PSO) method was found as a superior approach to control the home appliance with adequate environmental conditions. It is concluded from the MATLAB study that the PSO-PID controller delivered an energy saving of 14.88% for the heater, 36.9% for the exhaust fan, and 37.49% for the light bulb compared to the conventional appliances.

Original languageEnglish
Article number9611321
JournalJournal of Electrical and Computer Engineering
Volume2023
DOIs
Publication statusPublished - 2023
Externally publishedYes

ASJC Scopus subject areas

  • Signal Processing
  • General Computer Science
  • Electrical and Electronic Engineering

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