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Related Experiment Video

Updated: Nov 3, 2025

Measuring Light-Switching Behavior Using an Occupancy and Light Data Logger

Measuring Light-Switching Behavior Using an Occupancy and Light Data Logger

Published on: January 16, 2020

Design and Implementation of the E-Switch for a Smart Home.

Fabian García-Vázquez¹, Héctor A Guerrero-Osuna¹, Gerardo Ornelas-Vargas¹

¹Unidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, Zacatecas 98000, Mexico.

Sensors (Basel, Switzerland)

|June 2, 2021

Summary

This study introduces an Internet of Things platform for smart home energy management. It enables remote control and monitoring of Wi-Fi e-switches, paving the way for intelligent resource utilization.

Keywords:

IoT device internet of things smart home

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Area of Science:

Computer Science
Electrical Engineering
Smart Home Technology

Background:

Increasing development of smart home systems necessitates effective data utilization for energy management.
Artificial intelligence (AI) methods can analyze data to recognize patterns, detect anomalies, and optimize energy consumption in domestic services.

Purpose of the Study:

To design and implement an Internet of Things (IoT) based platform for smart home energy management.
To enable remote control and monitoring of Wi-Fi wireless electronic switches (e-switches) via a mobile application.
To lay the foundation for transforming conventional homes into smart homes through data collection and analysis.

Main Methods:

Development of a cloud-based platform integrating IoT devices.
Implementation of a mobile application for user interaction.
Remote control and monitoring capabilities for Wi-Fi wireless e-switches.

Main Results:

Successful design and implementation of the IoT platform.
Enabled remote monitoring and control of home e-switches.
Established a system for collecting and storing e-switch data for future analysis.

Conclusions:

The developed platform represents a significant first step towards smart home integration.
The collected e-switch data can be leveraged for advanced AI-driven energy management strategies.
This system offers users enhanced control over home resources and contributes to energy reduction efforts.