Seamless Home Automation with IoT Integration

Abstract

This project focuses on the development of an IoT-based Smart Home Automation System aimed at enhancing user convenience, energy efficiency, and safety within residential environments. The system integrates multiple sensors and an ESP32 microcontroller to monitor and control household appliances intelligently. It supports both manual and automatic modes, enabling users to operate devices through a web-based interface or allowing automated control based on real-time environmental data such as temperature, motion, and gas levels. Core components include the DHT11 temperature sensor, PIR motion sensor, MQ2 gas sensor, and real-time databases like Firebase for device state management and MongoDB for historical logging. The system architecture ensures seamless interaction between hardware and software, offering a scalable, low-cost, and efficient solution for modern smart home applications.

Introduction

The rapid advancement of IoT technologies has propelled the development of smart homes, which integrate connected devices and sensors for remote monitoring, automation, and control of home appliances, enhancing comfort, security, and energy efficiency. This project introduces a low-cost IoT-based smart home automation system using the ESP32 microcontroller. It supports two modes: manual control via a web interface and automatic operation based on sensor data (PIR motion, DHT11 temperature/humidity, MQ2 gas). The system uses Firebase Realtime Database for real-time device state synchronization and MongoDB for long-term data logging and analysis, enabling responsive and data-driven automation.

The architecture consists of a layered model: sensing hardware gathers environmental data, the ESP32 processes inputs and communicates with the cloud, and a React.js frontend offers user control and visualization. Manual mode allows users direct control over devices, while automatic mode triggers devices based on sensor thresholds. The system retains device states to ensure smooth mode transitions.

Key hardware components include:

• ESP32: Central microcontroller with Wi-Fi and Bluetooth, handling sensor data and device control.

• PIR Sensor: Detects motion to automate lighting.

• MQ2 Gas Sensor: Monitors gas leaks for safety alerts.

• DHT11 Sensor: Measures temperature and humidity for climate control.

• LDR: Detects ambient light to optimize lighting usage.

• LEDs and Connecting Wires: For system feedback and hardware integration.

This integrated system improves home convenience, energy conservation, and safety by combining real-time control, sensor-driven automation, and cloud-based data management.

Conclusion

The smart home automation system developed in this project successfully demonstrates the integration of IoT, cloud computing, and web technologies to create a responsive, intelligent, and user-friendly solution for modern living environments. By combining real-time sensor data, Firebase Realtime Database, and a React-based control interface, the system provides seamless control and monitoring of household devices. The dual-mode operation—manual and auto—offers flexibility to users, while the incorporation of logging through MongoDB enables detailed tracking of device usage. The implementation ensures energy efficiency, safety, and remote accessibility, addressing the core challenges faced in home automation. Furthermore, the modular design allows for scalability and future enhancements such as voice control, mobile app development, and AI-driven automation. Overall, this project lays a strong foundation for building advanced smart home ecosystems that are not only efficient and secure but also adaptable to evolving user needs and technological advancements.

References

[1] Evans, C., & Martinez, D. (2023). \"Smart Home Automation using ESP32, Rainmaker, Alexa, and Google Assistant.\" IEEE Transactions on Consumer Electronics, 69(2), 234-243. [2] Foster, J., & Lee, S. (2020). \"A Comparative Study of ESP32 and Raspberry Pi for Home Automation.\" International Journal of Advanced Computer Science and Applications, 11(5), 201-208. [3] Garcia, R., & Adams, M. (2019). \"Integration of ESP32 with Alexa for Smart Home Applications.\" Journal of Intelligent Systems, 25(3), 123-131. [4] Hernandez, L., & White, R. (2021). \"ESP32-based Home Automation System with Rainmaker and Google Assistant Integration.\" International Journal of Engineering and Technology, 13(2), 98-105. [5] Hill, S., & Garcia, R. (2023). \"Voice-Controlled Home Automation System using ESP32 and Alexa with Manual Switching.\" International Journal of Smart Home, 17(1), 67-75.

Copyright

Copyright © 2025 Akash Bhaduri , Md Razique Alam, Abhishek Kumar, Harsh Sah, Md Shizan Yusuf, Arpita Santra. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.