AI-Driven Smart Home Automation: Enhancing Energy Efficiency, Security, and User Comfort

Abstract

This review paper presents the development of a smart home automation system designed to improve energy management, security, and user convenience. The system is built using a Raspberry Pi and Python, allowing users to remotely monitor and control household appliances, such as lights, fans, air conditioners, and TVs, through any web browser on the local network without the need for additional software.
The system works in two main stages. The first stage uses IoT devices and sensors—including temperature and humidity sensors (DHT11), gas sensors (MQ2), and ultrasonic distance sensors (HC-SR04)—to monitor the home environment and control appliances in real time. Data is transmitted via the Zigbee protocol to Arduino and Raspberry Pi microcontrollers, while relays safely manage high-voltage devices. A web and mobile interface allows users to easily interact with the system.
The second stage uses a linear regression model to analyze historical data, enabling the system to anticipate user behavior and automatically optimize energy use. Additionally, the system incorporates security features, including video monitoring, face detection, and recognition, with alerts sent securely via email and mobile notifications. Local processing and encrypted cloud storage protect user privacy.
This approach offers a practical, scalable, and cost-effective solution for smart home management, providing energy efficiency, personalized automation, and enhanced security, with potential for future improvements such as voice control and broader device integration.